Effect of feed size on residence time and energy consumption in a stirred mill: An attainable region method

2021 ◽  
Vol 379 ◽  
pp. 485-493
Author(s):  
Wang Guo ◽  
Yuexin Han ◽  
Peng Gao ◽  
Yanjun Li ◽  
Zhidong Tang
Keyword(s):  
Energy Consumption ◽  
Residence Time ◽  
Region Method ◽  
Attainable Region ◽  
Time And Energy

scholarly journals Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model

2021 ◽  
Author(s):  
Ahmad Reza Jafarian-Moghaddam
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Pollutant Emissions ◽  
Scheduling Problems ◽  
Train Scheduling ◽  
Multi Objective ◽  
Consumption Ratio ◽  
Proposed Model ◽  
Objective Model ◽  
Time And Energy

AbstractSpeed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality, thereby improving railroad capacity and railway stakeholders’ satisfaction and revenues. However, a rise in speed leads to more energy consumption, costs, and thus, more pollutant emissions. Therefore, determining an economic speed, which requires a trade-off between the user’s expectations and the capabilities of the railway system in providing tractive forces to overcome the running resistance due to rail route and moving conditions, is a critical challenge in railway studies. This paper proposes a new fuzzy multi-objective model, which, by integrating micro and macro levels and determining the economical speed for trains in block sections, can optimize train travel time and energy consumption. Implementing the proposed model in a real case with different scenarios for train scheduling reveals that this model can enhance the total travel time by 19% without changing the energy consumption ratio. The proposed model has little need for input from experts’ opinions to determine the rates and parameters.

scholarly journals Trade-Off between Operating Time and Energy Consumption in Pulsed Electric Field Electrodialysis: A Comprehensive Simulation Study

Membranes ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 43
Author(s):  
Manuel César Martí-Calatayud ◽  
Mario Sancho-Cirer Poczatek ◽  
Valentín Pérez-Herranz
Keyword(s):  
Energy Consumption ◽  
Electric Field ◽  
Simulation Study ◽  
Specific Energy ◽  
Operating Time ◽  
Specific Energy Consumption ◽  
Threshold Value ◽  
Pulsed Electric Field ◽  
Pulse Frequency ◽  
Time And Energy

Electrodialysis (ED) has been recently introduced in a variety of processes where the recovery of valuable resources is needed; thus, enabling sustainable production routes for a circular economy. However, new applications of ED require optimized operating modes ensuring low energy consumptions. The application of pulsed electric field (PEF) electrodialysis has been demonstrated to be an effective option to modulate concentration polarization and reduce energy consumption in ED systems, but the savings in energy are usually attained by extending the operating time. In the present work, we conduct a comprehensive simulation study about the effects of PEF signal parameters on the time and energy consumption associated with ED processes. Ion transport of NaCl solutions through homogeneous cation-exchange membranes is simulated using a 1-D model solved by a finite-difference method. Increasing the pulse frequency up to a threshold value is effective in reducing the specific energy consumption, with threshold frequencies increasing with the applied current density. Varying the duty cycle causes opposed effects in the time and energy usage needed for a given ED operation. More interestingly, a new mode of PEF functions with the application of low values of current during the relaxation phases has been investigated. This novel PEF strategy has been demonstrated to simultaneously improve the time and the specific energy consumption of ED processes.

Joint Optimization Offloading Strategy of Execution Time and Energy Consumption of Mobile Edge Computing

2021 ◽  
Vol 18 (5) ◽  
Author(s):  
Qingzhu Wang ◽  
Xiaoyun Cui
Keyword(s):  
Energy Consumption ◽  
Mobile Devices ◽  
Execution Time ◽  
Optimal Solution ◽  
Computation Offloading ◽  
Joint Optimization ◽  
Random Strategy ◽  
Fitness Value ◽  
Cloud Server ◽  
Time And Energy

As mobile devices become more and more powerful, applications generate a large number of computing tasks, and mobile devices themselves cannot meet the needs of users. This article proposes a computation offloading model in which execution units including mobile devices, edge server, and cloud server. Previous studies on joint optimization only considered tasks execution time and the energy consumption of mobile devices, and ignored the energy consumption of edge and cloud server. However, edge server and cloud server energy consumption have a significant impact on the final offloading decision. This paper comprehensively considers execution time and energy consumption of three execution units, and formulates task offloading decision as a single-objective optimization problem. Genetic algorithm with elitism preservation and random strategy is adopted to obtain optimal solution of the problem. At last, simulation experiments show that the proposed computation offloading model has lower fitness value compared with other computation offloading models.

Secured data aggregation in wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (3) ◽  
pp. 369-375 ◽  
Author(s):  
Sathya D. ◽  
Ganesh Kumar P.
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Computation Time ◽  
Wireless Sensor ◽  
Content Type ◽  
Homomorphic Cryptosystem ◽  
Secured Data ◽  
Time And Energy

PurposeThis study aims to provide a secured data aggregation with reduced energy consumption in WSN. Data aggregation is the process of reducing communication overhead in wireless sensor networks (WSNs). Presently, securing data aggregation is an important research issue in WSNs due to two facts: sensor nodes deployed in the sensitive and open environment are easily targeted by adversaries, and the leakage of aggregated data causes damage in the networks, and these data cannot be retrieved in a short span of time. Most of the traditional cryptographic algorithms provide security for data aggregation, but they do not reduce energy consumption.Design/methodology/approachNowadays, the homomorphic cryptosystem is used widely to provide security with low energy consumption, as the aggregation is performed on the ciphertext without decryption at the cluster head. In the present paper, the Paillier additive homomorphic cryptosystem and Bonehet al.’s aggregate signature method are used to encrypt and to verify aggregate data at the base station.FindingsThe combination of the two algorithms reduces computation time and energy consumption when compared with the state-of-the-art techniques.Practical implicationsThe secured data aggregation is useful in health-related applications, military applications, etc.Originality/valueThe new combination of encryption and signature methods provides confidentiality and integrity. In addition, it consumes less computation time and energy consumption than existing methods.

scholarly journals Superabundant design

2016 ◽  
Vol 5 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pablo R. Velasco González
Keyword(s):  
Energy Consumption ◽  
Production Rate ◽  
Electronic Devices ◽  
Production Cycle ◽  
Trace Back ◽  
The Creation ◽  
Definition Of ◽  
Time And Energy

Tiziana Terranova draws attention to the necessity of questioning how algorithmically enabled automation works “in terms of control and monetization” and “what kind of time and energy” is being subsumed by it (Terranova 387). Cryptocurrencies are payment technologies that automate the production of money-like tokens (Bergstra and Weijland) following algorithmic rules to maintain a fixed production rate. Different kinds of energy and residues, which are not always acknowledged, are involved in this process. Here I distinguish between two closely linked layers in the Bitcoin token production: first, an algorithmic layer, which contains the instructions and rules for the creation of bitcoins; second, a hardware layer, which performs and embodies the former. While these layers work together, I will argue that they enact their own kind of logics of energy and waste. I will begin at the more visible end of the production cycle, the hardware layer, where the definition of waste and energy consumption is shared with many electronic devices; then I will trace back its algorithmic layer, which as I argue, follows a different logic.

Meso-mechanics simulation analysis of microwave-assisted mineral liberation

2015 ◽  
Author(s):  
Qin Like ◽  
Dai Jun ◽  
Yuan Liqun
Keyword(s):  
Energy Consumption ◽  
Microwave Irradiation ◽  
Power Density ◽  
Microwave Power ◽  
Mineral Content ◽  
Crystal Size ◽  
Irradiation Time ◽  
Mineral Crystal ◽  
Microwave Assisted ◽  
Time And Energy

Microwave-assisted crushing and grinding can improve efficiency and reduce energy consumption. This paper takes rock grains with galena and calcite as the research object to establish a two-dimensional computational model through the finite difference software FLAC2D. It analyzes the process and law of mineral boundary failure under microwave irradiation, and assesses the effects of four factors, namely, microwave irradiation time, power density, mineral crystal size, and mineral content, on mineral boundary failure. Results indicate an optimal microwave irradiation period for the rapid failure of mineral boundary. Moreover, irradiation time and energy consumption can be reduced by increasing the microwave power density. However, irradiation time and energy consumption are basically unchanged when the microwave power density is above a certain threshold. Mineral content slightly affects the microwave irradiation time, whereas mineral crystal size significantly affects the microwave irradiation time. In addition, a larger-sized mineral crystal requires less irradiation time and energy consumption to reach the same failure rate. However, irradiation time and energy consumption slightly change when the crystal size is larger than a certain value.

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