scholarly journals A frequency-amplitude coordinator and its optimal energy consumption for biological oscillators

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bo-Wei Qin ◽  
Lei Zhao ◽  
Wei Lin
Keyword(s):  
Energy Consumption ◽  
Optimal Energy ◽  
Biological Oscillators ◽  
Practical Usefulness ◽  
Universal Approach ◽  
Single Well ◽  
Gene Regulatory ◽  
First Time ◽  
Regulatory Models ◽  
Fundamental Mechanism

AbstractBiorhythm including neuron firing and protein-mRNA interaction are fundamental activities with diffusive effect. Their well-balanced spatiotemporal dynamics are beneficial for healthy sustainability. Therefore, calibrating both anomalous frequency and amplitude of biorhythm prevents physiological dysfunctions or diseases. However, many works were devoted to modulate frequency exclusively whereas amplitude is usually ignored, although both quantities are equally significant for coordinating biological functions and outputs. Especially, a feasible method coordinating the two quantities concurrently and precisely is still lacking. Here, for the first time, we propose a universal approach to design a frequency-amplitude coordinator rigorously via dynamical systems tools. We consider both spatial and temporal information. With a single well-designed coordinator, they can be calibrated to desired levels simultaneously and precisely. The practical usefulness and efficacy of our method are demonstrated in representative neuronal and gene regulatory models. We further reveal its fundamental mechanism and optimal energy consumption providing inspiration for biorhythm regulation in future.

scholarly journals Solubility Product of Vanadinite Pb5(VO4)3Cl at 25 °C—A Comprehensive Approach to Incongruent Dissolution Modeling

Minerals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 135
Author(s):  
Justyna Topolska ◽  
Bartosz Puzio ◽  
Olaf Borkiewicz ◽  
Julia Sordyl ◽  
Maciej Manecki
Keyword(s):  
Nuclear Waste ◽  
Solubility Product ◽  
Geochemical Modeling ◽  
Incongruent Dissolution ◽  
Mineral Solubility ◽  
Actual Application ◽  
Universal Approach ◽  
Solubility Constant ◽  
First Time

Although vanadinite (Pb5(VO4)3Cl) occurs in abundance in various terrestrial geochemical systems of natural and anthropogenic origin and is seriously considered as a potential nuclear waste sequestering agent, its actual application is severely limited by a lack of understanding of its basic thermodynamic parameters. In this regard, the greatest challenge is posed by its incongruent dissolution, which is a pivotal hurdle for effective geochemical modeling. Our paper presents an universal approach for geochemical computing of systems undergoing incongruent dissolution which, along with unique, long-term experiments on vanadinites’ stability, allowed us to determine the mineral solubility constant. The dissolution experiments were carried out at pH = 3.5 for 12 years. Vanadinite has dissolved incongruently, continuously re-precipitating into chervetite (Pb2V2O7) with the two minerals remaining in mutual equilibrium until termination of the experiments. The empirically derived solubility constant Ksp,V,298 = 10–91.89 ± 0.05 of vanadinite was determined for the first time. The proposed modeling method is versatile and can be adopted to other mineral systems undergoing incongruent dissolution.

scholarly journals Optimal energy consumption and throughput for workflow applications on distributed architectures

2014 ◽  
Vol 4 (1) ◽  
pp. 44-51
Author(s):  
Abdallah Ben Othman ◽  
Jean-Marc Nicod ◽  
Laurent Philippe ◽  
Veronika Rehn-Sonigo
Keyword(s):  
Energy Consumption ◽  
Distributed Architectures ◽  
Optimal Energy

Energy Aware Grid Scheduling for Dependent Task Using Genetic Algorithm

2016 ◽  
Vol 7 (2) ◽  
pp. 18-36
Author(s):  
Shiv Prakash ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Job Scheduling ◽  
Computing System ◽  
Computational Grid ◽  
Task Execution ◽  
Energy Aware ◽  
Optimal Energy ◽  
Proposed Model ◽  
Dynamic Voltage

Consumption of energy in the large computing system is an important issue not only because energy sources are depleting fast but also due to the deteriorating environmental conditions. A computational grid is a large heterogeneous distributed computing platform which consumes enormous energy in the task execution. Energy-aware job scheduling, in the computational grid, is an important issue that has been addressed in this work. If the tasks are properly scheduled, keeping the optimal energy concern, it is possible to save the energy consumed by the system in the task execution. The prime objective, in this work, is to schedule the dependent tasks of a job, on the grid nodes with optimal energy consumption. Energy consumption is estimated with the help of Dynamic Voltage Frequency Scaling (DVFS). Makespan, while optimizing the energy consumption, is also taken care of in the proposed model. GA is applied for the purpose and therefore the model is named as Energy Aware Genetic Algorithm (EAGA). Performance evaluation of the proposed model is done using GridSim simulator. A comparative study with other existing models viz. min-min and max-min proves the efficacy of the proposed model.

scholarly journals Powertrain Optimization for Electric Buses under Optimal Energy-Efficient Driving

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6451
Author(s):  
Alexander Koch ◽  
Olaf Teichert ◽  
Svenja Kalt ◽  
Aybike Ongel ◽  
Markus Lienkamp
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Ride Comfort ◽  
Programming Approach ◽  
Automated Driving ◽  
Dynamic Programming Approach ◽  
Optimal Energy ◽  
Driving Cycles ◽  
Powertrain Configuration

State of the art powertrain optimization compares the energy consumption of different powertrain configurations based on simulations with fixed driving cycles. However, this approach might not be applicable to future vehicles, since speed advisory systems and automated driving functions offer the potential to adapt the speed profile to minimize energy consumption. This study aims to investigate the potential of powertrain optimization with respect to energy consumption under optimal energy-efficient driving for electric buses. The optimal powertrain configurations of the buses under energy-efficient driving and their respective energy consumptions are obtained using powertrain-specific optimized driving cycles and compared with those of human-driven unconnected buses and buses with non-powertrain-specific optimal speed profiles. Based on the results, new trends in the powertrain design of vehicles under energy-efficient driving are derived. The optimized driving cycles are calculated using a dynamic programming approach. The evaluations were based on the fact that the buses under energy-efficient driving operate in dedicated lanes with vehicle-to-infrastructure (V2I) communication while the unconnected buses operate in mixed traffic. The results indicate that deviating from the optimal powertrain configuration does not have a significant effect on energy consumption for optimized speed profiles; however, the energy savings from an optimized powertrain configuration can be significant when ride comfort is considered. The connected buses under energy-efficient driving operating in dedicated lanes may reduce energy consumption by up to 27% compared to human-driven unconnected buses.

Distributed optimal energy consumption control of HEVs under MFG-based speed consensus

2020 ◽  
Vol 18 (2) ◽  
pp. 193-203
Author(s):  
Qiaobin Fu ◽  
Fuguo Xu ◽  
Tielong Shen ◽  
Kenichi Takai
Keyword(s):  
Energy Consumption ◽  
Optimal Energy ◽  
Consumption Control

scholarly journals Modeling the Effect of Scrap on the Electrical Energy Consumption of an Electric Arc Furnace

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1044
Author(s):  
Leo S. Carlsson ◽  
Peter B. Samuelsson ◽  
Pär G. Jönsson
Keyword(s):  
Energy Consumption ◽  
Statistical Model ◽  
Electrical Energy ◽  
Electric Arc Furnace ◽  
Electric Arc ◽  
Melting Time ◽  
Arc Furnace ◽  
Total Energy Consumption ◽  
Data Set ◽  
Practical Usefulness

The melting time of scrap is a factor that affects the Electrical Energy (EE) consumption of the Electric Arc Furnace (EAF) process. The EE consumption itself stands for most of the total energy consumption during the process. Three distinct representations of scrap, based partly on the apparent density and shape of scrap, were created to investigate the effect of scrap on the accuracy of a statistical model predicting the EE consumption of an EAF. Shapley Additive Explanations (SHAP) was used as a tool to investigate the effects by each scrap category on each prediction of a selected model. The scrap representation based on the shape of scrap consistently resulted in the best performing models while all models using any of the scrap representations performed better than the ones without any scrap representation. These results were consistent for all four distinct and separately used cleaning strategies on the data set governing the models. In addition, some of the main scrap categories contributed to the model prediction of EE in accordance with the expectations and experience of the plant engineers. The results provide significant evidence that a well-chosen scrap categorization is important to improve a statistical model predicting the EE and that experience on the specific EAF under study is essential to evaluate the practical usefulness of the model.

scholarly journals An Incentive-based Optimal Energy Consumption Scheduling Algorithm for Residential Users

2015 ◽  
Vol 52 ◽  
pp. 851-857 ◽  
Author(s):  
Ihsan Ullah ◽  
Nadeem Javaid ◽  
Zahoor A. Khan ◽  
Umar Qasim ◽  
Zafar A. Khan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Scheduling Algorithm ◽  
Optimal Energy
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