Minimum Energy Time Tables for Subway Operation - And Hamiltonian Feedback to Return to Schedule

2017 ◽  
pp. 1-14
Author(s):  
Hans Georg Bock ◽  
Abdelahad Cadi ◽  
Richard W. Longman ◽  
Johannes P. Schlöder
Keyword(s):  
Minimum Energy

Minimum Energy Wind Dependent Optimised Path Generation for Multirotors

2021 ◽  
Author(s):  
Alexander McConville ◽  
Colin Greatwood ◽  
Duncan Hine ◽  
Peiman Moradi ◽  
Thomas S. Richardson
Keyword(s):  
Minimum Energy ◽  
Path Generation

Instant and Persistent Hydrogen Production Using Nano High Entropy Catalyst

2019 ◽  
Author(s):  
Nirmal Kumar ◽  
Subramanian Nellaiappan ◽  
Ritesh Kumar ◽  
Kirtiman Deo Malviya ◽  
K. G. Pradeep ◽  
...  
Keyword(s):  
Formic Acid ◽  
Minimum Energy ◽  
High Entropy Alloy ◽  
Hydrogen Energy ◽  
High Entropy ◽  
Electro Oxidation ◽  
The Individual ◽  
Novel Catalyst ◽  
Cell Anode ◽  
Fuel Cell Anode

<div>Renewable harvesting clean and hydrogen energy using the benefits of novel multicatalytic materials of high entropy alloy (HEA equimolar Cu-Ag-Au-Pt-Pd) from formic acid with minimum energy input has been achieved in the present investigation. The synthesis effect of pristine elements in the HEA drives the electro-oxidation reaction towards non-carbonaceous pathway . The atomistic simulation based on DFT rationalize the distinct lowering of the d-band center for the individual atoms in the HEA as compared to the pristine counterparts. This catalytic activity of the HEA has also been extended to methanol electro-oxidation to show the unique capability of the novel catalyst. The nanostructured HEA, properties using a combination of casting and cry omilling techniques can further be utilized as fuel cell anode in direct formic acid/methanol fuel cells (DFFE).<br></div>

Laplace watershed segmentation based on minimum energy

2009 ◽  
Vol 29 (2) ◽  
pp. 462-464 ◽  
Author(s):  
Hui-jun FENG ◽  
Bin CHEN ◽  
Xiang-hui ZHAO ◽  
Fan XIA
Keyword(s):  
Minimum Energy ◽  
Watershed Segmentation

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

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