A Survey of Different Storage Methods for NGN Mobile Networks: Storage Capacity, Security and Response Time

2019 ◽  
pp. 39-59
Author(s):  
Boughanja Manale ◽  
Mazri Tomader
Keyword(s):  
Response Time ◽  
Mobile Networks ◽  
Storage Capacity ◽  
Storage Methods

scholarly journals The Deltah Lab, a New Multidisciplinary European Facility to Support the H2 Distribution & Storage Economy

2021 ◽  
Vol 11 (7) ◽  
pp. 3272
Author(s):  
Sara Stelitano ◽  
Alberto Rullo ◽  
Luigi Piredda ◽  
Elisabetta Mecozzi ◽  
Luigi Di Vito ◽  
...  
Keyword(s):  
Storage Capacity ◽  
Renewable Energy Sources ◽  
Energy System ◽  
System Transformation ◽  
Life Tests ◽  
Storage Methods ◽  
Complementary Techniques ◽  
H2 Effect ◽  
Empty Condition ◽  
New Facility

The target for European decarburization encourages the use of renewable energy sources and H2 is considered the link in the global energy system transformation. So, research studies are numerous, but only few facilities can test materials and components for H2 storage. This work offers a brief review of H2 storage methods and presents the preliminary results obtained in a new facility. Slow strain rate and fatigue life tests were performed in H2 at 80 MPa on specimens and a tank of AISI 4145, respectively. Besides, the storage capacity at 30 MPa of a solid-state system, they were evaluated on kg scale by adsorption test. The results have shown the H2 influence on mechanical properties of the steel. The adsorption test showed a gain of 26% at 12 MPa in H2 storage with respect to the empty condition. All samples have been characterized by complementary techniques in order to connect the H2 effect with material properties.

TECHNOLOGY AND INTERACTIVE SOFTWARE FOR OIL SPILL PLANNING AND RESPONSE

1997 ◽  
Vol 1997 (1) ◽  
pp. 973-975
Author(s):  
Carl G. Kitz ◽  
Michael J. Szerlog ◽  
Sean M. Hyde
Keyword(s):  
Response Time ◽  
Oil Spill ◽  
Storage Capacity ◽  
Easy Access ◽  
Digital Information ◽  
Interactive Software ◽  
Critical Information ◽  
Response Information ◽  
Oil Spill Response ◽  
User Friendly

ABSTRACT EPA Region X has combined the immense storage capacity of CD-ROMs with interactive software to develop a user-friendly tool to provide quick and easy access to digital information for use by oil spill response teams. These CD-ROMs, created specifically for spill planning and response, provide responders with hypertext links and powerful search capabilities allowing uncomplicated access to response information, regulations, nationally recognized standards, and area maps. This format enhances response time by reducing the time needed to access critical information and the volume of materials carried to the site by responders.

scholarly journals Properties of adsorbed hydrogen and methane films on nanoporous solids

2017 ◽  
Author(s):  
◽  
Andrew Karl Gillespie
Keyword(s):  
Energy Density ◽  
Fossil Fuels ◽  
Storage Capacity ◽  
Isosteric Heat ◽  
Adsorptive Capacity ◽  
Storage Tanks ◽  
Adsorbed Film ◽  
Renewable Fuel ◽  
Storage Methods ◽  
Nanoporous Solids

The environmental impacts and costs of fossil fuels necessitate the development of clean, renewable fuel sources for vehicular applications. Hydrogen based systems, with water as their byproduct, have zero carbon emissions, which mitigates the negative effects of using conventional fossil fuels. Further, hydrogen can be produced from renewable energy sources, such as renewable electrolysis and biohydrogen. When produced from such methods, hydrogen is a renewable fuel. The main drawback of hydrogen as a fuel is its low energy density at ambient pressures and temperatures. Hydrogen has a mass energy density three times that of gasoline, but occupies more than 30 times the volume. Therefore, it is necessary to increase the volumetric energy density of hydrogen before it can be considered as a practical option. Conventional storage methods for hydrogen include compression and liquefaction. In order to yield a sufficient deliverable storage capacity, these methods require high pressures or cryogenic temperatures. Compressed gas systems require tanks with massive walls which reduce spatial and mass efficiency and thus, vehicle performance. These systems are geometrically constrained due to their high pressure, making them difficult to integrate into the vehicle. Due to these constraints, conventional storage methods are insufficient at increasing the energy density of hydrogen to compete with that of fossil fuels. To bridge this gap, it is necessary to develop a low-pressure, high-capacity storage technology in order to address the temperature, pressure, weight, and volume constraints present in the conventional storage methods. To achieve this, we investigate the storage capacity of nanoporous solids, which are capable of densifying a high volume of hydrogen on their surfaces through the process of adsorption. Several factors affect the adsorptive capacity of these materials, such as specific surface area, pore geometry, and the strength of the adsorption potential. The strength of the adsorption potential often cited as a figure of merit for the adsorptive capacity of new materials and is commonly estimated through the Clausius-Clapeyron relation between two adsorption isotherms. However, this method requires an assumption of the adsorbed film volume, which poses as the primary source of error. From supercritical hydrogen isotherms from 77 - 473 Kelvin, we propose a method to measure the volumes, densities, and thicknesses of the adsorbed film. This method will lead to more accurate isosteric heat calculations, which is an important factor to consider when designing storage tanks. Furthermore, we investigated the correlation between the isosteric heat of adsorption, surface chemistry, and pore size distribution with an adsorbed film. In most of the samples the saturated film density was approximately 100 g/L across a large range of temperatures. The specific volumes of the adsorbed film scaled with specific surface area and binding energies. The saturated, adsorbed film density approaches 100 g/L for all adsorbent types at 77 K. The saturated, adsorbed film thickness was between 3.1 - 3.2 [superscript A] for hydrogen on most sorbent materials. In the future, we intend to investigate changes in these parameters of the adsorbed film with increasing temperature as well as the affects that these changes may have on the estimated values of isosteric heat. Improved estimates of isosteric heats of adsorption will assist in optimizing the thermal properties of on-board storage tanks.

Adaptive Replica Creation and Selection Strategies for Latency-Aware Application in Collaborative Edge-Cloud System

2019 ◽  
Vol 63 (9) ◽  
pp. 1338-1354
Author(s):  
Chunlin Li ◽  
YiHan Zhang ◽  
Youlong Luo
Keyword(s):  
Response Time ◽  
Storage Capacity ◽  
Replica Placement ◽  
File Access ◽  
User Request ◽  
Replica Selection ◽  
Replica Management ◽  
Research Problems ◽  
Two Parameters ◽  
And Storage

Abstract There are many research problems in cloud replica management such as low data reliability, unbalanced node load and large resource consumption. The strategy and status of replica creation, replica placement and replica selection are analyzed. The replica creation based on access tendency (DRC-AT), the replica placement based on user request response time and storage capacity (DRP-RS) and the replica selection based on response time (DRS-RT) are proposed. The DRC-AT algorithm introduces the two parameters of file popularity and period value of file popularity, calculates the file access tendency periodically and decides the creation and deletion of the replica of the file according to the size of the file access tendency. The DRP-RS algorithm evaluates the user’s request response time and storage capacity to select the best node set to place the replica. The DRS-RT algorithm returns to the user the node with the strongest service capability that contains the user’s requested data. Experiments show that the algorithm can improve the speed of data reading by the client, improve the resource utilization, balance the load of the node and improve the overall performance of the system.

A Study of Distributed Photovoltaic Energy Storage Configuration Capacity

2015 ◽  
Vol 733 ◽  
pp. 215-218
Author(s):  
Ming Kai Yu ◽  
Chong Yuan ◽  
Jing Xu
Keyword(s):  
Energy Storage ◽  
Future Development ◽  
Storage Capacity ◽  
Battery Energy Storage ◽  
Photovoltaic Energy ◽  
Advantages And Disadvantages ◽  
Energy Storage Capacity ◽  
Storage Methods ◽  
Battery Energy ◽  
Research Situation

In order to solve the problem of storage capacity configuration in distributed photovoltaic energy, firstly a brief introduction of the storage methods in distributed PV (photovoltaic) energy is given out. Then it mainly discusses the configuration mode of distributed photovoltaic battery energy storage capacity within a variety of methods and principles of the research situation. And their advantages and disadvantages are analyzed in detail. Finally, the energy storage capacity configuration problems to be solved in the future development and its application should be made to focus on the aspect shortly.

scholarly journals Concept of minimizing the response time for reducing dynamic data redundancy in cloud computing

2019 ◽  
Vol 15 (3) ◽  
pp. 1597
Author(s):  
Wan Nurazieelin Wan Abd Manan ◽  
Mohamad Aizi Salamat
Keyword(s):  
Cloud Computing ◽  
Response Time ◽  
Cloud Storage ◽  
Storage Capacity ◽  
Service Providers ◽  
Maintenance Cost ◽  
Dynamic Data ◽  
Data Redundancy ◽  
Static Data ◽  
The Cost

<span>Reduction of dynamic data redundancy in cloud computing is one of the best ways to maintain the storage capacity from being fully utilized. Cloud storage is a part of cloud computing technology which holds a high demand in any organization for reducing the cost of purchasing and maintaining storage infrastructures. Increase in the number of users will require a larger storage capacity for storing their data. Reduction of dynamic data redundancy allows service providers to be energy savvy and minimize maintenance cost. Recent researches focus more on static data nature despite its limited capability as compared to dynamic data characteristic in cloud storage. Therefore, this paper theoretically compares various techniques for reduction of redundant dynamic data in cloud computing and suggests the best technique for completing the task in terms of response time.</span>

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

A Response-Time Investigation of Vehicle Stereotypes

2000 ◽  
Author(s):  
Michael Anthony ◽  
Robert W. Fuhrman
Keyword(s):  
Response Time

System response time and problem solving behavior.

1981 ◽  
Author(s):  
Hans Bergman ◽  
Albert Brinkman ◽  
Harry S. Koelega
Keyword(s):  
Problem Solving ◽  
Response Time ◽  
System Response ◽  
System Response Time ◽  
Problem Solving Behavior
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