Effects of permeability heterogeneity on CO2injectivity and storage efficiency coefficient

2015 ◽  
Vol 6 (1) ◽  
pp. 112-124 ◽  
Author(s):  
Liang Tian ◽  
Zhibing Yang ◽  
Fritjof Fagerlund ◽  
Auli Niemi
Keyword(s):  
Efficiency Coefficient ◽  
Storage Efficiency ◽  
Permeability Heterogeneity ◽  
And Storage

Estimations of energy density and storage efficiency for cascading adsorption heat storage concepts

2019 ◽  
Vol 105 ◽  
pp. 59-65 ◽  
Author(s):  
Matthias S. Treier ◽  
Gunther Munz ◽  
Andreas Velte ◽  
Stefan K. Henninger ◽  
Ferdinand P. Schmidt
Keyword(s):  
Energy Density ◽  
Heat Storage ◽  
Adsorption Heat ◽  
Storage Efficiency ◽  
And Storage

MXene Ti3C2Tx for phase change composite with superior photothermal storage capability

2019 ◽  
Vol 7 (23) ◽  
pp. 14319-14327 ◽  
Author(s):  
Xiaoqiao Fan ◽  
Lu Liu ◽  
Xin Jin ◽  
Wentao Wang ◽  
Shufen Zhang ◽  
...  
Keyword(s):  
Phase Change ◽  
Near Infrared ◽  
Infrared Region ◽  
Storage Efficiency ◽  
Sunlight Irradiation ◽  
Photothermal Conversion ◽  
Enhanced Absorption ◽  
Near Infrared Region ◽  
And Storage

A novel composite PCM was facilely synthesized, which exhibited enhanced absorption peaks at visible and near-infrared region, and the photothermal conversion and storage efficiency was outstanding under simulated and actual sunlight irradiation.

scholarly journals Decision Support based Resource Allocation for Cost Reduction in Cloud Storage using Big Data Analytics

2019 ◽  
Vol 8 (3) ◽  
pp. 8124-8126
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Data Storage ◽  
Input Data ◽  
Similarity Coefficient ◽  
Storage Efficiency ◽  
Decision Support Model ◽  
Storage Overhead ◽  
Tanimoto Similarity ◽  
And Storage

Provision of highly efficient storage for dynamically growing data is considered problem to be solved in data mining. Few research works have been designed for big data storage analytics. However, the storage efficiency using conventional techniques was not sufficient as where data duplication and storage overhead problem was not addressed. In order to overcome such limitations, Tanimoto Regressive Decision Support Based Blake2 Hashing Space Efficient Quotient Data Structure (TRDS-BHSEQDS) Model is proposed. Initially, TRDS-BHSEQDS technique gets larger number of input data as input. Then, TRDS-BHSEQDS technique computes 512 bits Blake2 hash value for each data to be stored. Consequently, TRDS-BHSEQDS technique applies Tanimoto Regressive Decision Support Model (TRDSM) where it carried outs regression analysis with application of Tanimoto similarity coefficient. During this process, proposed TRDS-BHSEQDS technique finds relationship between hash values of data by determining Tanimoto similarity coefficient value. If similarity value is ‘+1’, then TRDS-BHSEQDS technique considered that input data is already stored in BHSEQF memory. TRDSBHSEQDS technique enhances the storage efficiency of big data when compared to state-of-the-art works. The performance of TRDS-BHSEQDS technique is measured in terms of storage efficiency, time complexity and space complexity and storage overhead with respect to different numbers of input big data.

scholarly journals Geomechanical effects of carbon sequestration as CO2 hydrates and CO2-N2 hydrates on host submarine sediments

2020 ◽  
Vol 205 ◽  
pp. 11003
Author(s):  
Shuman Yu ◽  
Shun Uchida
Keyword(s):  
Carbon Sequestration ◽  
Methane Hydrate ◽  
Formation Rate ◽  
Hydrate Formation ◽  
Small Deformation ◽  
Storage Efficiency ◽  
The Past ◽  
Single Well ◽  
And Storage ◽  
Hydrate Formation Process

Over the past 10 years, more than 300 trillion kg of carbon dioxide (CO2) have been emitted into the atmosphere, deemed responsible for climate change. The capture and storage of CO2 has been therefore attracting research interests globally. CO2 injection in submarine sediments can provide a way of CO2 sequestration as solid hydrates in sediments by reacting with pore water. However, CO2 hydrate formation may occur relatively fast, resulting decreasing CO2 injectivity. In response, nitrogen (N2) addition has been suggested to prevent potential blockage through slower CO2-N2 hydrate formation process. Although there have been studies to explore this technique in methane hydrate recovery, little attention is paid to CO2 storage efficiency and geomechanical responses of host marine sediments. To better understand carbon sequestration efficiency via hydrate formation and related sediment geomechanical behaviour, this study presents numerical simulations for single well injection of pure CO2 and CO2-N2 mixture into submarine sediments. The results show that CO2-N2 mixture injection improves the efficiency of CO2 storage while maintaining relatively small deformation, which highlights the importance of injectivity and hydrate formation rate for CO2 storage as solid hydrates in submarine sediments.

scholarly journals An Effective NTRU-Based Fully Homomorphic Encryption Scheme

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaoyue Qin ◽  
Ruwei Huang ◽  
Huifeng Fan
Keyword(s):  
Chinese Remainder Theorem ◽  
Homomorphic Encryption ◽  
Security Model ◽  
Storage Efficiency ◽  
Complex Matrix ◽  
Fully Homomorphic Encryption ◽  
Multiple Data ◽  
Learning With Errors ◽  
Matrix Vector ◽  
And Storage

Fully homomorphic encryption (FHE) supports arbitrary computations on ciphertexts without decryption to protect users’ privacy. However, currently, there are still some shortcomings in research studies on FHE. For example, the NTRU-based FHE scheme constructed using the approximate eigenvector method requires complex matrix multiplications, and the power-of-two cyclotomic ring cannot prevent subfield attacks. To address these problems, this paper proposed a NTRU-based FHE scheme constructed based on the power-of-prime cyclotomic ring and made the following improvements: (1) the power-of-prime cyclotomic ring is immune to subfield attacks; (2) complex matrix multiplications are replaced with matrix-vector multiplications to modify the ciphertext forms and decryption structures, so as to gain advantages in storage, transportation, and computations; (3) the single instruction multiple data (SIMD) technology is introduced, and homomorphic operations are executed through the Chinese remainder theorem, further improving the scheme computation and storage efficiency. The ciphertext of the scheme is in a form of a vector, and no key exchange is required for homomorphic operations. In addition, this scheme can eliminate the decisional small polynomial ratio (DSPR) assumption under certain conditions and only relies on the ring learning with errors (RLWE) assumption. The standard security model can prove that this scheme is secure against chosen-plaintext (IND-CPA) attacks. Compared with similar schemes, the proposed scheme improves the efficiency at least by a factor of l φ x / d +   1 and quadratically decreases the noise growth rate.

scholarly journals Privacy-preserving public auditing with data deduplication in cloud computing

2021 ◽  
Author(s):  
Naelah Abdulrahman Alkhojandi
Keyword(s):  
Data Integrity ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Storage Efficiency ◽  
Data Deduplication ◽  
Public Auditing ◽  
Efficient Data ◽  
User Revocation ◽  
Public Auditability ◽  
And Storage

Storage represents one of the most commonly used cloud services. Data integrity and storage efficiency are two key requirements when storing users’ data. Public auditability, where users can employ a Third Part Auditor (TPA) to ensure data integrity, and efficient data deduplication which can be used to eliminate duplicate data and their corresponding authentication tags before sending the data to the cloud, offer possible solutions to address these requirements. In this thesis, we propose a privacy preserving public auditing scheme with data deduplication. We also present an extension of our proposed scheme that enables the TPA to perform multiple auditing tasks at the same time. Our analytical and experimental results show the efficiency of the batch auditing by reducing the number of pairing operations need for the auditing. Then, we extend our work to support user revocation where one of the users wants to leave the enterprise.

scholarly journals Privacy-preserving public auditing with data deduplication in cloud computing

2021 ◽  
Author(s):  
Naelah Abdulrahman Alkhojandi
Keyword(s):  
Data Integrity ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Storage Efficiency ◽  
Data Deduplication ◽  
Public Auditing ◽  
Efficient Data ◽  
User Revocation ◽  
Public Auditability ◽  
And Storage

Storage represents one of the most commonly used cloud services. Data integrity and storage efficiency are two key requirements when storing users’ data. Public auditability, where users can employ a Third Part Auditor (TPA) to ensure data integrity, and efficient data deduplication which can be used to eliminate duplicate data and their corresponding authentication tags before sending the data to the cloud, offer possible solutions to address these requirements. In this thesis, we propose a privacy preserving public auditing scheme with data deduplication. We also present an extension of our proposed scheme that enables the TPA to perform multiple auditing tasks at the same time. Our analytical and experimental results show the efficiency of the batch auditing by reducing the number of pairing operations need for the auditing. Then, we extend our work to support user revocation where one of the users wants to leave the enterprise.

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