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نتیجه جستجو - hydrogen

تعداد مقالات یافته شده: 78
ردیف عنوان نوع
1 Learning to Learn Variational Quantum Algorithm
آموزش یادگیری الگوریتم کوانتومی متغیر-2022
Variational quantum algorithms (VQAs) use classical computers as the quantum outer loop optimizer and update the circuit parameters to obtain an approximate ground state. In this article, we present a meta-learning variational quantum algorithm (meta-VQA) by recurrent unit, which uses a technique called “meta-learner.” Motivated by the hybrid quantum-classical algorithms, we train classical recurrent units to assist quantum computing, learning to find approximate optima in the parameter landscape. Here, aiming to reduce the sampling number more efficiently, we use the quantum stochastic gradient descent method and introduce the adaptive learning rate. Finally, we deploy on the TensorFlow Quantum processor within approximate quantum optimization for the Ising model and variational quantum eigensolver for molecular hydrogen (H2), lithium hydride (LiH), and helium hydride cation (HeH+). Our algorithm can be expanded to larger system sizes and problem instances, which have higher performance on near-term processors.
Index Terms: Meta-learning | quantum algorithm | quantum computing | quantum information | quantum machine learning(QML).
مقاله انگلیسی
2 Quantum Federated Learning With Decentralized Data
یادگیری فدرال کوانتومی با داده های غیرمتمرکز-2022
Variational quantum algorithm (VQA) accesses the centralized data to train the model, and using distributed computing can significantly improve the training overhead; however, the data is privacy sensitive. In this paper, we propose communication-efficient learning of VQA from decentralized data, which is so-called quantumfederated learning(QFL).Motivated by the classical federated learning algorithm, we improve data privacy by aggregating updates from local computation to share model parameters. Here, aiming to find approximate optima in the parameter landscape, we develop an extension of the conventional VQA. Finally, we deploy onthe TensorFlowQuantum processor within variational quantumtensor networks classifiers, approximate quantum optimization for the Ising model, and variational quantum eigensolver for molecular hydrogen. Our algorithm demonstrates model accuracy from decentralized data, which have higher performance on near-term processors. Importantly, QFL may inspire new investigations in the field of secure quantum machine learning.
Index Terms: Quantum algorithm | quantum computing | quantum information | quantum machine learning.
مقاله انگلیسی
3 A Distributed Learning Scheme for Variational Quantum Algorithms
یک طرح یادگیری توزیع شده برای الگوریتم های کوانتومی متغیر-2022
Variational quantum algorithms (VQAs) are prime contenders to gain computational advantages over classical algorithms using near-term quantum machines. As such, many endeavors have been made to accelerate the optimization of modern VQAs in past years. To further improve the capability of VQAs, here, we propose a quantum distributed optimization scheme (dubbed as QUDIO), whose back ends support both real quantum devices and various quantum simulators. Unlike traditional VQAs subsuming a single quantum chip or simulator, QUDIO collaborates with multiple quantum machines or simulators to complete learning tasks. In doing so, the required wall-clock time for optimization can be continuously reduced by increasing the accessible computational resources when ignoring the communication and synchronization time. Moreover, through the lens of optimization theory, we unveil the potential factors that could affect the convergence of QUDIO. In addition, we systematically understand the ability of QUDIO to reduce wall-clock time via two standard benchmarks, which are hand-written image classification and the ground energy estimation of the dihydrogen. Our proposal facilitates the development of advanced VQAs to narrow the gap between the state of the art and applications with the quantum advantage.
INDEX TERMS: Distributed optimization | quantum computing | quantum Hamiltonians | quantum machine learning.
مقاله انگلیسی
4 Failure mode and reliability study for Electrical Facility of the High Temperature Engineering Test Reactor
بررسی حالت خرابی و قابلیت اطمینان برای تاسیسات الکتریکی راکتور آزمایشی مهندسی دما بالا-2021
The first-of-a-kind commercial electricity and hydrogen cogeneration system is being designed by the Japan Atomic Energy Agency (JAEA) to establish the industrial application of the High Temperature Gas-cooled Reactors (HTGR). The High Temperature Engineering Test Reactor (HTTR) is expected to be coupled with a test cogeneration plant to demonstrate its safety features and justify further HTGR technology development. The aim of this work was to assess the frequency of the unplanned outages of such a plant due to the failures of the HTTR Electrical Facility. The system analysis has been performed followed by the Failure Mode and Effect Analysis (FMEA). The new FMEA-based Gradual Screening Approach has been proposed and applied in order to select the most relevant failure modes. The initial calculation performed for the standard configuration of the system indicated that the reliability may be insufficient for its long-term commercial operation, as planned for about 20 years. Therefore, several modifications of the design have been proposed, aiming at the reliability enhancement. However, the updated results are still below the industrial standards. This opens up a new field of research in reliability engineering and creates a challenge for the HTGR-based cogeneration plants consisting of the joint nuclear-chemical facilities.
Keywords: HTTR reactor | Electrical Facility | FMEA-based Gradual Screening | Nuc-Chem facility | Reliability
مقاله انگلیسی
5 Urban landfills investigation for leachate assessment using electrical resistivity imaging in Johor, Malaysia
بررسی محل های دفن زباله شهری برای ارزیابی شیرابه با استفاده از تصویربرداری مقاومت الکتریکی در جوهور، مالزی-2021
The use of the electrical resistivity imaging (ERI) approach has expanded dramatically in engineering applications over the years due to the efficiency of the technique in terms of time, expense, and data coverage. The assessment was carried out using ERI to assess the landfill leachate’s pollution level at Simpang Renggam, Johor, Malaysia. The ERI survey was carried out in the research region, utilizing the ABEM Terrameter LS 2 equipment using the Schlumberger electrode configuration. Besides, seven (7) parameters of leachate characterization such as Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD5), Suspended Solid (SS), Power of Hydrogen (pH), Ammonia Hydrogen (NH3-N), Turbidity and Biodegradability Ratio (BOD5/COD) were also performed to identify and evaluate the current leachate condition of the landfill. Furthermore, the study, which involves the measurement of the apparent resistivity of the subsurface materials were able to determine the existence of chemical pollutants in the soil at 1.5 m to 4.0 m depth, with special reference to the chemically apparent resistivity linked with the low resistivity anomalies of 1 – 10 Ωm. Based on the investigations conducted, the physiochemical and microbial analysis of the Simpang Renggam leachate site was found to be 1633 mg/L (Chemical Oxygen Demand), 137.41 mg/L (Biological Oxygen Demand), 359.8 mg/L (Suspended Solid), 7.61 (Power of Hydrogen), 385.29 (Ammonia Hydrogen), 117.65 (Turbidity) and 0.07 (Biodegradability Ratio) which shows that all of the parameter’s value exceeded the value as stated in the local standard which is Environmental Quality Act (1974) except for the pH value which is within the range value as stated in the standard. The leachate from dumps was thought to arise due to system failures in accepting and managing trash, which was exacerbated by the recent high rains. In hindsight, the ERI result was practical for identifying leachate and, therefore, can benefit the authorities in immediate action to halt the extensive water disturbance at the research region.
Keywords: Landfill Leachate | Electrical Resistivity Imaging | Leachate Characterization | Contaminants
مقاله انگلیسی
6 Bi-objective optimal design of hydrogen and methane supply chains based on Power-to-Gas systems
طراحی بهینه دو هدفه زنجیره های تأمین هیدروژن و متان بر اساس سیستم های نیرو به گاز-2021
This paper presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC) based on Power-to-Gas (PtG) systems. The novelty of the work is twofold, first considering a specific demand for hydrogen for electromobility in addition to the hydrogen demand required as a feedstock to produce synthetic methane from the methanation process. and performing a bi-objective optimization of the HMSC to provide effective support for the study of deployment scenarios. The approach is based on a Mixed Integer Linear Programming (MILP) approach with augmented epsilon-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050) with several available energy sources (wind, PV, hydro, national network) for hydrogen production. Carbon dioxide sources stem mainly from mechanization and gasification processes. The objectives to be minimized simultaneously are the Total Annual Cost and the greenhouse gas emissions related to the whole HMSC over the entire period studied.
KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | Augmented epsilon constraint | GAMS | optimization approach
مقاله انگلیسی
7 A Novel Matheuristic based on bi-level optimization for the multi-Objective design of hydrogen supply chains
Matheuristic جدید مبتنی بر بهینه سازی سطح دو برای طراحی چند هدفه زنجیره های تأمین هیدروژن-2021
This work introduces an efficient tool for the design of sustainable hydrogen supply chains (HSCs), considering both economic and environmental concerns, through an appropriate multi-objective strategy. The original problem, being formulated as a bi-objective mixed-integer linear programming (MILP) problem, takes into consideration the availability of different energy sources, the installation and operation of hydrogen facilities of different sizes and technologies, and the transportation of hydrogen from production units to storage facilities. The area of study is divided into grids which have a specific hydrogen demand that evolves over time, thus a multi-period model of the HSC is considered. In order to overcome the computational burden associated to the solution of large size instances of the resulting problem, we proposed a solution strategy consisting of a hybrid algorithm. The original problem is reformulated into a bi-level optimization problem: the upper level (discrete problem) consists of finding the optimal location for production plants and storage facilities, whereas the lower level (continuous problem) minimizes their corresponding costs associated to transportation and facility operation. A multi-objective evolutionary algorithm is employed for the solution of the bi-objective upper level, whereas the bi-objective lower level is decomposed using a scalarizing function, which is then solved using a linear programming solver. The proposed methodology is validated through the comparison of the true Pareto fronts given by CPLEX with ε-constraint method, for six increasing size instances. Numerical results prove that the proposed hybrid approach produces an accurate approximation of the Pareto-optimal fronts, more efficiently than the exact solution approach.
مقاله انگلیسی
8 A methodological design framework for hydrogen and methane supply chain with special focus on Power-to-Gas systems: application to Occitania region, France
یک چارچوب طراحی روش برای زنجیره تأمین هیدروژن و متان با تمرکز ویژه بر روی سیستم های نیرو به گاز: کاربرد در منطقه اوکسیتانیا ، فرانسه-2021
This work presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC). An innovative approach is to focus on Power-to-Hydrogen (PtH) and Power-to-Methane (PtM) concepts, and their interactions with other technologies, and energy carriers (i.e., Steam Methane Reforming – SMR, and natural gas). The overall objective of this work is to perform single objective and multi-objective optimizations for HMSC design to provide effective support for deployment scenarios. The methodological framework developed is based on a Mixed Integer Linear Programming (MILP) approach with augmented ε-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050). Several available energy sources (wind, PV, hydro, national power grid, and natural gas) for hydrogen production through electrolysis and SMR are included. Carbon dioxide sources stem mainly from methanization and gasification processes, which are used to produce methane through methanation. The objective to be minimised in the single optimization approach is the total annual cost considering the externality of greenhouse gas emissions through the carbon price for the whole HMSC over the entire period studied. The multi-objective optimization includes as objectives the total annual cost, greenhouse gas emissions, and the total methane production from methanation. The Levelized Cost of Energy (LCOE), and the greenhouse gas emissions for each energy carrier are also computed. The results show that renewable hydrogen from PtG can be competitive with SMR through the implementation of carbon prices below 0.27 €/kgCO2. In the case of synthetic methane, the available resources can meet the demand through PtG, and even if synthetic methane for natural gas network injection is thus far from competitive with natural gas, power-to-gas technologies have the potential to decarbonize the fossil economy and achieve a circular economy through CO2 recovery.
KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | supply chain | optimization
مقاله انگلیسی
9 Mapping global fuel cell vehicle industry chain and assessing potential supply risks
نقشه برداری از زنجیره صنعت خودروی سوختی سوخت جهانی و ارزیابی خطرات احتمالی تأمین-2021
Fuel cell vehicles (FCVs) have the potential to contribute significantly to improving air quality and addressing climate concerns in the future. However, due to the highly dynamic technology and manufacturing developments, there is a lack of understanding of the state- of-the-art global FCV industry chain and associated supply risks. This study fills such a research gap by mapping global FCV industry chain during the period 2017e2019, and assessing the supply risks of relevant key commodities. The results show that significant supply risks existed in global FCV industry chain, especially in upstream commodities like platinum and gas diffusion layer (GDL). The combined indicator of Herfindahl-Hirschman Index and Worldwide Governance-Indicator (HHI-WGI) is used to quantify the supply risks, showing that HHI-WGI of platinum is on the highest level. On the national level, supply risks are identified primarily in platinum for Japan, in vehicles for the United States, and along the entire industry chain for China. Network analysis is conducted to visualize and analyze how countries, companies and commodities are connected, showing that the highest supply risks were identified in GDLs. It is recommended that country-specific measures should be taken to mitigate supply risks, including building up national stocks of critical materials, investing overseas, enhancing the guidance over industry policies, and stepping up infrastructure construction.© 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.* Corresponding author. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China. E-mail address: hao@tsinghua.edu.cn (H. Hao).https://doi.org/10.1016/j.ijhydene.2021.02.0410360-3199/© 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Keywords: Fuel cell vehicle | Industry chain | Supply risk | Network analysis
مقاله انگلیسی
10 Hydrogen supply chain and challenges in large-scale LH2 storage and transportation
زنجیره تامین هیدروژن و چالش هایی در ذخیره سازی و حمل و نقل LH2 در مقیاس بزرگ-2021
Hydrogen is considered to be one of the fuels of future and liquid hydrogen (LH2) technology has great potential to become energy commodity beyond LNG. However, for commercial widespread use and feasibility of hydrogen technology, it is of utmost importance to develop cost-effective and safe technologies for storage and transportation of LH2 for use in stationary applications as well as offshore transportation. This paper reviews various aspects of global hydrogen supply chain starting from several ways of production to storage and delivery to utilization. While each these aspects contribute to the overall success and efficiency of the global supply chain, storage and delivery/transport are the key enablers for establishing global hydrogen technology, especially while current infrastructure and technology are being under development. In addition, while all storage options have their own advantages/disadvantages, the LH2 storage has unique advantages due to the familiarity with well-established LNG technology and existing hydrogen technology in space programs. However, because of extremely low temperature constraints, commercialization of LH2 technology for large-scale storage and transportation faces many challenges, which are discussed in this paper along with the current status and key gaps in the existing technology. © 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Keywords: Hydrogen supply chain | Hydrogen production | Liquefaction | Hydrogen storage | Insulation strategy | Thermal modeling
مقاله انگلیسی
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