Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Wenjun Chu"'
Publikováno v:
Frontiers in Energy Research, Vol 9 (2021)
Void fraction is one of the key parameters for gas-liquid study and detection of nuclear power system state. Based on fully convolutional neural network (FCN) and high-speed photography, an indirect void fraction measure approach for flow boiling con
Externí odkaz:
https://doaj.org/article/7038beb04e854eb8a325243636e60c0f
Publikováno v:
Journal of Advanced Transportation, Vol 2021 (2021)
With the personalized and diversified development of customer demand in the freight market, road transportation has become a main competitor of railway transportation in container transportation due to its high flexibility, convenience, and low price
Externí odkaz:
https://doaj.org/article/66c5dfdafad4410e81ec1600e8ecd23b
Pareto optimal train scheduling for urban rail transit using generalized particle swarm optimization
Publikováno v:
Advances in Mechanical Engineering, Vol 8 (2016)
In urban rail transport, train timetable plays a crucial role, whose quality determines the whole system’s performance to a large extent. In practical urban rail operation, two contradictive aspects—service quality and operation cost—should be
Externí odkaz:
https://doaj.org/article/d635ab6b5e2848208d987351fbed9ae7
Publikováno v:
Brazilian Journal of Microbiology
Background Accurate and rapid diagnosis of Clostridium difficile infection (CDI) is critical for effective patient management and implementation of infection control measures to prevent transmission. Objectives We updated our previous meta-analysis t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c1164f4cb3664a64d7f1dba858b24cd
http://europepmc.org/articles/PMC8578272
http://europepmc.org/articles/PMC8578272
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e1cadc109642c9f80279460524ee605
https://doi.org/10.2139/ssrn.4122867
https://doi.org/10.2139/ssrn.4122867
Publikováno v:
Volume 1: Operating Plant Challenges, Successes, and Lessons Learned; Nuclear Plant Engineering; Advanced Reactors and Fusion; Small Modular and Micro-Reactors Technologies and Applications.
The narrow rectangular channel has the advantages of compact structure and high heat transfer coefficient, and has been widely used in nuclear systems. However, the internal flow of the narrow channel will be affected by the non-inertial force when i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f63107402a76b365c8f53068d0a0e12e
https://doi.org/10.1115/icone28-62494
https://doi.org/10.1115/icone28-62494
Publikováno v:
Sustainability; Volume 14; Issue 15; Pages: 9287
The impact of China’s green finance policies on renewable energy, clean energy, and other green companies is a hot topic of concern. This study uses the difference-in-differences (DID) model to examine the incentive effect of the Green Credit Guide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b06f1ca631208fe6f2233720ba8f15b
https://doi.org/10.3390/su14159287
https://doi.org/10.3390/su14159287
Publikováno v:
Frontiers in Energy Research, Vol 9 (2021)
Void fraction is one of the key parameters for gas-liquid study and detection of nuclear power system state. Based on fully convolutional neural network (FCN) and high-speed photography, an indirect void fraction measure approach for flow boiling con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33a30725cf92ee87e196d2c2806f7c77
https://doi.org/10.3389/fenrg.2021.636813
https://doi.org/10.3389/fenrg.2021.636813
Publikováno v:
Flow Measurement and Instrumentation. 83:102086
In this paper, an indirect flow pattern recognition method based on time-frequency analysis and neural networks is proposed to investigate the flow patterns in the narrow rectangular channel under heating and non-inertial conditions. Firstly, the ada
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c0e5c93c95a6d21a69a2a5aed31e8fc
https://doi.org/10.1016/j.flowmeasinst.2021.102086
https://doi.org/10.1016/j.flowmeasinst.2021.102086
Publikováno v:
Mathematical Problems in Engineering, Vol 2020 (2020)
Predicting CO2 emission prices is an important and challenging task for policy makers and market participants, as carbon prices follow a stochastic process of complex time series with nonstationary and nonlinear characteristics. Existing literature h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ee80beb00a81ae004967f976344a851
https://doaj.org/article/0b37fd382fe34a8599a9cc7b6e8df83e
https://doaj.org/article/0b37fd382fe34a8599a9cc7b6e8df83e