A Bayesian approach for estimating the parameters of a forest process model based on long-term growth data

This paper describes the teaming strategy between the U. S. Air Force’s two major propulsion test centers, Arnold Engineering Development Center (AEDC) and the Air Force Flight Test Center (AFFTC), to employ new modeling and simulation (M&S) techniques to reduce test cost and cycle time. With the long-term goal of developing joint ground/flight modeling and simulation capabilities, AEDC and AFFTC have teamed to apply these data analysis tools to two major propulsion flight test programs, the F-22 and the Joint Strike Fighter (JSF). The emphasis of this paper is on the development and application of a non-linear aerothermodynamic component-level model that serves as the basis for the model-based analysis and fault identification process. Model-to-data comparisons and model-based fault detection and analysis results for F-22/F119 propulsion ground and flight test are also presented for a variety of flight conditions.

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Study on the Development of ‘Managerial Wisdom’ Learning Process Model: Based on Grounded Theory

Korea Association of Business Education ◽

10.23839/kabe.2019.34.1.241 ◽

2019 ◽

Vol 34 (1) ◽

pp. 241-263

Author(s):

Joo－Won Kim ◽

Yong－Seung Park

Keyword(s):

Grounded Theory ◽

Learning Process ◽

Process Model ◽

Model Based

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Semantics of OWL-S process model based on temporal description logic

Journal of Computer Applications ◽

10.3724/sp.j.1087.2013.00266 ◽

2013 ◽

Vol 33 (1) ◽

pp. 266-269 ◽

Cited By ~ 1

Author(s):

Ming LI ◽

Shiyi LIU ◽

Fuzhong NIAN

Keyword(s):

Process Model ◽

Description Logic ◽

Model Based

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The Evaluation of Efficient Process Model Based on Survey

SSRN Electronic Journal ◽

10.2139/ssrn.3168404 ◽

2018 ◽

Author(s):

Thulasee Krishna Dr. S. ◽

Sreekanth Dr.S. ◽

Dharanidhar K. N.

Keyword(s):

Process Model ◽

Efficient Process ◽

Model Based

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Analysis of factors affecting long-term coal demand in China Error correction model based on co-integration

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/769/3/032076 ◽

2021 ◽

Vol 769 (3) ◽

pp. 032076

Author(s):

Xiwen Feng ◽

Mingshang Xin

Keyword(s):

Error Correction ◽

Error Correction Model ◽

Correction Model ◽

Factors Affecting ◽

Model Based

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A Combined Approach for Model-Based PV Power Plant Failure Detection and Diagnostic

Energies ◽

10.3390/en14051261 ◽

2021 ◽

Vol 14 (5) ◽

pp. 1261

Author(s):

Christopher Gradwohl ◽

Vesna Dimitrievska ◽

Federico Pittino ◽

Wolfgang Muehleisen ◽

András Montvay ◽

...

Keyword(s):

Power Plants ◽

Large Scale ◽

Failure Detection ◽

Energy Yield ◽

Combined Approach ◽

Levelized Cost Of Electricity ◽

Term Operation ◽

Model Based

Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive market environment where even small performance losses have a high impact on profit margins. Therefore, operation at maximum performance is the key for long-term profitability. This can be achieved by advanced performance monitoring and instant or gradual failure detection methodologies. We present in this paper a combined approach on model-based fault detection by means of physical and statistical models and failure diagnosis based on physics of failure. Both approaches contribute to optimized PV plant operation and maintenance based on typically available supervisory control and data acquisition (SCADA) data. The failure detection and diagnosis capabilities were demonstrated in a case study based on six years of SCADA data from a PV plant in Slovenia. In this case study, underperforming values of the inverters of the PV plant were reliably detected and possible root causes were identified. Our work has led us to conclude that the combined approach can contribute to an efficient and long-term operation of photovoltaic power plants with a maximum energy yield and can be applied to the monitoring of photovoltaic plants.

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