Validation and Automatic Tuning of Integrated Reservoir and Surface Pipeline Network Models

Author(s):  
M.L. Litvak ◽  
C.J. Macdonald ◽  
B.L. Darlow
2020 ◽  
Author(s):  
Huiping Shi ◽  
Xiaobing Zhou

Abstract Background: The cause of the disease is one of the main contents of biomedical research. Extracting effective relational information from a large number of biomedical texts has important applications for biomedical research. At present, most of the work of biomedicine is to use manual screening or use rule-based or feature-based pipeline network models to obtain screening characteristics. These methods require a lot of time to design specific rules or features to complete specific tasks, resulting in some features that non-compliant features cannot be filtered out.Results: The model gets micro-F1 scores of 0.802 and 0.876 on the Chemprot data set and DDI data set, respectively. The resources that can be used in this project can be found in https://github.com/HunterHeidy/DDICPI-.Conclusions: Experiments have proved that without Bert, you can get good results by learning from Bert<s core ideas.


2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Vadim E. Seleznev

We propose an adaptation method for gas dynamic pipeline network models to enable credible representation of actual properties of real simulation objects. The presentation is illustrated by fitting equivalent pipeline section roughnesses used in the models to accommodate the influence of flow resistance on gas transport parameters. The method is based on the setting up and solution of a series of special parametric identification problems based on a limited set of field measurement data at local (in space) network points. This method can be used by specialists in mathematical modeling of gas transport systems to solve practical parametric identification problems.


Author(s):  
Eadred Birchenough ◽  
James Munro ◽  
Jun Zhang ◽  
Dagfinn Hansen ◽  
Ola Rinde ◽  
...  

This paper addresses the on-line application of ATMOS SIM simulation software, integrated with ABB Network Manager WS500, to a subsea pipeline network of 7,800 km (4,847 mile) length — see Figure 1. The pipeline system is operated by Gassco Norway, and it delivers an annual volume of approximately 100 billion standard cubic meters of Norwegian gas to customers in Western Europe. One of the main challenges to such a great subsea pipeline system is the limited measurements available. For nearly all of the pipelines, the only location where flow, pressure and temperature are measured is at the inlet and outlet which could be more than 800 km (497 mile) apart. The following applications will be addressed in this paper: • IT architecture. User controls including Common Alarm List. • Data validation overview. • Pipeline inventory calculation. • Continuous calculation of settle-out-pressures for (sub)sections of pipelines to provide information for emergency shutdown systems. • Integration of ambient seabed temperatures as provided by UK Met. • Composition tracking including the possibility to track user specified trace components. • Estimated arrival times and volumes of “off-specification” gas. • Tracking of the parentage of batches such that the party responsible for off-spec gas can be identified (polluter pays principle). • Facilities to restart models from historic data with the possibility to remove erroneous inputs. • Continuous running of look-ahead cases based on user defined transient time series and nominations for contractual exit points. • Using larger network models to plan and monitor mixing of gasses to prevent off-spec gas. Comparisons between simulated and measured values will be made to illustrate the accuracy of the hydraulic models. In addition, the application of Maximum Likelihood State Estimation will be discussed to demonstrate its effectiveness in overcoming measurement errors.


2019 ◽  
Vol 42 ◽  
Author(s):  
Hanna M. van Loo ◽  
Jan-Willem Romeijn

AbstractNetwork models block reductionism about psychiatric disorders only if models are interpreted in a realist manner – that is, taken to represent “what psychiatric disorders really are.” A flexible and more instrumentalist view of models is needed to improve our understanding of the heterogeneity and multifactorial character of psychiatric disorders.


2019 ◽  
Vol 42 ◽  
Author(s):  
Don Ross

AbstractUse of network models to identify causal structure typically blocks reduction across the sciences. Entanglement of mental processes with environmental and intentional relationships, as Borsboom et al. argue, makes reduction of psychology to neuroscience particularly implausible. However, in psychiatry, a mental disorder can involve no brain disorder at all, even when the former crucially depends on aspects of brain structure. Gambling addiction constitutes an example.


Author(s):  
S. R. Herd ◽  
P. Chaudhari

Electron diffraction and direct transmission have been used extensively to study the local atomic arrangement in amorphous solids and in particular Ge. Nearest neighbor distances had been calculated from E.D. profiles and the results have been interpreted in terms of the microcrystalline or the random network models. Direct transmission electron microscopy appears the most direct and accurate method to resolve this issue since the spacial resolution of the better instruments are of the order of 3Å. In particular the tilted beam interference method is used regularly to show fringes corresponding to 1.5 to 3Å lattice planes in crystals as resolution tests.


1995 ◽  
Author(s):  
Robert T. Trotter ◽  
Anne M. Bowen ◽  
James M. Potter

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