Modelling methods for pressure balance calibration

2019 ◽  
Vol 31 (3) ◽  
pp. 034004 ◽  
Author(s):  
P Otal ◽  
C Yardin
Measurement ◽  
2018 ◽  
Vol 124 ◽  
pp. 179-183
Author(s):  
Gigin Ginanjar ◽  
In-Mook Choi ◽  
Sung-Mok Kim

2017 ◽  
Vol 48 (2) ◽  
pp. 187-197 ◽  
Author(s):  
Valerii Semyonovich Volobuyev ◽  
Anton Roaldovich Gorbushin ◽  
Iraida Alekseevna Sudakova ◽  
V. I. Tikhomirov

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sameera Senanayake ◽  
Nicholas Graves ◽  
Helen Healy ◽  
Keshwar Baboolal ◽  
Adrian Barnett ◽  
...  

Abstract Background Economic-evaluations using decision analytic models such as Markov-models (MM), and discrete-event-simulations (DES) are high value adds in allocating resources. The choice of modelling method is critical because an inappropriate model yields results that could lead to flawed decision making. The aim of this study was to compare cost-effectiveness when MM and DES were used to model results of transplanting a lower-quality kidney versus remaining waitlisted for a kidney. Methods Cost-effectiveness was assessed using MM and DES. We used parametric survival models to estimate the time-dependent transition probabilities of MM and distribution of time-to-event in DES. MMs were simulated in 12 and 6 monthly cycles, out to five and 20-year time horizon. Results DES model output had a close fit to the actual data. Irrespective of the modelling method, the cycle length of MM or the time horizon, transplanting a low-quality kidney as compared to remaining waitlisted was the dominant strategy. However, there were discrepancies in costs, effectiveness and net monetary benefit (NMB) among different modelling methods. The incremental NMB of the MM in the 6-months cycle lengths was a closer fit to the incremental NMB of the DES. The gap in the fit of the two cycle lengths to DES output reduced as the time horizon increased. Conclusion Different modelling methods were unlikely to influence the decision to accept a lower quality kidney transplant or remain waitlisted on dialysis. Both models produced similar results when time-dependant transition probabilities are used, most notable with shorter cycle lengths and longer time-horizons.


Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2798
Author(s):  
Konstanty M. Gawrylczyk ◽  
Szymon Banaszak

The paper provides a review of the modelling techniques used to simulate the frequency response of transformer windings. The aim of the research and development of modelling methods was to analyze the influence of deformations and faults in the windings on the changes in the frequency response. All described methods are given with examples of the modelling results performed by the authors of this paper and from literature sources. The research is prefaced with a thorough literature review. There are described models based on lumped parameters with input data coming from direct calculations based on the winding geometry and obtained from FEM modelling software and models considering the wave phenomena in the windings. The analysis was also performed for practical problems in winding modelling: the influence of windings other than the modelled one and the influence of parallel wires in a winding.


2021 ◽  
Vol 11 (7) ◽  
pp. 2995
Author(s):  
Tae-Hwan Kim ◽  
In-Mo Lee ◽  
Hee-Young Chung ◽  
Jeong-Jun Park ◽  
Young-Moo Ryu

Soil conditioning is a key factor in increasing tunnel face stability and extraction efficiency of excavated soil when excavating tunnels using an earth pressure balance (EPB) shield tunnel boring machine (TBM). Weathered granite soil, which is abundant in the Korean Peninsula (also in Japan, Hong Kong, and Singapore), has different characteristics than sand and clay; it also has particle-crushing characteristics. Conditioning agents were mixed with weathered granite soils of different individual particle-size gradations, and three characteristics (workability, permeability, and compressibility) were evaluated to find an optimal conditioning method. The lower and upper bounds of the water content that are needed for a well-functioning EPB shield TBM were also proposed. Through a trial-and-error experimental analysis, it was confirmed that soil conditioning using foam only was possible when the water content was controlled within the allowable range, that is, between the upper and lower bounds; when water content exceeded the upper bound, soil conditioning with solidification agents was needed along with foam. By taking advantage of the particle-crushing characteristics of the weathered granite soil, it was feasible to adopt the EPB shield TBM even when the soil was extremely coarse and cohesionless by conditioning with polymer slurries along with foam. Finally, the application ranges of EPB shield TBM in weathered granite soil were proposed; the newly proposed ranges are wider and expanded to coarser zones compared with those proposed so far.


Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 307
Author(s):  
Dawid Wojcieszak ◽  
Maciej Zaborowicz ◽  
Jacek Przybył ◽  
Piotr Boniecki ◽  
Aleksander Jędruś

Neural image analysis is commonly used to solve scientific problems of biosystems and mechanical engineering. The method has been applied, for example, to assess the quality of foodstuffs such as fruit and vegetables, cereal grains, and meat. The method can also be used to analyse composting processes. The scientific problem lets us formulate the research hypothesis: it is possible to identify representative traits of the image of composted material that are necessary to create a neural model supporting the process of assessment of the content of dry matter and dry organic matter in composted material. The effect of the research is the identification of selected features of the composted material and the methods of neural image analysis resulted in a new original method enabling effective assessment of the content of dry matter and dry organic matter. The content of dry matter and dry organic matter can be analysed by means of parameters specifying the colour of compost. The best developed neural models for the assessment of the content of dry matter and dry organic matter in compost are: in visible light RBF 19:19-2-1:1 (test error 0.0922) and MLP 14:14-14-11-1:1 (test error 0.1722), in mixed light RBF 30:30-8-1:1 (test error 0.0764) and MLP 7:7-9-7-1:1 (test error 0.1795). The neural models generated for the compost images taken in mixed light had better qualitative characteristics.


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