Diamond in the Rough Model Sheet: Refi ning Character Designs

2015 ◽  
pp. 231-252
Keyword(s):  
Rough Model

Experimental Investigation of Roughness Effect on Ship Resistance Using Flat Plate and Model Towing Tests

2017 ◽  
Vol 61 (02) ◽  
pp. 75-90
Author(s):  
Evangelia D. Kiosidou ◽  
Dimitrios E. Liarokapis ◽  
Georgios D. Tzabiras ◽  
Dimitrios I. Pantelis
Keyword(s):  
Flat Plate ◽  
Resistance Coefficient ◽  
Extrapolation Method ◽  
Total Resistance ◽  
Roughness Effect ◽  
Towing Tank ◽  
Ship Model ◽  
Rough Model ◽  
Smooth Model ◽  
Flow Stimulation

Towing tests on a thin flat plate of 3-mm thickness and on a ship model in smooth and rough condition were performed and extrapolation to ship scale was attempted. A newly designed experimental setup was constructed for the examination of the thin plate. The experiments on smooth flat plate included examination of a series of trip wires for flow stimulation, among which the optimum was 1.3 mm. In rough condition, the plate was covered with sandpapers of 40 and 80 grit. Both calculated roughness functions exhibited Nikuradse behavior, verifying the validity of the experiments. The equivalent sand roughness height was 1.7 times the average sandpaper roughness, as calculated by the Schlichting diagram for sand-roughened plates. Both roughness functions indicated transitionally rough regime, except for the last two data of the rougher sandpaper that lay on the fully rough regime. The results were extrapolated to ship scale using Granville method. Extrapolation of smooth model results in ship scale revealed that the traditional Froude method predicts higher resistance coefficient compared to the International Towing Tank Conference (ITTC) 78 method. Rough model results were extrapolated to ship scale by applying a newly proposed extrapolation method, using Schlichting resistance formula for rough plates as the friction correlation line, according to Froude method and for two length scales, namely the plate and ship length. The two versions of the proposed extrapolation method provided an upper and lower limit for the predicted rough hull total resistance coefficient.

Computation of Normal Depth in Trapezoidal Open Channel Using the Rough Model Method

2014 ◽  
Vol 955-959 ◽  
pp. 3231-3237
Author(s):  
Bachir Achour
Keyword(s):  
Aspect Ratio ◽  
Turbulent Flow ◽  
Friction Factor ◽  
Linear Dimension ◽  
Open Channel ◽  
Discharge Energy ◽  
Flow Discharge ◽  
Model Method ◽  
Rough Model ◽  
Depth Relationship

The recurring problem of calculating the normal depth in a trapezoidal open channel is easily solved by the rough model method. The Darcy-Weisbach relationship is applied to a referential rough model whose friction factor is arbitrarily chosen. This leads to establish the non-dimensional normal depth relationship in the rough model. Through a non-dimensional correction factor of linear dimension, the aspect ratio and therefore normal depth in the studied channel is deduced. Keywords: Rough model method, Trapezoidal channel, Normal depth, Turbulent flow, Discharge, Energy slope.

Past, present, and future of geophysical inversion—A new millennium analysis

Geophysics ◽  
2001 ◽  
Vol 66 (1) ◽  
pp. 21-24 ◽  
Author(s):  
Sven Treitel ◽  
Larry Lines
Keyword(s):  
Inverse Problem ◽  
Review Article ◽  
Data Sets ◽  
Inversion Process ◽  
Geophysical Inversion ◽  
Field Recordings ◽  
Theory To Practice ◽  
Rough Model ◽  
Recorded Data

Geophysicists have been working on solutions to the inverse problem since the dawn of our profession. An interpreter infers subsurface properties on the basis of observed data sets, such as seismograms or potential field recordings. A rough model of the process that produces the recorded data resides within the interpreter’s brain; the interpreter then uses this rough mental model to reconstruct subsurface properties from the observed data. In modern parlance, the inference of subsurface properties from observed data is identified with the solution of a so‐called “inverse problem.” In contrast, the “forward problem” consists of the determination of the data that would be recorded for a given subsurface configuration and under the assumption that given laws of physics hold. Until the early 1960s, geophysical inversion was carried out almost exclusively within the geophysicist’s brain. Since then, we have learned to make the geophysical inversion process much more quantitative and versatile by recourse to a growing body of theory, along with the computer power to reduce this theory to practice. We should point out the obvious, however, namely that no theory and no computer algorithm can presumably replace the ultimate arbiter who decides whether the results of an inversion make sense or nonsense: the geophysical interpreter. Perhaps our descendants writing a future third Millennium review article can report that a machine has been solving the inverse problem without a human arbiter. For the time being, however, what might be called “unsupervised geophysical inversion” remains but a dream.

scholarly journals Chezy’s resistance coefficient in an egg-shaped conduit

2018 ◽  
Vol 37 (1) ◽  
pp. 87-96
Author(s):  
Imed Loukam ◽  
Bachir Achour ◽  
Lakhdar Djemili
Keyword(s):  
Kinematic Viscosity ◽  
Research Work ◽  
Resistance Coefficient ◽  
Filling Rate ◽  
Rough Model ◽  
Major Disadvantage ◽  
Longitudinal Slope ◽  
The Absolute ◽  
Explicit Relation ◽  
Problem Data

Abstract When calculating uniform flows in open conduits and channels, Chezy’s resistance coefficient is not a problem data and its value is arbitrarily chosen. Such major disadvantage is met in all the geometric profiles of conduits and channels. Knowing the value of this coefficient is essential to both the design of the channel and normal depth calculation. The main objective of our research work is to focus upon the identification of the resistance coefficient relationship. On the basis of the rough model method (RMM) for the calculation of conduits and channels, a general explicit relation of the resistance coefficient in turbulent flow is established with different geometric profiles, particularly the egg-shaped conduit. Chezy’s resistance coefficient depends strongly on the filling rate, the discharge, the longitudinal slope, the absolute roughness of the internal walls of the conduit and the kinematic viscosity of the liquid. Moreover, in this work, a simplified method is presented to determine Chezy’s resistance coefficient with a limited number of data, namely the discharge, the slope of the conduit, the absolute roughness and the kinematic viscosity. Last but not least, after studying the variation of Chezy’s resistance coefficient as a function of the filling rate, an equally explicit expression is given for the easy calculation of this coefficient when its maximum value is reached. Examples of calculation are suggested in order to show how the Chezy’s coefficient can be calculated in the egg-shaped conduit.

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