A Methodology for the Analysis of Physical Model Scale Effects on the Simulation of Wave Propagation up to Wave Breaking: Preliminary Physical Model Results

2008 ◽  
Author(s):  
Conceic¸a˜o Fortes ◽  
Maria da Grac¸a Neves ◽  
Joa˜o Alfredo Santos ◽  
Rui Capita˜o ◽  
Artur Palha ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Physical Model ◽  
Scale Effects ◽  
National Laboratory ◽  
Physical Models ◽  
Type Model ◽  
Research Activity ◽  
Joint Research ◽  
Common Structure ◽  
Constant Slope

This paper describes the experiments performed at the National Laboratory for Civil Engineering (LNEC) aiming at simulating, in a flume, the wave propagation along a constant slope bottom that ends on a sea wall coastal defence structure, a common structure employed in the Portuguese coast. The objective of these tests is to calibrate the parameters of FUNWAVE, a Boussinesq type model, for wave propagation in coastal regions. This is the first step in the validation of a methodology to combine numerical and physical models in the study of the interactions between beaches and structures. This work is performed in the framework of the Composite Modelling of the Interactions between Beaches and Structures (CoMIBBs) project, a joint research activity of the HYDRALAB III European project.

scholarly journals Influence of scale on the daylighting system evaluation in physical models: Experimental method based on objective and subjective measurements

2021 ◽  
Vol 2042 (1) ◽  
pp. 012121
Author(s):  
Safa Daich ◽  
Mohamed Yacine Saadi ◽  
Barbara E.A Piga ◽  
Ahmed Motie Daiche
Keyword(s):  
Physical Model ◽  
Scale Effects ◽  
Physical Models ◽  
Subjective Evaluations ◽  
Test Models ◽  
Scale Models ◽  
Measurement Results ◽  
Illuminance Level ◽  
Survey Results ◽  
Sky Conditions

Abstract The daylight evaluation in architectural spaces can be carried out using several tools and methods of investigation and analysis. However, many types of research have proven the usefulness of the scale models to evaluate daylighting system performances in buildings. Several scales of a physical model have been used varying between (1:50) and real scale (1:1), and no comparative study has been done to evaluate the effect of the model size in daylighting assessment. The objective of this investigation is to make a comparison between two different scales of a physical model: the first one is a model with a scale of (1:12) while the second is with the scale of (1: 4), aiming to study the scale effects on daylight perception with models equipped with a daylighting system under very high exterior illuminance levels. The methodology of this study consists in collecting simultaneously the measurement of the exterior and interior illuminance level (lux) and subjective evaluations from a questionnaire survey with the two scale models (1:4 and 1:12) under real sky conditions. A correlation between collected data has been explored. Comparing the measurement results, it is obvious that the quantity of light that penetrates the test models (1:4 and 1:12) was the same. The results are with a range of ±1.6%. Moreover, survey results show that the participants’ perceptions regarding satisfaction, light distribution and glare questions differ with the scale of the physical 3D model. The subjects felt more satisfied with the luminous atmosphere with the physical model of (1:4) compared with the model of (1:12).

scholarly journals Two-Dimensional Numerical Modeling of Flow in Physical Models of Rock Vane and Bendway Weir Configurations

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 458
Author(s):  
Drew C. Baird ◽  
Benjamin Abban ◽  
S. Michael Scurlock ◽  
Steven B. Abt ◽  
Christopher I. Thornton
Keyword(s):  
Numerical Modeling ◽  
Physical Model ◽  
Numerical Models ◽  
Hydraulic Performance ◽  
Physical Models ◽  
Protection Measures ◽  
Design Engineers ◽  
Model Study ◽  
Study Results ◽  
Wide Range

While there are a wide range of design recommendations for using rock vanes and bendway weirs as streambank protection measures, no comprehensive, standard approach is currently available for design engineers to evaluate their hydraulic performance before construction. This study investigates using 2D numerical modeling as an option for predicting the hydraulic performance of rock vane and bendway weir structure designs for streambank protection. We used the Sedimentation and River Hydraulics (SRH)-2D depth-averaged numerical model to simulate flows around rock vane and bendway weir installations that were previously examined as part of a physical model study and that had water surface elevation and velocity observations. Overall, SRH-2D predicted the same general flow patterns as the physical model, but over- and underpredicted the flow velocity in some areas. These over- and underpredictions could be primarily attributed to the assumption of negligible vertical velocities. Nonetheless, the point differences between the predicted and observed velocities generally ranged from 15 to 25%, with some exceptions. The results showed that 2D numerical models could provide adequate insight into the hydraulic performance of rock vanes and bendway weirs. Accordingly, design guidance and implications of the study results are presented for design engineers.

Model Test Study on Influences of Layered Rock Mass Dip Angle on Stability of Deep-Buried Tunnel

2011 ◽  
Vol 90-93 ◽  
pp. 2363-2371
Author(s):  
Bin Wei Xia ◽  
Ke Hu ◽  
Yi Yu Lu ◽  
Dan Li ◽  
Zu Yong Zhou
Keyword(s):  
Rock Mass ◽  
Physical Model ◽  
Model Test ◽  
Physical Models ◽  
Physical Model Test ◽  
Stress Distributions ◽  
Failure Characteristics ◽  
Layered Rock ◽  
Layered Rock Mass ◽  
Dip Angle

Physical models of layered rock mass with different dip angles are built by physical model test in accordance with the bias failure characteristics of surrounding rocks of layered rock mass in Gonghe Tunnel. Bias failure characteristics of surrounding rocks in thin-layered rock mass and influences of layered rock mass dip angle on stability of tunnel are studied. The research results show that failure characteristics of physical models generally coincide with those of surrounding rocks monitored from the tunnel site. The failure regions of surrounding rock perpendicular to the stratification planes are obviously larger than those parallel to. The stress distributions and failure characteristics in the surrounding rocks are similar to each physical model of different dip angles. The stress distributions and failure regions are all elliptic in shape, in which the major axis is in the direction perpendicular to the stratification planes while the minor axis is parallel to them. As a result, obvious bias failure of surrounding rocks has gradually formed. The physical model tests provide reliable basis for theoretical analysis on the failure mechanism of deep-buried layered rock mass.

Accelerating Climate Model Computation by Neural Networks: A Comparative Study

2021 ◽  
Author(s):  
Maha Mdini ◽  
Takemasa Miyoshi ◽  
Shigenori Otsuka
Keyword(s):  
Neural Networks ◽  
Computational Complexity ◽  
Statistical Model ◽  
Physical Model ◽  
Climate Model ◽  
Numerical Models ◽  
Computation Time ◽  
High Accuracy ◽  
Physical Models ◽  
Computer Resources

<p>In the era of modern science, scientists have developed numerical models to predict and understand the weather and ocean phenomena based on fluid dynamics. While these models have shown high accuracy at kilometer scales, they are operated with massive computer resources because of their computational complexity.  In recent years, new approaches to solve these models based on machine learning have been put forward. The results suggested that it be possible to reduce the computational complexity by Neural Networks (NNs) instead of classical numerical simulations. In this project, we aim to shed light upon different ways to accelerating physical models using NNs. We test two approaches: Data-Driven Statistical Model (DDSM) and Hybrid Physical-Statistical Model (HPSM) and compare their performance to the classical Process-Driven Physical Model (PDPM). DDSM emulates the physical model by a NN. The HPSM, also known as super-resolution, uses a low-resolution version of the physical model and maps its outputs to the original high-resolution domain via a NN. To evaluate these two methods, we measured their accuracy and their computation time. Our results of idealized experiments with a quasi-geostrophic model [SO3] show that HPSM reduces the computation time by a factor of 3 and it is capable to predict the output of the physical model at high accuracy up to 9.25 days. The DDSM, however, reduces the computation time by a factor of 4 and can predict the physical model output with an acceptable accuracy only within 2 days. These first results are promising and imply the possibility of bringing complex physical models into real time systems with lower-cost computer resources in the future.</p>

Physical Model of Estuarine Salinity Intrusion into Rivers: A Review

2014 ◽  
Vol 905 ◽  
pp. 348-352 ◽  
Author(s):  
Nuryazmeen Farhan Haron ◽  
Wardah Tahir
Keyword(s):  
Physical Model ◽  
Physical Models ◽  
Salinity Intrusion ◽  
Mixing Process ◽  
Salt Wedge ◽  
Laboratory Investigations ◽  
Estuarine Salinity

This paper reviews the physical models that had been used in order to conduct the experiment of estuarine salinity intrusion into rivers. Several studies used the physical models to get a better understanding of the estuary salinity mixing process and salt-wedge estuary characteristics along the flume. Besides, the laboratory investigations using the physical model also useful for verification purposes as discussed by previous researchers.

scholarly journals Demonstration and application of diffusive and ballistic wave propagation for drone-to-ground and drone-to-drone wireless communications

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Peter J. Burke
Keyword(s):  
Wave Propagation ◽  
Electromagnetic Wave ◽  
Path Loss ◽  
Base Station ◽  
Physical Models ◽  
Mapping Technology ◽  
Aerial Vehicle ◽  
A Cell ◽  
Independent Path ◽  
The Waves

Abstract In order to determine how an electromagnetic wave propagates from a base station to a cell phone or a wirelessly connected device, we use a novel Unmanned Aerial Vehicle (UAV) mapping technology to map the cellular network coverage at various altitudes in various terrains (flat, hilly, mountainous). For the flat terrains, the waves are shown to propagate ballistically: They have an altitude independent path loss consistent with minimal scatter in the propagation from transmitter to (aerial) receiver. In mountainous terrain, the waves are shown to propagate in the diffuse regime, and demonstrate a 10 dB increase in received signal intensity per 100′ of altitude gain, up to 400′. In the intermediate case, evidence of coherent wave interference is clearly observed in altitude independent interference patterns. These general observations can be used to build a physical or empirical model for drone-to-ground and drone-to-drone propagation, for which existing models are shown to fail. While important for building physical models of wave propagation in wireless networks, this method can be used more generally to determine the magnitude and phase of an electromagnetic wave at every point in space, as well as usher in the era of drone-to-ground and drone-to-drone communications.

Using Integration of Thermal-Balance Based and Data-Driven Models to Determine Single Duct Variable Air Volume System Cooling Baseline

2013 ◽  
Author(s):  
Gyujin Shim ◽  
Li Song ◽  
Gang Wang
Keyword(s):  
Physical Model ◽  
Least Square Method ◽  
Energy Performance ◽  
Least Square ◽  
Physical Models ◽  
Data Driven ◽  
Lumped Model ◽  
Variable Air Volume ◽  
Data Driven Approach ◽  
Cooling Coil

In order to use real-time energy measurements to identify system operation faults and inefficiencies, a cooling coil energy baseline is studied in an air-handling unit (AHU) through an integration of physical models and a data driven approach in this paper. A physical model for an AHU cooling coil energy consumption is first built to understand equipment mechanism and to determine the variables impacting cooling coil energy performance, and then the physical model is simplified into a lumped model by reducing the number of independent variables needed. Regression coefficients in the lumped model are determined statistically through searching optimal fit using the least square method with short periods of measured data. Experimental results on an operational AHU (8 ton) are presented to validate the effectiveness of this approach with statistical analysis. As a result of this experiment, the proposed cooling energy baselines at the cooling coil have ±20% errors at 99.7% confidence. Six-day data for obtaining baseline is preferred since it shows similar results as 12-day.

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