Sensitivity studies with a statistical downscaling method the role of the driving large scale model

2009 ◽  
Vol 18 (6) ◽  
pp. 597-606 ◽  
Author(s):  
Frank Kreienkamp ◽  
Arne Spekat ◽  
Wolfgang Enke
Keyword(s):  
Statistical Downscaling ◽  
Large Scale ◽  
Scale Model ◽  
Statistical Downscaling Method ◽  
Downscaling Method ◽  
Large Scale Model ◽  
Sensitivity Studies

RANCANG BANGUN PERANGKAT EKSPERIMENTASI PROSES PIROLISIS BIOMASA GELOMBANG MIKRO

2013 ◽  
Vol 14 (2) ◽  
Author(s):  
Noor Fachrizal
Keyword(s):  
Large Scale ◽  
Continuous Model ◽  
Biomass Energy ◽  
Scale Model ◽  
Small Scale ◽  
Laboratory Apparatus ◽  
Liquid Form ◽  
Large Scale Model ◽  
Bio Oil ◽  
Pyrolysis Of Biomass

Biomass such as agriculture waste and urban waste are enormous potency as energy resources instead of enviromental problem. organic waste can be converted into energy in the form of liquid fuel, solid, and syngas by using of pyrolysis technique. Pyrolysis process can yield higher liquid form when the process can be drifted into fast and flash response. It can be solved by using microwave heating method. This research is started from developing an experimentation laboratory apparatus of microwave-assisted pyrolysis of biomass energy conversion system, and conducting preliminary experiments for gaining the proof that this method can be established for driving the process properly and safely. Modifying commercial oven into laboratory apparatus has been done, it works safely, and initial experiments have been carried out, process yields bio-oil and charcoal shortly, several parameters are achieved. Some further experiments are still needed for more detail parameters. Theresults may be used to design small-scale continuous model of productionsystem, which then can be developed into large-scale model that applicable for comercial use.

Effect of an Oscillating Flow Direction on Leading Edge Heat Transfer

1984 ◽  
Vol 106 (1) ◽  
pp. 222-228 ◽  
Author(s):  
M. L. Marziale ◽  
R. E. Mayle
Keyword(s):  
Heat Transfer ◽  
Strouhal Number ◽  
Large Scale ◽  
Flow Direction ◽  
Leading Edge ◽  
Periodic Variation ◽  
Scale Model ◽  
Transfer Rates ◽  
Large Scale Model ◽  
Turbulence Length

An experimental investigation was conducted to examine the effect of a periodic variation in the angle of attack on heat transfer at the leading edge of a gas turbine blade. A circular cylinder was used as a large-scale model of the leading edge region. The cylinder was placed in a wind tunnel and was oscillated rotationally about its axis. The incident flow Reynolds number and the Strouhal number of oscillation were chosen to model an actual turbine condition. Incident turbulence levels up to 4.9 percent were produced by grids placed upstream of the cylinder. The transfer rate was measured using a mass transfer technique and heat transfer rates inferred from the results. A direct comparison of the unsteady and steady results indicate that the effect is dependent on the Strouhal number, turbulence level, and the turbulence length scale, but that the largest observed effect was only a 10 percent augmentation at the nominal stagnation position.

Large scale model tests on Royal Schelde SES

1989 ◽  
Author(s):  
R. DE GAAIJ ◽  
E. VAN RIETBERGEN ◽  
M. SLEGERS
Keyword(s):  
Large Scale ◽  
Model Tests ◽  
Scale Model ◽  
Large Scale Model

Experimental Study on the Behavior of a Swimming Pool Onboard a Large Passenger Ship

2009 ◽  
Vol 46 (01) ◽  
pp. 27-33
Author(s):  
Pekka Ruponen ◽  
Jerzy Matusiak ◽  
Janne Luukkonen ◽  
Mikko Ilus
Keyword(s):  
Large Scale ◽  
Hydraulic Cylinder ◽  
Operating Conditions ◽  
Swimming Pool ◽  
Scale Model ◽  
Longitudinal Motion ◽  
Sea State ◽  
Passenger Ship ◽  
Large Scale Model ◽  
Computer Controlled

The water in a swimming pool on the top deck of a large passenger ship can be excited to a resonant motion, even in a moderate sea state. The motion of the water in the pool is mainly caused by longitudinal acceleration, resulting from the ship's pitch and surge motions. At resonance, there can be high waves in the pool and splashing of water. In this study the behavior of the Solarium Pool of the Freedom of the Seas was examined in various sea states and operating conditions. The motions of the pool were calculated on the basis of a linear seakeeping method, and the behavior of the water in the pool was studied with experimental model tests. A large-scale model of the pool was constructed and fitted to a purpose-built test bench that could be axially moved by a computer-controlled hydraulic cylinder. Water elevation in the pool was measured, and all tests were video recorded. Different modifications of the pool were tested to improve the behavior of the pool. A strong correlation between the longitudinal motion and the behavior of the water in the pool was found.

Comparisons of Machine Learning Methods of Statistical Downscaling Method: Case Studies of Daily Climate Anomalies in Thailand

2021 ◽  
Author(s):  
Kanawut Chattrairat ◽  
Waranyu Wongseree ◽  
Adisorn Leelasantitham
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Performance Criteria ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Support Vector ◽  
Seasonal Temperature ◽  
Statistical Downscaling Method ◽  
Downscaling Method

The climate change which is essential for daily life and especially agriculture has been forecasted by global climate models (GCMs) in the past few years. Statistical downscaling method (SD) has been used to improve the GCMs and enables the projection of local climate. Many pieces of research have studied climate change in case of individually seasonal temperature and precipitation for simulation; however, regional difference has not been included in the calculation. In this research, four fundamental SDs, linear regression (LR), Gaussian process (GP), support vector machine (SVM) and deep learning (DL), are studied for daily maximum temperature (TMAX), daily minimum temperature (TMIN), and precipitation (PRCP) based on the statistical relationship between the larger-scale climate predictors and predictands in Thailand. Additionally, the data sets of climate variables from over 45 weather stations overall in Thailand are used to calculate in this calculation. The statistical analysis of two performance criteria (correlation and root mean square error (RMSE)) shows that the DL provides the best performance for simulation. The TMAX and TMIN were calculated and gave a similar trend for all models. PRCP results found that in the North and South are adequate and poor performance due to high and low precipitation, respectively. We illustrate that DL is one of the suitable models for the climate change problem.

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