Dynamics of a Proportional Fluidic Amplifier: Part 1

1970 ◽  
Vol 92 (2) ◽  
pp. 303-310 ◽  
Author(s):  
R. A. Humphrey ◽  
F. T. Brown
Keyword(s):  
Dynamic Behavior ◽  
Complex Number ◽  
Large Scale ◽  
Wide Band ◽  
Atmospheric Conditions ◽  
Experimental Procedure ◽  
General Experimental Procedure ◽  
Asme Paper

A general experimental procedure is described for determining the complete linearized characteristics of a fluidic component over a wide band of frequencies. The method is applied to a large-scale Corning proportional amplifier with a 0.054-in. throat for frequencies up to over 3 kHz. Similarity was preserved for a 1/4 scale amplifier operating at atmospheric conditions. Since all eight independent complex-number self and transfer admittances are given for linearization about the symmetrical state, the results can be used to predict the behavior of the amplifier in any compatible coupled or uncoupled environment. The paper is continued in Part 2, ASME Paper No. 69-WA/Flcs-3, with an examination of the causes of the observed dynamic behavior in this and other proportional amplifiers.

scholarly journals Atmospheric Conditions Associated with Labrador Sea Deep Convection: New Insights from a Case Study of the 2006/07 and 2007/08 Winters

2016 ◽  
Vol 29 (14) ◽  
pp. 5281-5297 ◽  
Author(s):  
Who M. Kim ◽  
Stephen Yeager ◽  
Ping Chang ◽  
Gokhan Danabasoglu
Keyword(s):  
North America ◽  
North Atlantic ◽  
Large Scale ◽  
Initial Conditions ◽  
Deep Convection ◽  
La Niña ◽  
Labrador Sea ◽  
Atmospheric Conditions ◽  
Circulation Anomaly ◽  
La Nina

Abstract Deep convection in the Labrador Sea (LS) resumed in the winter of 2007/08 under a moderately positive North Atlantic Oscillation (NAO) state. This is in sharp contrast with the previous winter with weak convection, despite a similar positive NAO state. This disparity is explored here by analyzing reanalysis data and forced-ocean simulations. It is found that the difference in deep convection is primarily due to differences in large-scale atmospheric conditions that are not accounted for by the conventional NAO definition. Specifically, the 2007/08 winter was characterized by an atmospheric circulation anomaly centered in the western North Atlantic, rather than the eastern North Atlantic that the conventional NAO emphasizes. This anomalous circulation was also accompanied by anomalously cold conditions over northern North America. The controlling influence of these atmospheric conditions on LS deep convection in the 2008 winter is confirmed by sensitivity experiments where surface forcing and/or initial conditions are modified. An extended analysis for the 1949–2009 period shows that about half of the winters with strong heat losses in the LS are associated with such a west-centered circulation anomaly and cold conditions over northern North America. These are found to be accompanied by La Niña–like conditions in the tropical Pacific, suggesting that the atmospheric response to La Niña may have a strong influence on LS deep convection.

Dynamic behavior of diffusion flame interacting with a large-scale vortex by laser imaging techniques

2005 ◽  
Vol 30 (1) ◽  
pp. 465-473 ◽  
Author(s):  
Masaharu Komiyama ◽  
Tomoya Fujimura ◽  
Toshimi Takagi ◽  
Shinichi Kinoshita
Keyword(s):  
Dynamic Behavior ◽  
Diffusion Flame ◽  
Large Scale ◽  
Imaging Techniques ◽  
Laser Imaging ◽  
Large Scale Vortex

scholarly journals Domain-Adversarial Training of Self-Attention-Based Networks for Land Cover Classification Using Multi-Temporal Sentinel-2 Satellite Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2564
Author(s):  
Mauro Martini ◽  
Vittorio Mazzia ◽  
Aleem Khaliq ◽  
Marcello Chiaberge
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Domain Adaptation ◽  
Learning Approaches ◽  
Atmospheric Conditions ◽  
Practical Applications ◽  
Area Of Interest ◽  
Multi Temporal ◽  
Significant Performance ◽  
Adversarial Training

The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and crop classification (LC&CC). Moreover, with the introduction of self-attention and introspection mechanisms, deep learning approaches have shown promising results in processing long temporal sequences in the multi-spectral domain with a contained computational request. Nevertheless, most practical applications cannot rely on labeled data, and in the field, surveys are a time-consuming solution that pose strict limitations to the number of collected samples. Moreover, atmospheric conditions and specific geographical region characteristics constitute a relevant domain gap that does not allow direct applicability of a trained model on the available dataset to the area of interest. In this paper, we investigate adversarial training of deep neural networks to bridge the domain discrepancy between distinct geographical zones. In particular, we perform a thorough analysis of domain adaptation applied to challenging multi-spectral, multi-temporal data, accurately highlighting the advantages of adapting state-of-the-art self-attention-based models for LC&CC to different target zones where labeled data are not available. Extensive experimentation demonstrated significant performance and generalization gain in applying domain-adversarial training to source and target regions with marked dissimilarities between the distribution of extracted features.

scholarly journals Cloud-to-ground lightning in Portugal: patterns and dynamical forcing

2012 ◽  
Vol 12 (3) ◽  
pp. 639-649 ◽  
Author(s):  
J. A. Santos ◽  
M. A. Reis ◽  
J. Sousa ◽  
S. M. Leite ◽  
S. Correia ◽  
...  
Keyword(s):  
Large Scale ◽  
Bimodal Distribution ◽  
Lightning Activity ◽  
Atmospheric Conditions ◽  
Remote Forcing ◽  
Cloud To Ground Lightning ◽  
Using Data ◽  
Number Of Discharges ◽  
Low Pressures ◽  
Large Scale Atmospheric Circulation

Abstract. An analysis of the cloud-to-ground discharges (CGD) over Portugal is carried out using data collected by a network of sensors maintained by the Portuguese Meteorological Institute for 2003–2009 (7 yr). Only cloud-to-ground flashes are considered and negative polarity CGD are largely dominant. The total number of discharges reveals a considerable interannual variability and a large irregularity in their distribution throughout the year. However, it is shown that a large number of discharges occur in the May–September period (71%), with a bimodal distribution that peaks in May and September, with most of the lightning activity recorded in the afternoon (from 16:00 to 18:00 UTC). In spring and autumn the lightning activity tends to be scattered throughout the country, whereas in summer it tends to be more concentrated over northeastern Portugal. Winter generally presents low lightning activity. Furthermore, two significant couplings between the monthly number of days with discharges and the large-scale atmospheric circulation are isolated: a regional forcing, predominantly in summer, and a remote forcing. In fact, the identification of daily lightning regimes revealed three important atmospheric conditions for triggering lightning activity: regional cut-off lows, cold troughs induced by remote low pressure systems and summertime regional low pressures at low-tropospheric levels combined with a mid-tropospheric cold trough.

Application of Wide-Band Ultrasound for the Detection of Angled Crack Features in Oil and Gas Pipelines

2018 ◽  
Author(s):  
Willem Vos ◽  
Petter Norli ◽  
Emilie Vallee
Keyword(s):  
Large Scale ◽  
Crack Detection ◽  
Oil And Gas ◽  
Wide Band ◽  
Theoretical Background ◽  
Proof Of Concept ◽  
Offshore Pipelines ◽  
Large Scale Testing ◽  
Theoretical Predictions ◽  
Set Up

This paper describes a novel technique for the detection of cracks in pipelines. The proposed in-line inspection technique has the ability to detect crack features at random angles in the pipeline, such as axial, circumferential, and any angle in between. This ability is novel to the current ILI technology offering and will also add value by detecting cracks in deformed pipes (i.e. in dents), and cracks associated with the girth weld (mid weld cracks, rapid cooling cracks and cracks parallel to the weld). Furthermore, the technology is suitable for detection of cracks in spiral welded pipes, both parallel to the spiral weld as well as perpendicular to the weld. Integrity issues around most features described above are not addressed with ILI tools, often forcing operators to perform hydrostatic tests to ensure pipeline safety. The technology described here is based on the use of wideband ultrasound inline inspection tools that are already in operation. They are designed for the inspection of structures operating in challenging environments such as offshore pipelines. Adjustments to the front-end analog system and data collection from a grid of transducers allow the tools to detect cracks in any orientation in the line. Description of changes to the test set-up are presented as well as the theoretical background behind crack detection. Historical development of the technology will be presented, such as early laboratory testing and proof of concept. The proof of concept data will be compared to the theoretical predictions. A detailed set of results are presented. These are from tests that were performed on samples sourced from North America and Europe which contain SCC features. Results from ongoing testing will be presented, which involved large-scale testing on SCC features in gas-filled pipe spools.

scholarly journals Optimal Estimation MSG-SEVIRI Clear-Sky Total Column Water Vapour Retrieval Using the Split Window Difference

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1256
Author(s):  
Jan El Kassar ◽  
Cintia Carbajal Henken ◽  
Rene Preusker ◽  
Jürgen Fischer
Keyword(s):  
Water Vapour ◽  
Large Scale ◽  
Pearson Correlation ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Forward Model ◽  
Observation Data ◽  
Atmospheric Conditions ◽  
Uncertainty Estimates ◽  
Total Column

A new algorithm for the retrieval of day-time total column water vapour (TCWV) from measurements of a MSG-SEVIRI (Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager) instrument is presented. The retrieval is based on a forward operator, at the core of which lies Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV). This forward model relates TCWV and surface temperature to brightness temperatures in the split window at 11 and 12µm with the use of a first guess for temperature and humidity profiles from the ERA5 reanalysis. The forward model is then embedded in a full Optimal Estimation (OE) method, which yields pixel by pixel uncertainty estimates and performance indicators. The algorithm is applicable to any instrument which features the split window configuration, given a first guess for atmospheric conditions (i.e., from NWP) and an estimate of surface emissivity at 11 µm. The algorithm was developed within the framework of RealPEP (Near-Realtime Quantitative Precipitation Estimation and Prediction) in which the advancement of the estimation and nowcasting of extreme precipitation and flooding in Germany are studied. Thus, processing and validation has been limited to the German domain. Three independent ground-based TCWV observation data sets were used as reference, i.e., AERONET (Aerosol Robotic Network), GNSS Germany (Global Navigation Satellite System) and measurements from two MWR (Microwave Radiometer) sites. The validation concludes with good agreement, with absolute biases between 0.11 and 2.85 kg/m2, root mean square deviations (rmsds) between 1.63 and 3.24 kg/m2 and Pearson correlation coefficients ranging from 0.96 to 0.98. The retrievals uncertainty estimates were evaluated against AERONET. The comparison suggests that, in sum, uncertainties are estimated well, while still some error sources seem to be over- and underestimated. In limited case studies it could be shown that SEVIRI TCWV is capable to both display large scale variabilities in water vapour fields and reproduce the daily course of water vapour exposed by ground-based observations.

Large-Scale Sensor Network Analysis

2013 ◽  
pp. 314-347 ◽  
Author(s):  
Joaquin Vanschoren ◽  
Ugo Vespier ◽  
Shengfa Miao ◽  
Marvin Meeng ◽  
Ricardo Cachucho ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Large Scale ◽  
Vital Signs ◽  
Sensor Data ◽  
Atmospheric Conditions ◽  
Big Data Applications ◽  
The World ◽  
Sheer Size ◽  
Effective Use

Sensors are increasingly being used to monitor the world around us. They measure movements of structures such as bridges, windmills, and plane wings, human’s vital signs, atmospheric conditions, and fluctuations in power and water networks. In many cases, this results in large networks with different types of sensors, generating impressive amounts of data. As the volume and complexity of data increases, their effective use becomes more challenging, and novel solutions are needed both on a technical as well as a scientific level. Founded on several real-world applications, this chapter discusses the challenges involved in large-scale sensor data analysis and describes practical solutions to address them. Due to the sheer size of the data and the large amount of computation involved, these are clearly “Big Data” applications.

Atmospheric forcing of coastal polynyas in the south-western Weddell Sea

2015 ◽  
Vol 27 (4) ◽  
pp. 388-402 ◽  
Author(s):  
Verena Haid ◽  
Ralph Timmermann ◽  
Lars Ebner ◽  
Günther Heinemann
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Weddell Sea ◽  
Small Scale ◽  
Atmospheric Conditions ◽  
Atmospheric Forcing ◽  
The South ◽  
Ice Production

AbstractThe development of coastal polynyas, areas of enhanced heat flux and sea ice production strongly depend on atmospheric conditions. In Antarctica, measurements are scarce and models are essential for the investigation of polynyas. A robust quantification of polynya exchange processes in simulations relies on a realistic representation of atmospheric conditions in the forcing dataset. The sensitivity of simulated coastal polynyas in the south-western Weddell Sea to the atmospheric forcing is investigated with the Finite-Element Sea ice-Ocean Model (FESOM) using daily NCEP/NCAR reanalysis data (NCEP), 6 hourly Global Model Europe (GME) data and two different hourly datasets from the high-resolution Consortium for Small-Scale Modelling (COSMO) model. Results are compared for April to August in 2007–09. The two coarse-scale datasets often produce the extremes of the data range, while the finer-scale forcings yield results closer to the median. The GME experiment features the strongest winds and, therefore, the greatest polynya activity, especially over the eastern continental shelf. This results in higher volume and export of High Salinity Shelf Water than in the NCEP and COSMO runs. The largest discrepancies between simulations occur for 2008, probably due to differing representations of the ENSO pattern at high southern latitudes. The results suggest that the large-scale wind field is of primary importance for polynya development.

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