A simple empirical model for recycled polyurethane foams for acoustical applications.

2010 ◽  
Vol 128 (4) ◽  
pp. 2366-2366
Author(s):  
Romina del Rey Tormos ◽  
Jesús Alba Fernández ◽  
Jorge P. Arenas
Keyword(s):  
Empirical Model ◽  
Polyurethane Foams ◽  
Simple Empirical Model

A Simple Empirical Model of Data Fouling by High-Grading in Capture Fisheries

2007 ◽  
Vol 83 (1) ◽  
pp. 74-85 ◽  
Author(s):  
C. M. Wernerheim ◽  
R. L. Haedrich ◽  
S. Ussif Rashid ◽  
G. R. Munro ◽  
J. G. Sutinen
Keyword(s):  
Empirical Model ◽  
High Grading ◽  
Simple Empirical Model

scholarly journals Prediction of nitrous oxide fluxes from managed grassland on peat soil using a simple empirical model

1996 ◽  
Vol 44 (4) ◽  
pp. 339-356 ◽  
Author(s):  
G.L. Velthof ◽  
J.G. Koops ◽  
J.H. Duyzer ◽  
O. Oenema
Keyword(s):  
Nitrous Oxide ◽  
Empirical Model ◽  
Peat Soil ◽  
Flux Chamber ◽  
Mineral N ◽  
Gradient Technique ◽  
N2o Fluxes ◽  
Intensively Managed ◽  
Simple Empirical Model ◽  
Measurement Campaigns

Three measurement campaigns were carried out to answer questions related to the factors controlling variations in nitrous oxide (N2O) fluxes from intensively managed grassland on peat soil, comparison of flux measurements with a closed flux chamber method and a flux gradient technique and the development and testing of a simple empirical model for the estimation of N2O fluxes from intensively managed grassland on peat soils. Fluxes of N2O were measured with 42-48 flux chambers and ranged from less than 0.01 to 6.66 mg N/msuperscript 2 per hr. Fluxes were significantly correlated with denitrification activity (Rsuperscript 2=0.34-0.56). Contents of nitrate (NO3-) and ammonium (NH4+) in the top soil and the water-filled pore space (WFPS) explained 37-77% of the variance in N2O flux. Spatial variability of N2O fluxes was large with coefficients of variation ranging from 101 to 320%. Spatial variability was suggested to be related to distribution of mineral N fertilizer and cattle slurry, urine and dung patches and variations in groundwater level within the field. Average field fluxes obtained with the closed flux chamber method were about a factor 10 larger than those with the flux gradient technique on one measurement day but were similar on two other measurement days. The results of the measurement campaigns were used to derive a simple empirical model including total mineral N content and WFPS. This model was tested using an independent data set, i.e. the results of a monitoring study of two years carried out on two other grassland sites on peat soil. The model reasonably predicted magnitude of and temporal variations in N2O fluxes. It is suggested that a simple empirical model which requires only easily obtainable data such as mineral N content and moisture content, in combination with a few days lasting measurement campaigns, may be a valuable tool to predict N2O fluxes from similar sites.

An empirical model of denitrification

1993 ◽  
Vol 73 (4) ◽  
pp. 421-431 ◽  
Author(s):  
D. W. Bergstrom ◽  
E. G. Beauchamp
Keyword(s):  
Empirical Model ◽  
Sampling Period ◽  
Denitrification Rate ◽  
Nitrate Content ◽  
Boundary Line ◽  
Mean Values ◽  
Population Means ◽  
Episodic Events ◽  
Key Words Denitrification ◽  
Simple Empirical Model

We used a simple empirical model to predict denitrification rates from measurements of bulk soil properties. Boundary analysis was used to define relationships between denitrification rate and each of air-filled porosity, respiration rate and mineralizable-C content. The ratio of measured denitrifying enzyme activity to the maximum measured value was used to account for variation in amounts of enzymes and numbers of denitrifiers in soil. Nitrate content had little effect on denitrification rate and was excluded from the model. Because the model did not account for microscale variability, it did not accurately predict rates in individual soil cores. Nevertheless, population means and distributions of predicted and measured values were similar. The seasonal patterns of mean values of predicted and measured denitrification rates were also similar over the second half of the sampling period, which extended from May to November. The model did not account for appreciable denitrification on three dates in May. This discrepancy indicated that environmental regulation of denitrification may not be uniform over the season. The model was not sufficiently sensitive to factors influencing episodic events. Key words: Denitrification rate, model, boundary line

A simple empirical model for the clarification-thickening process in wastewater treatment plants

2014 ◽  
Vol 71 (3) ◽  
pp. 366-372
Author(s):  
Y. K. Zhang ◽  
H. C. Wang ◽  
L. Qi ◽  
G. H. Liu ◽  
Z. J. He ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Empirical Model ◽  
Wastewater Treatment Plants ◽  
Volume Index ◽  
Compression Zone ◽  
Efficient Operation ◽  
Secondary Settling ◽  
Sludge Thickening ◽  
Simple Empirical Model

In wastewater treatment plants (WWTPs), activated sludge is thickened in secondary settling tanks and recycled into the biological reactor to maintain enough biomass for wastewater treatment. Accurately estimating the activated sludge concentration in the lower portion of the secondary clarifiers is of great importance for evaluating and controlling the sludge recycled ratio, ensuring smooth and efficient operation of the WWTP. By dividing the overall activated sludge-thickening curve into a hindered zone and a compression zone, an empirical model describing activated sludge thickening in the compression zone was obtained by empirical regression. This empirical model was developed through experiments conducted using sludge from five WWTPs, and validated by the measured data from a sixth WWTP, which fit the model well (R2 = 0.98, p < 0.001). The model requires application of only one parameter, the sludge volume index (SVI), which is readily incorporated into routine analysis. By combining this model with the conservation of mass equation, an empirical model for compression settling was also developed. Finally, the effects of denitrification and addition of a polymer were also analysed because of their effect on sludge thickening, which can be useful for WWTP operation, e.g., improving wastewater treatment or the proper use of the polymer.

scholarly journals Statistical Exploration of SENTINEL-1 Data, Terrain Parameters, and in-situ Data for Estimating the Near-Surface Soil Moisture in a Mediterranean Agroecosystem

2021 ◽  
Vol 3 ◽  
Author(s):  
Sarah Schönbrodt-Stitt ◽  
Nima Ahmadian ◽  
Markus Kurtenbach ◽  
Christopher Conrad ◽  
Nunzio Romano ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Empirical Model ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Channel Network ◽  
Near Surface ◽  
Short Period ◽  
Terrain Parameters ◽  
Simple Empirical Model

Reliable near-surface soil moisture (θ) information is crucial for supporting risk assessment of future water usage, particularly considering the vulnerability of agroforestry systems of Mediterranean environments to climate change. We propose a simple empirical model by integrating dual-polarimetric Sentinel-1 (S1) Synthetic Aperture Radar (SAR) C-band single-look complex data and topographic information together with in-situ measurements of θ into a random forest (RF) regression approach (10-fold cross-validation). Firstly, we compare two RF models' estimation performances using either 43 SAR parameters (θNovSAR) or the combination of 43 SAR and 10 terrain parameters (θNovSAR+Terrain). Secondly, we analyze the essential parameters in estimating and mapping θ for S1 overpasses twice a day (at 5 a.m. and 5 p.m.) in a high spatiotemporal (17 × 17 m; 6 days) resolution. The developed site-specific calibration-dependent model was tested for a short period in November 2018 in a field-scale agroforestry environment belonging to the “Alento” hydrological observatory in southern Italy. Our results show that the combined SAR + terrain model slightly outperforms the SAR-based model (θNovSAR+Terrain with 0.025 and 0.020 m3 m−3, and 89% compared to θNovSAR with 0.028 and 0.022 m3 m−3, and 86% in terms of RMSE, MAE, and R2). The higher explanatory power for θNovSAR+Terrain is assessed with time-variant SAR phase information-dependent elements of the C2 covariance and Kennaugh matrix (i.e., K1, K6, and K1S) and with local (e.g., altitude above channel network) and compound topographic attributes (e.g., wetness index). Our proposed methodological approach constitutes a simple empirical model aiming at estimating θ for rapid surveys with high accuracy. It emphasizes potentials for further improvement (e.g., higher spatiotemporal coverage of ground-truthing) by identifying differences of SAR measurements between S1 overpasses in the morning and afternoon.

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