Evaluation of elemental depletion weathering rate estimation methods on acid-sensitive soils of north-eastern Alberta, Canada

Geoderma ◽  
2011 ◽  
Vol 166 (1) ◽  
pp. 189-197 ◽  
Author(s):  
Colin J. Whitfield ◽  
Shaun A. Watmough ◽  
Julian Aherne
Keyword(s):  
Estimation Methods ◽  
Weathering Rate ◽  
Rate Estimation ◽  
North Eastern ◽  
Elemental Depletion

scholarly journals Experimental Verification of Real-Time Flow-Rate Estimations in a Tilting-Ladle-Type Automatic Pouring Machine

2021 ◽  
Vol 11 (15) ◽  
pp. 6701
Author(s):  
Yuta Sueki ◽  
Yoshiyuki Noda
Keyword(s):  
Real Time ◽  
Molten Metal ◽  
Flow Rate ◽  
Kalman Filters ◽  
Estimation Method ◽  
Estimation Methods ◽  
Liquid Volume ◽  
Model Parameters ◽  
Rate Estimation ◽  
Time Flow

This paper discusses a real-time flow-rate estimation method for a tilting-ladle-type automatic pouring machine used in the casting industry. In most pouring machines, molten metal is poured into a mold by tilting the ladle. Precise pouring is required to improve productivity and ensure a safe pouring process. To achieve precise pouring, it is important to control the flow rate of the liquid outflow from the ladle. However, due to the high temperature of molten metal, directly measuring the flow rate to devise flow-rate feedback control is difficult. To solve this problem, specific flow-rate estimation methods have been developed. In the previous study by present authors, a simplified flow-rate estimation method was proposed, in which Kalman filters were decentralized to motor systems and the pouring process for implementing into the industrial controller of an automatic pouring machine used a complicatedly shaped ladle. The effectiveness of this flow rate estimation was verified in the experiment with the ideal condition. In the present study, the appropriateness of the real-time flow-rate estimation by decentralization of Kalman filters is verified by comparing it with two other types of existing real-time flow-rate estimations, i.e., time derivatives of the weight of the outflow liquid measured by the load cell and the liquid volume in the ladle measured by a visible camera. We especially confirmed the estimation errors of the candidate real-time flow-rate estimations in the experiments with the uncertainty of the model parameters. These flow-rate estimation methods were applied to a laboratory-type automatic pouring machine to verify their performance.

scholarly journals Bit Error Rate Estimation Methods for QPSK CO-OFDM Transmission

2014 ◽  
Vol 32 (17) ◽  
pp. 2951-2959 ◽  
Author(s):  
Son Thai Le ◽  
Keith J. Blow ◽  
Vladimir K. Mezentsev ◽  
Sergei K. Turitsyn
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Estimation Methods ◽  
Rate Estimation

scholarly journals Dual-wavelength radar technique development for snow rate estimation: a case study from GCPEx

2019 ◽  
Vol 12 (2) ◽  
pp. 1409-1427 ◽  
Author(s):  
Gwo-Jong Huang ◽  
Viswanathan N. Bringi ◽  
Andrew J. Newman ◽  
Gyuwon Lee ◽  
Dmitri Moisseev ◽  
...  
Keyword(s):  
Particle Size ◽  
Power Law ◽  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Hydrodynamic Theory ◽  
Estimation Methods ◽  
Fall Velocity ◽  
Large Variability ◽  
Ka Band ◽  
Rate Estimation

Abstract. quantitative precipitation estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the prefactor of the power law due to changes in particle size distribution (PSD), density, and fall velocity, whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter), thus reducing the variability due to the prefactor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is falls in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold-season Precipitation Experiment). Since the particle mass can be estimated using 2-D video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare it directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z–SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

scholarly journals Comparison of Bit Error Rate Estimation Methods for QPSK CO-OFDM Transmission

2014 ◽  
Vol 26 (22) ◽  
pp. 2244-2247 ◽  
Author(s):  
Son Thai Le ◽  
Mary E. McCarthy ◽  
Naoise Mac Suibhne ◽  
Elias Giacoumidis ◽  
Nick J. Doran ◽  
...  
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Estimation Methods ◽  
Rate Estimation

scholarly journals Detection of LFM Radar Signals and Chirp Rate Estimation Based on Time-Frequency Rate Distribution

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5415
Author(s):  
Ewa Swiercz ◽  
Dariusz Janczak ◽  
Krzysztof Konopko
Keyword(s):  
Parameter Estimation ◽  
Instantaneous Frequency ◽  
Estimation Methods ◽  
Joint Analysis ◽  
Cubic Phase ◽  
Chirp Rate ◽  
Time Frequency ◽  
Rate Estimation ◽  
Detection And Estimation ◽  
Frequency Rate

Linear frequency-modulated (LFM) signals are the most significant example of waveform used in low probability of intercept (LPI) radars, synthetic aperture radars and modern communication systems. Thus, interception and parameter estimation of the signals is one of the challenges in Electronic Support (ES) systems. The methods, which are widely used to accomplish this task are mainly based on transformations from time to time-frequency domain, which concentrate the energy of signals along an instantaneous frequency (IF) line. The most popular examples of such transforms are the short time Fourier transform (STFT) and Wigner-Ville distribution (WVD). However, for LFM waveforms, methods that concentrate signal energy along a line in the time-frequency rate domain may allow to obtain better detection and estimation performance. This type of transformation can be obtained using the cubic phase (CP) function (CPF). In the paper, the detection of LFM waveform and its chirp rate (CR) parameter estimation based on the extended forms of the standard CPF is proposed. The CPF was originally introduced for instantaneous frequency rate (IFR) estimation for quadratic frequency modulated (QFM) signals i.e., cubic phase signals. Summation or multiplication operations on time cross-sections of the CPF allow to formulate the extended forms of the CPF. Based on these forms, detection test statistics and the estimation procedure of LFM signal parameters have been proposed. The widely known estimation methods assure satisfying accuracy for high SNR levels, but for low SNRs the reliable estimation is a challenge. The proposed approach based on joint analysis of detection and estimation characteristics allows to increase the reliability of chirp rate estimates for low SNRs. The results of Monte-Carlo simulation investigations on LFM signal detection and chirp rate estimation evaluated by the mean squared error (MSE) obtained by the proposed methods with comparisons to the Cramer-Rao lower bound (CRLB) are presented.

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