scholarly journals PyTheis—A Python Tool for Analyzing Pump Test Data

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2180
Author(s):  
Sun Woo Chang ◽  
Sama S. Memari ◽  
T. Prabhakar Clement
Keyword(s):  
Test Data ◽  
Real Field ◽  
Test Problems ◽  
Python Script ◽  
Fitting Procedure ◽  
Fitting Method ◽  
Nonlinear Curve Fitting ◽  
Pump Test ◽  
Mechanical Procedure ◽  
Two Parameters

The Theis equation is an important mathematical model used for analyzing drawdown data obtained from pumping tests to estimate aquifer parameters. Since the Theis model is a nonlinear equation, a complex graphical procedure is employed for fitting this equation to pump test data. This graphical method was originally proposed by Theis in the late 1930s, and since then, all the groundwater textbooks have included this fitting method. Over the past 90 years, every groundwater hydrologist has been trained to use this tedious procedure for estimating the values of aquifer transmissivity (T) and storage coefficient (S). Unfortunately, this mechanical procedure does not provide any intuition for understanding the inherent limitations in this manual fitting procedure. Furthermore, it does not provide an estimate for the parameter error. In this study, we employ the public domain coding platform Python to develop a script, namely, PyTheis, which can be used to simultaneously evaluate T and S values, and the error associated with these two parameters. We solve nine test problems to demonstrate the robustness of the Python script. The test problems include several published case studies that use real field data. Our tests show that the proposed Python script can efficiently solve a variety of pump test problems. The code can also be easily adapted to solve other hydrological problems that require nonlinear curve fitting routines.

Kinetic study of the Jaffé reaction for quantifying creatinine in serum: 1. Alkalinity controlled with NaOH.

1987 ◽  
Vol 33 (2) ◽  
pp. 278-285 ◽  
Author(s):  
H L Pardue ◽  
B L Bacon ◽  
M G Nevius ◽  
J W Skoug
Keyword(s):  
Curve Fitting ◽  
Interactive Effects ◽  
Kinetic Behavior ◽  
Factorial Experimental Design ◽  
Fitting Method ◽  
Nonlinear Curve Fitting ◽  
Relative Standard ◽  
Standard Additions ◽  
Curve Fitting Method ◽  
Nonlinear Curve

Abstract We studied the kinetic behavior of the reaction of alkaline picrate and creatinine and evaluated a nonlinear curve-fitting method for quantifying creatinine in serum. Using a 3 X 3 factorial experimental design, we evaluated interactive effects among temperature and concentrations of creatinine, picrate, and NaOH. We found no evidence of interference by glucose or unconjugated bilirubin; the effects of the acetoacetate reaction, which is fast, are easily compensated by the curve-fitting method. The reaction with human serum albumin is very complex, but its effects are compensated by the curve-fitting method and by preparing standards containing 50 g of albumin per liter. Calibration plots are linear under a wide variety of conditions for both aqueous standards and standard additions of creatinine to pooled serum. Reproducibility studies with standards containing creatinine at 2, 10, and 20 mg/L yielded relative standard deviations (RSD) of 8.2, 2.5, and 1.3%, corresponding to absolute variations of 0.16, 0.25, and 0.26 mg/L. The average SD for 17 sera containing creatinine at 15-50 mg/L was 0.7 mg/L. The averages of ratios (as percent) of determined vs expected concentrations in 17 sera with added creatinine (7.27 mg/L) were 97.8% for aqueous standards, 99.9% for standards with added albumin.

Influence of Shape of Region of Interest on the Architectural Parameters in Micro CT Image Analysis

2011 ◽  
Vol 340 ◽  
pp. 241-247
Author(s):  
Ya Bo Yan ◽  
Jun Wang ◽  
Wei Qi ◽  
Yang Zhang ◽  
Wei Lei
Keyword(s):  
Region Of Interest ◽  
Ct Scanning ◽  
Control Group ◽  
Micro Ct ◽  
Fitting Method ◽  
Nonlinear Curve Fitting ◽  
Significant Difference ◽  
Cylindrical Region ◽  
Ct Image Analysis ◽  
Curve Fitting Method

To study whether the architectural parameters are sensitive to the shape of volume of interests in micro-CT scanning, six human C5 body samples were scanned by micro-CT. Cubic and cylindrical volumes of interests were acquired as the length of cubic samples was being changed continually. The nonlinear curve fitting method was employed to explore the correlation between the parameters and the volume of interests. The selected morphological indices showed a significantly variable tendency for the lengths of cubic and cylindrical regions of interests, except the Tb.Th and BS/BV. The Dunnett-t tests were performed to compare the architectural parameters of different region of interests against that of control group. There was no significant difference observed between the architectural parameters from cubic region of interests and that from the cylindrical region of interests.

Implications of Applying Semi-Scale Pump Test Data to Two-Phase RCP Performance Modeling for PWR LOCA Analyses

2014 ◽  
Author(s):  
Mathew C. Jacob ◽  
Michael T. Coon ◽  
John A. Blaisdell ◽  
Ruben J. Espinosa
Keyword(s):  
Test Data ◽  
Performance Modeling ◽  
Full Scale ◽  
Performance Model ◽  
Performance Data ◽  
Performance Models ◽  
Two Phase ◽  
Coolant Pump ◽  
Pump Performance ◽  
Pump Test

Emergency Core Cooling System (ECCS) analyses using Loss of Coolant Accident (LOCA) codes utilize two-phase Reactor Coolant Pump (RCP) performance models formulated on the basis of data from tests conducted on the Semi-scale pump (Reference 1) operating at 60 Hz frequency. In some PWRs, the RCPs operate at a frequency of 50 Hz. This paper presents the results of an evaluation performed to determine the applicability of RCP two-phase performance models developed on the basis of data from the Semi-scale tests for analyzing ECCS performance of new generation PWRs. The evaluation addressed two major issues: (1) the applicability of the two-phase RCP performance model developed using the data from the Semi-scale pump tests (Reference 1) for full scale Pressurized Water Reactor (PWR) LOCA simulations, and (2) the relevance of the two-phase RCP performance model developed on the basis of test data for the Semi-scale pumps running at 60 Hz frequency to PWR RCPs running at 50 Hz frequency with higher specific speeds. Reviews of pump performance test data available in the open literature identified two-phase performance data appropriate for use in substantiating the validity of current PWR pump performance models. These data supported the conclusion that the two-phase head performance degradation for the Semi-scale Mod-1 pump is conservative compared to the two-phase pump performance data generated from testing of pumps representative of full scale PWR RCPs. A review of ECCS analyses results available in the literature determined that the use of the current RCP two-phase performance model (developed using the Semi-scale Mod-1 pump test data) for a typical PWR plant resulted in about a 100 °F increase in the Peak Clad Temperature (PCT) for a Large Break LOCA (LBLOCA) in comparison to the PCTs calculated using the two-phase pump performance model developed on the basis of test data for pumps representative of full scale PWR RCPs. It was determined from the current study that the frequency (50 Hz vs. 60 Hz) of the electrical power that drives the pump motor is not of much consequence for two-phase RCP performance modeling, since (1) the RCP performance model is characterized via normalized pump performance parameters, and (2) for the LBLOCA analysis of interest, the RCPs are assumed to lose power at the start of the event.

Spatialization of physical variables in soils by geophysical, geotechnical and geostatistic methods: the Bayesian maximum entropy data fusion approach

2021 ◽  
Author(s):  
Sara Rabouli ◽  
Vivien Dubois ◽  
Marc Serre ◽  
Julien Gance ◽  
Hocine Henine ◽  
...  
Keyword(s):  
Hydraulic Conductivity ◽  
Data Fusion ◽  
Maximum Entropy ◽  
Test Data ◽  
Saturated Hydraulic Conductivity ◽  
Geophysical Data ◽  
Real Field ◽  
Bayesian Maximum Entropy ◽  
Near Surface ◽  
Infiltration Test

<p>The soil is considered as a biological reactor or an outlet for treated domestic wastewater, respectively to reduce pollutant concentrations in the flows or because the surface hydraulic medium is too remote. In these cases, the saturated hydraulic conductivity of the soil is a key is a quantitative measure to assess whether the necessary infiltration capacity is available. To our knowledge, there is no satisfactory technique for evaluating the saturated hydraulic conductivity Ks of a heterogeneous soil (and its variability) at the scale of a parcel of soil. The aim of this study is to introduce a methodology that associates geophysical measurements and geotechnical in order to better described the near-surface saturated hydraulic conductivity Ks. Here we demonstrate here the interest of using a geostatistical approach, the BME "Bayesian Maximum Entropy", to obtain a 2D spatialization of Ks in heterogeneous soils. This tool opens up prospects for optimizing the sizing infiltration structures that receive treated wastewater. In our case, we have Electrical Resistivity Tomography (ERT) data (dense but with high uncertainty) and infiltration test data (reliable but sparse). The BME approach provides a flexible methodological framework to process these data. The advantage of BME is that it reduces to kriging as its linear limiting cases when only Gaussian data is used, but can also integrate data of other types as might be considered in future works. Here we use hard and Gaussian soft data to rigorously integrate the different data at hand (ERT, and Ks measurement) and their associated uncertainties. Based on statistical analysis, we compared the estimation performances of 3 methods: kriging interpolation of infiltration test data, the transformation of ERT data, and BME data fusion of geotechnical and geophysical data. We evaluated the 3 methods of estimation on simulated datasets and we then do a validation analysis using real field data. We find that BME data fusion of geotechnical and geophysical data provides better estimates of hydraulic conductivity than using geotechnical or geophysical data alone.</p>

scholarly journals Masses of constituent quarks confined in open bottom hadrons

2014 ◽  
Vol 29 (38) ◽  
pp. 1450202 ◽  
Author(s):  
V. Borka Jovanović ◽  
D. Borka ◽  
P. Jovanović ◽  
J. Milošević ◽  
S. R. Ignjatović
Keyword(s):  
Hyperfine Interaction ◽  
Quark Mass ◽  
Constituent Quark ◽  
Coupling Constants ◽  
Quark Masses ◽  
Fitting Procedure ◽  
Average Color ◽  
Fitting Method ◽  
Hadron Masses ◽  
B Quark

We apply color-spin and flavor-spin quark–quark interactions to the meson and baryon constituent quarks, and calculate constituent quark masses, as well as the coupling constants of these interactions. The main goal of this paper was to determine constituent quark masses from light and open bottom hadron masses, using the fitting method we have developed and clustering of hadron groups. We use color-spin Fermi–Breit (FB) and flavor-spin Glozman–Riska (GR) hyperfine interaction (HFI) to determine constituent quark masses (especially b quark mass). Another aim was to discern between the FB and GR HFI because our previous findings had indicated that both interactions were satisfactory. Our improved fitting procedure of constituent quark masses showed that on average color-spin (FB) HFI yields better fits. The method also shows the way how the constituent quark masses and the strength of the interaction constants appear in different hadron environments.

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