Design of facultative ponds based on uncertainty analysis

1996 ◽  
Vol 33 (7) ◽  
pp. 41-47 ◽  
Author(s):  
Marcos von Sperling
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Wastewater Treatment ◽  
Uncertainty Analysis ◽  
Accurate Determination ◽  
Effluent Quality ◽  
Uniform Distributions ◽  
Wastewater Treatment Systems ◽  
Selection Of

The paper presents a methodology for the utilisation of the Uncertainty analysis based on Monte Carlo simulations for the design of wastewater treatment systems. The special and important case of facultative-ponds design is exemplified. The design is carried out a large number of times, each run with different values of the inputs, randomly selected from uniform distributions within ranges which define the designer's uncertainty with the data. The results are interpreted statistically, giving elements for the selection of more or less conservative designs, according to the resulting effluent quality. The procedure for undertaking a Sensitivity Analysis is also described and exemplified, allowing the designer to concentrate more efforts on a more accurate determination of those inputs found to be significantly important.

scholarly journals A Two-Fluid Model for High Viscosity Upward Annular Flow in Vertical Pipes

2021 ◽  
Author(s):  
Joseph X. F. Ribeiro ◽  
Ruiquan Liao ◽  
Aliyu M. Aliyu ◽  
Salem K. B. Ahmed ◽  
Yahaya D. Baba ◽  
...  
Keyword(s):  
Fluid Model ◽  
Accurate Determination ◽  
Flow Characteristics ◽  
High Viscosity ◽  
Two Phase ◽  
Friction Factors ◽  
Two Fluid Model ◽  
Two Fluid ◽  
Selection Of

Selection of appropriate friction factors is paramount for accurate prediction of key flow characteristics in gas–liquid two-phase flows. In this work, experimental investigation of vertical air and oil (with viscosities up to 200 mPa s) flow in a 0.060-m ID pipe is reported. Superficial air and oil velocity ranges utilized are from 22.37 to 59.06 m/s and 0.05 to 0.16 m/s respectively. The influence of estimation of interfacial friction factor on accurate determination of film thickness, void fraction and pressure gradient was investigated using a two-fluid model. The results indicated that the two-fluid model is capable of accurately predicting flow characteristics. Further, it reveals that the best performing correlations are the Belt et al. and Ambrosini et al. correlations.

scholarly journals Uncertainty and sensitivity analysis for reducing greenhouse gas emissions from wastewater treatment plants

2020 ◽  
Author(s):  
Giorgio Mannina ◽  
Alida Cosenza ◽  
Taise Ferreira Rebouças
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Wastewater Treatment ◽  
Uncertainty Analysis ◽  
Total Nitrogen ◽  
Wastewater Treatment Plants ◽  
Ghg Emissions ◽  
Sensitivity Testing ◽  
N2o Formation ◽  
Operational Conditions

Abstract This paper presents the sensitivity and uncertainty analysis of a plant-wide mathematical model for wastewater treatment plants (WWTPs). The mathematical model assesses direct and indirect (due to the energy consumption) greenhouse gases (GHG) emissions from a WWTP employing a whole-plant approach. The model includes: i) the kinetic/mass-balance based model regarding nitrogen; ii) two-step nitrification process; iii) N2O formation both during nitrification and denitrification (as dissolved and off-gas concentration). Important model factors have been selected by using the Extended-Fourier Amplitude Sensitivity Testing (FAST) global sensitivity analysis method. A scenario analysis has been performed in order to evaluate the uncertainty related to all selected important model factors (scenario 1), important model factors related to the influent features (scenario 2) and important model factors related to the operational conditions (scenario 3). The main objective of this paper was to analyse the key factors and sources of uncertainty at a plant-wide scale influencing the most relevant model outputs: direct and indirect (DIR,CO2eq and IND,CO2eq, respectively), effluent quality index (EQI), chemical oxygen demand (COD) and total nitrogen (TN) effluent concentration (CODOUT and TNOUT, respectively). Sensitivity analysis shows that model factors related to the influent wastewater and primary effluent COD fractionation exhibit a significant impact on direct, indirect and EQI model factors. Uncertainty analysis reveals that outflow TNOUT has the highest uncertainty in terms of relative uncertainty band for scenario 1 and scenario 2. Therefore, uncertainty of influential model factors and influent fractionation factors has a relevant role on total nitrogen prediction. Results of the uncertainty analysis show that the uncertainty of model prediction decreases after fixing stoichiometric/kinetic model factors.

scholarly journals Forecasting Wastewater Temperature Based on Artificial Neural Network (ANN) Technique and Monte Carlo Sensitivity Analysis

2020 ◽  
Vol 12 (16) ◽  
pp. 6386 ◽  
Author(s):  
Farzin Golzar ◽  
David Nilsson ◽  
Viktoria Martin
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Artificial Neural Network ◽  
Monte Carlo ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Heat Recovery ◽  
Historical Data ◽  
Treatment Plant ◽  
Artificial Neural Network Ann

Wastewater contains considerable amounts of thermal energy. Heat recovery from wastewater in buildings could supply cities with an additional source of renewable energy. However, variations in wastewater temperature influence the performance of the wastewater treatment plant. Thus, the treatment is negatively affected by heat recovery upstream of the plant. Therefore, it is necessary to develop more accurate models of the wastewater temperature variations. In this work, a computational model based on artificial neural network (ANN) is proposed to calculate wastewater treatment plant influent temperature concerning ambient temperature, building effluent temperature and flowrate, stormwater flowrate, infiltration flowrate, the hour of day, and the day of year. Historical data related to the Stockholm wastewater system are implemented in MATLAB software to drive the model. The comparison of calculated and observed data indicated a negligible error. The main advantage of this ANN model is that it only uses historical data commonly recorded, without any requirements of field measurements for intricate heat transfer models. Moreover, Monte Carlo sensitivity analysis determined the most influential parameters during different seasons of the year. Finally, it was shown that installing heat exchangers in 40% of buildings would reduce 203 GWh year−1 heat loss in the sewage network. However, heat demand in WWTP would be increased by 0.71 GWh year−1, and the district heating company would recover 176 GWh year−1 less heat from treated water.

Accurate Determination of Critical Safety Height During Available Safe Egress Time Assessment

2016 ◽  
Vol 13 (10) ◽  
pp. 7545-7547
Author(s):  
Xuefeng Han ◽  
Yao Deng ◽  
Xiaomei Wang ◽  
Juncheng Jiang
Keyword(s):  
Numerical Simulation ◽  
Heat Release ◽  
Heat Release Rate ◽  
Release Rate ◽  
Accurate Determination ◽  
Hazard Index ◽  
Simulation Results ◽  
Time Assessment ◽  
Selection Of

When evaluating the ASET (available safe egress time), the fire scenario and the heat release rate (HRR) of the fire need to be set firstly according to the function and the combustible materials of the building, then CFD (Computational Fluent Dynamics) software is used to perform simulations. The ASET is obtained at the time when the hazard index of smoke reaches the minimum value at a safety height, and this height could be defined as critical safety height. It is very important to select critical safety height and heat release rate for the accuracy of the simulation results. The variation of selection of the critical safety height in references is large and it is lacking of credible evidence. This paper discusses the critical safety height based on statistics, probability and ergonomicsvvso as to improve the accuracy, credibility and reliability of the numerical simulation.

Optimization Design of Single Steering Trapezoid Mechanism of Vehicle Based on MATLAB

2012 ◽  
Vol 490-495 ◽  
pp. 2499-2504
Author(s):  
Ai Hua Ren ◽  
Chuan Qiong Sun
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Optimization Design ◽  
Research Direction ◽  
Selection Of Variables ◽  
Analysis Of Results ◽  
Actual Operation ◽  
Matlab Programming ◽  
Selection Of

Firstly the optimum mathematical model of single steering trapezoid mechanism of vehicle was established gradually through selection of variables, setting constraints, determination of objective function. And then the optimum calculation is carried out with MATLAB programming in the case of EQ1092, and the problem occurring in actual operation that the optimum results changed with initial points was solved. In the end the further optimum research direction of this mechanism was intuitively pointed out through visualization and sensitivity analysis of results.

scholarly journals Influence of organic compound functionality on aerosol hygroscopicity: dicarboxylic acids, alkyl-substituents, sugars and amino acids

2017 ◽  
Vol 17 (9) ◽  
pp. 5583-5599 ◽  
Author(s):  
Aleksandra Marsh ◽  
Rachael E. H. Miles ◽  
Grazia Rovelli ◽  
Alexander G. Cowling ◽  
Lucy Nandy ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Amino Acids ◽  
Organic Compounds ◽  
Accurate Determination ◽  
Dicarboxylic Acids ◽  
Original Data ◽  
Set Up ◽  
Complex Organic ◽  
Selection Of

Abstract. Hygroscopicity data for 36 organic compounds, including amino acids, organic acids, alcohols and sugars, are determined using a comparative kinetics electrodynamic balance (CK-EDB). The CK-EDB applies an electric field to trap-charged aqueous droplets in a chamber with controlled temperature and relative humidity (RH). The dual micro dispenser set-up allows for sequential trapping of probe and sample droplets for accurate determination of droplet water activities from 0.45 to > 0.99. Here, we validate and benchmark the CK-EDB for the homologous series of straight-chain dicarboxylic acids (oxalic–pimelic) with measurements in better agreement with Universal Quasichemical Functional Group Activity Coefficients (UNIFAC) predictions than the original data used to parametrise UNIFAC. Furthermore, a series of increasingly complex organic compounds, with subtle changes to molecular structure and branching, are used to rigorously assess the accuracy of predictions by UNIFAC, which does not explicitly account for molecular structure. We show that the changes in hygroscopicity that result from increased branching and chain length are poorly represented by UNIFAC, with UNIFAC under-predicting hygroscopicity. Similarly, amino acid hygroscopicity is under-predicted by UNIFAC predictions, a consequence of the original data used in the parametrisation of the molecular subgroups. New hygroscopicity data are also reported for a selection of alcohols and sugars and they show variable levels of agreement with predictions.

scholarly journals Procedure for Determining the Uncertainties in the Modeling of Surface Roughness in the Turning of NiTi Alloys Using the Monte Carlo Method

Materials ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 4338 ◽  
Author(s):  
Małgorzata Kowalczyk ◽  
Krzysztof Tomczyk
Keyword(s):  
Surface Roughness ◽  
Monte Carlo ◽  
Point Of View ◽  
Machining Process ◽  
Machining Parameters ◽  
Optimal Selection ◽  
Niti Alloys ◽  
The Monte Carlo Method ◽  
Selection Of

The paper presents a procedure for the determination of uncertainties in the modeling of surface roughness in the turning of NiTi alloys. The presented procedure is applicable both to the analysis of the measurement values of the two main roughness factors, as well as to research related to the prediction and optimization of the machining process. Type A and B, total, and expanded uncertainties were considered herein, and the obtained uncertainty values were assessed. A procedure for optimizing machining by applying the Monte Carlo (MC) method is also presented. The solutions presented in this paper are important from the point of view of practical solutions related to the prediction and optimization of the machining process. The considered procedure for determining and assessing uncertainty can be useful for the optimal selection of both machining parameters and measuring tools.

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