Shuffled Complex Evolution Optimization Algorithm Research Articles

Kinetic modeling of thermal degradation of TDI/MDI-based flexible polyurethane foam under nitrogen and air atmospheres with Shuffled Complex Evolution algorithm: Insights from TG-FTIR analysis

This study investigates the thermal degradation mechanisms and kinetics of TDI/MDI-based flexible polyurethane foam (FPUF) under nitrogen and air atmospheres, employing thermogravimetric (TG) analysis in conjunction with TG-FTIR technique. The information gleaned from these analysis is used to construct kinetic model based on model-free approaches coupled with the Shuffled Complex Evolution optimization algorithm. The results uncovered the five-step complex thermal degradation process of TDI/MDI-based FPUF compared to TDI-based or MDI-based polyurethane in both atmospheres. In nitrogen atmosphere, this involve the dissociation of TDI- and MDI-based urethane bonds, breakage of recombined urea bonds, random chain scission of polyol, and further degradation of incompletely pyrolyzed solid products. In air atmosphere, the process emcompasses dissociation of TDI- and MDI-based urethane linkages, accelerated oxidation of polyol chains, consumption of urea groups, and combustion of partially oxidized intermediates. This work also emphasizes the limitations of solely relying on TG tests for kinetic modeling, necessitating the integration of TG tests and TG-FTIR technique to obtain a comprehensive understanding of degradation mechanisms. The significance of the acquired insights lies in their potential to reshape the design of thermo-chemical reactors, resulting in heightened resource recovery, diminished environmental impact, and a stride towards a circular economy within the polyurethane industry.

A pyrolysis model for the thermal decomposition of low-density polyethylene blended with ammonium polyphosphate and pentaerythritol

In this work, a semi-empirical pyrolysis model is developed to predict the thermal decomposition behavior of an intumescent fire retardant (IFR) system consisting of ammonium polyphosphate/pentaerythritol (APP/PER) with the ratio 3:1 (wt/wt) in a low-density polyethylene (LDPE) matrix. This work is based on a previously developed semi-global reaction mechanism for the degradation of LDPE and APP/PER, which consists of two consecutive first-order reactions for the LDPE and five first and second-order reactions for the APP/PER combination. The apparent properties that define heat transport inside the pyrolyzing solid are determined via inverse modeling of cone calorimeter experiments for the pure LDPE and then for the complete IFR system. This is achieved by using the Shuffled Complex Evolution optimization algorithm. The flame heat flux in the cone calorimeter experiments is also evaluated by targeting the heat release rate (HRR) data in the optimization process of one of the cone radiative heat setups. The optimized parameters and flame heat feedback are in line with the literature and the robustness of the model is assessed by a comparison with the experimental data for a wide range of cone heat fluxes. Ignition times and peaks of HRR and total HRs are within the engineering accuracy whatever the flux conditions for both pure LDPE and the IFR system.

Pyrolysis and combustion behavior study of PMMA waste from micro-scale to bench-scale experiments

With the increasing use of polymethyl methacrylate (PMMA), there is growing concern about its waste utilization. It is of great significance to study its pyrolysis and combustion behaviors, then a series of experiments were conducted from micro-scale (thermogravimetry, fourier transform infrared spectroscopy and mass spectrometry) to bench-scale (fire propagation apparatus and cone calorimeter). By the micro-scale experiments, the pyrolysis kinetic model was established and kinetic parameters were obtained by coupling the Shuffled Complex Evolution optimization algorithm. Moreover, based on the inferred pyrolysis gases and functional groups, the possible chemical reactions of PMMA pyrolysis from molecular structure were also put forward. By the bench-scale experiments, the pyrolysis and combustion behaviors were further studied by coupling the pyrolysis kinetics and mass/heat transfer process, including mass loss rate, heat release rate and CO2/CO production. The obtained pyrolysis and combustion characteristics by the multi-scale experiments would be helpful for the further energy utilization.

Energy Utilization of Algae Biomass Waste Enteromorpha Resulting in Green Tide in China: Pyrolysis Kinetic Parameters Estimation Based on Shuffled Complex Evolution

Enteromorpha is a species of algae biomass that is spread widely and has resulted in green tides in China in recent years. It was urgent to explore an appropriate method for taking advantage of the ocean waste as an energy supply in the current sustainable development. Pyrolysis, as the first step of thermochemical conversion in energy utilization, was given attention in order to study its behavior based on thermogravimetric experiments over a wide heating-rate range from 5 to 60 K/min. The whole pyrolysis process was divided into three stages: water evaporation, the main components decomposition, and carbonate decomposition. To estimate the detailed kinetic parameters (activation energy, the pre-exponential factor, and reaction order etc.), the Kissinger method was used to establish the original kinetic parameters at different stages and provide the parameter search range for the next heuristic algorithm, and then the Shuffled Complex Evolution optimization algorithm was coupled and first applied to the algae biomass pyrolysis. Eventually, the predicted results of mass loss rate based on the optimized kinetic parameters agreed well with the thermogravimetric experimental data, with the R2 value being up to 0.92 for all the heating rates.

A purpose-oriented shuffled complex evolution optimization algorithm for energy management of multi-microgrid systems considering outage duration uncertainty

A purpose-oriented shuffled complex evolution optimization algorithm for energy management of multi-microgrid systems considering outage duration uncertainty

Development of Equations for Meander Movement Velocities by SCE Optimization Algorithm based on Experimental Study

Meandering rivers have a dynamic planform, which means that rivers move in radial direction with variable velocities. The movement velocities can be estimated from historical maps of specific river or using mathematical approach. There is not explicit method or suitable algebraic equation for estimation of river meander movement velocities. In this study, experiments were carried out in a laboratory flume, to develop novel equations to calculate meandering river movement velocities. We designated these empirical equations as the river resistance equations. The experiments were conducted with non-uniform, nonchosive sediment in a re-circulating flume with changeable slopes. The influence of bankfull discharge, bed slope and channel width on the meander movement velocities were discussed. Based on the experimental data, three novel empirical equations for prediction of Wx and Wexp and Wm were proposed. Moreover, the shuffled complex evolution (SCE) optimization algorithm was used to estimate the unknown parameters of the empirical equations. To validate SCE method, the result was compared with traditional multiple regression analysis. This comparison indicated that the SCE optimization algorithm outperformed the multiple regression analysis method in the empirical equations calibration.

Automatic Calibration Tool for Hydrologic Simulation Program-FORTRAN Using a Shuffled Complex Evolution Algorithm

Hydrologic Simulation Program-Fortran (HSPF) model calibration is typically done manually due to the lack of an automated calibration tool as well as the difficulty of balancing objective functions to be considered. This paper discusses the development and demonstration of an automated calibration tool for HSPF (HSPF-SCE). HSPF-SCE was developed using the open source software “R”. The tool employs the Shuffled Complex Evolution optimization algorithm (SCE-UA) to produce a pool of qualified calibration parameter sets from which the modeler chooses a single set of calibrated parameters. Six calibration criteria specified in the Expert System for the Calibration of HSPF (HSPEXP) decision support tool were combined to develop a single, composite objective function for HSPF-SCE. The HSPF-SCE tool was demonstrated, and automated and manually calibrated model performance were compared using three Virginia watersheds, where HSPF models had been previously prepared for bacteria total daily maximum load (TMDL) development. The example applications demonstrate that HSPF-SCE can be an effective tool for calibrating HSPF.

Relating hydrograph components to rainfall and streamflow: a case study from northern Taiwan

This study investigates the characteristics of hydrograph components from a watershed in Taiwan. Hydrograph components were modelled by using a model of three serial reservoirs with one parallel reservoir. Mean rainfall was calculated by using the block kriging method. The model parameters for 38 events were calibrated by using the shuffled complex evolution optimization algorithm. The model verification was made using 18 events. Based on the study results, the following findings were obtained: (1) for single-peak events, times to peak of hydrograph components are an increasing power function of the peak time of rainfall; (2) peak discharges of hydrograph components are linearly proportional to that of total runoff, and the ratios of quick and slow runoff are approximately 83% and 17% of total runoff, respectively; and (3) the total volume of quick runoff component is 52% of total runoff and that of slow runoff is 27%. Editor D. Koutsoyiannis Citation Li, Y.-J., Cheng, S.-J. Pao, T.-L. and Bi, Y.-J., 2012. Relating hydrograph components to rainfall and streamflow: a case study from northern Taiwan. Hydrological Sciences Journal, 57 (5), 861–877.

Bias correction of satellite rainfall estimates using a radar-gauge product – a case study in Oklahoma (USA)

Abstract. Hourly Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products. SPEs are prone to larger systematic errors and more uncertainty sources in comparison with ground based radar and gauge precipitation products. The present work develops an approach to seamlessly blend satellite, radar and gauge products to fill gaps in ground-based data. To mix different rainfall products, the bias of any of the products relative to each other should be removed. The study presents and tests a proposed ensemble-based method which aims to estimate spatially varying multiplicative biases in hourly SPEs using a radar-gauge rainfall product and compare it with previously used bias correction methods. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. Bias field parameters were determined on a daily basis using the shuffled complex evolution optimization algorithm. To include more error sources, ensembles of bias factors were generated and applied before bias field generation. We demonstrate this method using two satellite-based products, CPC Morphing (CMORPH) and Hydro-Estimator (HE), and a radar-gauge rainfall Stage-IV (ST-IV) dataset for several rain events in 2006 over Oklahoma. The method was compared with 3 simpler methods for bias correction: mean ratio, maximum ratio and spatial interpolation without ensembles. Bias ratio, correlation coefficient, root mean square error and mean absolute difference are used to evaluate the performance of the different methods. Results show that: (a) the methods of maximum ratio and mean ratio performed variably and did not improve the overall correlation with the ST-IV in any of the rainy events; (b) the method of interpolation was consistently able to improve all the performance criteria; (c) the method of ensembles outperformed the other 3 methods.

Predicting Hydrologic Response to Climate Change in the Luohe River Basin Using the SWAT Model

This article assesses the effect of potential future climate change on streamflow in the Luohe River basin. The predicted future climate change by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) and two general circulation models (HadCM3 and CGCM2) were applied. SWAT (Soil and Water Assessment Tool), a physically based distributed hydrological model, was calibrated using daily streamflow records from 1992 to 1996 with a powerful shuffled complex evolution optimization algorithm (SCE-UA) and validated using daily streamflow records from 1997 to 2000. The calibration and validation results showed that the SWAT model was able to simulate the daily streamflow well, with a coefficient of determination and Nash-Sutcliffe efficiency greater than 0.7 and 0.5, respectively, for both the calibration and validation periods. Using the average streamflow from 1992 to 2000 as a baseline, the simulated annual average streamflow showed almost no change in the near future (around 2020) and increased by approximately 10% by 2050. Predicted seasonal average streamflow showed changes within 20%. Monthly average streamflow showed changes within 20% for all months except May, which showed predicted monthly streamflow increases of as much as 60%. Based on model results, the Luohe River basin will likely experience a small change in streamflow by the mid-21st century. However, the uncertainty associated with climate change scenarios and general circulation model outputs need to be carefully evaluated in regard to future water policies and strategies.

Principles and practical aspects of an automatic calibration procedure for urban rainfall-runoff models

Automatic methods for model calibration take advantage of the speed and power of computers, while being objective and relatively easy to implement. This paper presents the principles of automatic calibration applicable for urban rainfall-runoff modelling. The automatic scheme was developed by modifying the computer code of the MOUSE software package to include the shuffled complex evolution optimization algorithm with appropriate objective functions. The kinematic wave model was applied for the surface runoff computation. The output of the rainfall-runoff modelling was used to design a sedimentation basin. The practical aspects of applying automatic calibration results using different objectives are elaborated. It is clearly demonstrated that the proposed automatic scheme can be applied in urban water engineering design.

A split operator approach to reactive transport with the forward particle tracking Eulerian Lagrangian localized adjoint method

A forward particle tracking Eulerian Lagrangian localized adjoint method (ELLAM) is applied to the multicomponent reactive transport problem using a split operator approach. Two split operator algorithms are compared, the Strang algorithm and the sequential non-iterative algorithm (SNIA). The reaction equations are integrated using a coupled predictor corrector algorithm with adaptive time stepping. Reaction time steps are adjusted at the inflow boundary to reflect the actual time of transport inside the solution domain. Results show that split operator ELLAM formulations are competitive with direct or fully coupled ELLAM solutions for reactive transport problems. The SNIA algorithm is more accurate than the Strang splitting algorithm when large time steps are used. The reaction algorithm employed dominates computational effort in runs with large time step sizes. To illustrate the use of the method in practical problems, the model is fitted to aerobic aniline degradation data from laboratory scale column experiments. Model inversion is achieved using non-linear regression with a shuffled complex evolution optimization algorithm and parameter uncertainty is assessed using a Bayesian uncertainty analysis procedure.