Application of evolutionary optimisers in data-based calibration of Activated Sludge Models

Modelling activated sludge systems has become an accepted practice in Wastewater Treatment Plant (WWTP) design, teaching and research, and Activated Sludge Models (ASM) are by far the most widely used models for activated sludge systems. In most ASM applications, calibration is based on more or less ad-hoc and trial and error approaches. Calibration of the ASMs remains the weakest link in the overall process of modelling biological wastewater treatment. In this paper, a calibration approach is proposed where the need for expert knowledge and modeller effort is significantly reduced. The calibration approach combines identifiability analysis and evolutionary optimisers to automate the ASM calibration. Identifiability analysis is used to deal with poor identifiability of the model structures and evolutionary optimisers are used to identify the model parameters. The applied evolutionary optimisers are Genetic Algorithms and Differential Evolution. Performance of the evolutionary optimisers is compared with a previously proposed calibration approach based on Monte Carlo simulations. All methods were capable of calibrating the model when given enough computation time. However, some of the evolutionary optimisation methods had an advantage in terms of computation time against the Monte Carlo method.     

Optimized laser processing of calibration blocks for grinding burn detection with Barkhausen noise

Calibration samples for the Barkhausen noise (BN) method were produced with laser processing. A planet gear wheel used for production quality control was subjected to laser irradiation to verify the BN sensor output. Different samples were found to respond similarly to the laser processing although the laser parameters needed to be adjusted for different surface qualities separately. The surface optimization for laser processing was studied with different surface qualities of samples. The ground surface was compared with a sandblasted and vibratory ground surface. The ground and sandblasted surfaces were both amenable to the laser processing whereas the vibratory grinding process created inhomogeneous surfaces for laser beam absorption. Laser processing was found to produce uniform changes in the residual stress values in two perpendicular measuring directions. The root mean square value of the BN voltage signal exhibited linear correlations with the values of the residual stress and surface hardness.     

Prediction of Residual Stresses Using Partial Least Squares Regression on Barkhausen Noise Signals

Residual stresses are quantitatively predicted based on the Barkhausen noise measurement with a partial least squares regression model. The measurements are taken from two sets of case-hardened samples. The benefits of using certain feature elimination strategies prior model identification are also studied. The elimination methods applied are correlation-based elimination, uninformative variable elimination and successive projections algorithm. The results show that the best predictions are usually obtained when the successive projections algorithm is applied. The prediction accuracy of the best models found shows that partial least squares models can be successfully used for prediction of material properties based on the Barkhausen noise measurement.     

Sorption of Pb(II), Cr(III), Cu(II), As(III) to peat,and utilization of the sorption properties in industrial waste landfill hydraulic barrier layers

The low conductivity landfill barrier layers protect the groundwater and soil by limiting the water flow through the bottom layers of the landfill material. Many materials used in hydraulic barrier layers also have sorption properties which could be used to reduce environmental risks. The adsorption of lead, chromium, copper, and arsenic to peat was studied with a batch-type test and a column test for compacted peat, both without pH adjustment in acidic conditions. Peat adsorbed all the metals well, 40 000 mg/kg of lead, 13 000 mg/kg of chromium, and 8400 mg/kg of copper in the column test. Arsenic was only tested in a batch-type test, and in that peat adsorbed 60 mg/kg of arsenic. The column test showed heavy metals to be adsorbed on the surface layers of the compacted peat sample, on the first centimeter of the sample. The adsorption was much greater in the column test than in the batch-type test, partly due to the different pH conditions and the buffer capacity of the peat in the column test. The liquid/solid ratio of the column experiment represented a time period of approximately 40 years in a landfill, under Finnish climate conditions. The hydraulic conductivity of the peat decreased as it was compressed, but it already met the hydraulic conductivity limits set by European Union legislation for the hydraulic barrier layer (1 × 10⁻⁹ m/s at a pressure of 150 kPa for a 5-m layer), with a pressure of 50 kPa. The results show that peat would be an excellent material to construct compacted, low hydraulic conductivity layers with adsorption properties in, e.g. industrial waste landfills.     

Effect of Flux Materials on the Reaction of Y2O3and SiO2

The solid-state reaction between yttrium oxide and amorphous silicon oxide with a molar ratio 1:1 has been studied. The effect of several flux materials on conversion at different temperatures (900° to 1300°C) has been investigated. Lithium compounds and especially fluoride gave the highest conversions. Fluorides of cations other than lithium were also powerful fluxes. The purity of the oxyorthosilicate formed was studied by different methods.     

Effect of A-site metal on methane combustion on 2% Pd / AMn1-x Fe x O3 (A = Ba, La, Pr; x = 0.4, 0.6, 1) perovskites

Barium, lanthanum, and praseodymium perovskites were prepared by malic acid complexation. Surface areas of the La and Pr perovskites were between 17.1 and 21.6 m² g⁻¹. The moderate low surface areas (5.7 m² g⁻¹) observed for corresponding barium perovskites were due to the high calcination temperatures. The calcination temperature also affected the shapes and sizes of the perovskite particles. According to SEM images the nanoparticles of the La and Pr perovskites were spherical, whereas those of barium perovskites were flakes. The conversion of methane increased in the order of A-site metal Ba < Pr < La. The CH₄ conversion after SO₂ treatment correlated with size of the perovskite particles: the smaller the particles the better the activity. The highest methane conversion after SO₂ treatment was achieved with lanthanum perovskite with B-site metal combination Mn_0.4Fe_0.6.     

An Efficient Procedure for Identifying the Prediction Model Between Residual Stress and Barkhausen Noise

Residual stress of case-hardened steel samples is predicted in this paper with the linear multivariable regression model. The development of the prediction model is based on the huge set of features calculated from the Barkhausen noise measurement signal among which the most suitable ones are chosen. The selection uses a genetic algorithm with leave-multiple-out cross-validation in the objective function. The original feature set contains collinear features that make the selection task even more complex. Thus a feature elimination procedure based on the successive projections algorithm is studied in this paper. Also the standard genetic algorithm is slightly modified to better serve the feature selection task. The obtained results are good showing that the proposed procedures suit well for residual stress predictions. Also the applied feature elimination procedure is applicable and can be safely used to reduce the dimensionality of the selection problem.     

Effect of biological wastewater treatment on the molecular weight distribution of soluble organic compounds and on the reduction of BOD, COD and P in pulp and paper mill effluent

Pulp and paper mill wastewater was characterizated, before (influent) and after (effluent) biological wastewater treatment based on an activated sludge process, by microfiltration (8, 3, 0.45 and 0.22mum) and ultrafiltration (100, 50, 30 and 3kDa) of the wastewater samples into different size fractions. Various parameters were measured on each fraction: molecular weight distribution (MWD) using high performance size exclusion chromatography (HPSEC), total organic carbon (TOC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (Tot-P), phosphate phosphorus (PO(4)-P), electrical conductivity, pH, turbidity, charge quantity and zeta potential. The MWD, TOC and COD(Cr) results indicated that the majority of the material present in both the influent and effluent was in the medium molecular weight (MW) range (i.e. MW<10kDa) with three main MW sub-fractions. There were no significant differences in the range of the MWD between the influent and effluent samples. The magnitude of the MWD in the effluent was about one half that in the influent, the greatest reduction being in the 6kDa fraction. The 3kDa fractions of both the influent and effluent showed a considerable increase in BOD(7), probably due to the removal of compounds harmful to bacteria in 3kDa ultrafiltration. Influent turbidity decreased considerably in microfiltration (8-0.22mum). As the turbidity was removed by 0.22mum filtration, the anionic charge quantity started to decrease. Particles in the influent and effluent contained 19-29% and 14-20% of the total phosphorus, respectively. The major phosphorus fraction was in the form of soluble phosphate.     

An 8-hour system for Salmonella detection with immunomagnetic separation and homogeneous time-resolved fluorescence PCR

We describe a system consisting of rapid sample enrichment and homogeneous end-point PCR analysis that enables the detection of Salmonella in various food matrices in 8 h. Sample preparation starts with 6 h enrichment step in supplemented broth, after which Salmonella cells are collected with immunomagnetic particles. The particles are washed and dispensed to ready-to-use PCR reaction vessels, which contain dried assay-specific reagents and an internal amplification control. PCR is performed with a novel instrument platform utilising the sensitive label technology of time-resolved fluorometry. Qualitative assay results are automatically interpreted and available in 45 min after sample addition. The overall accuracy, sensitivity and specificity of the Magda CA Salmonella system were 99.1%, 98.4% and 100.0%, respectively, based on the evaluation of 107 samples (beef, pork, poultry and ready-to-eat meals) artificially contaminated with sub-lethally injured Salmonella cells.