Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.     

Analysis of phosphorus removal and anaerobic selector performance in a full-scale activated sludge process in Singapore.

This paper analyses the performance of the anaerobic selector (A/O process) in a full-scale activated sludge process receiving mostly industrial sewage discharge (> 60%) in Singapore. In addition to the sludge settleability, enhanced biological phosphorus removal (EBPR) was studied. The sludge volume index (SVI) reduced from 200 to 80 ml g(-1) and foaming was suppressed significantly, indicating the effectiveness of the anaerobic selector in improving sludge settleability. The phosphorus removal efficiency was 66%, and 7.5 mg HAc-COD was consumed per mg PO4(3-) -P removed. In the anaerobic compartment, 31% of the SCOD and 73% of the acetic acid in the settled sewage were removed with PO4(3-) -P release of 14.1 mg PO4(3-)-P l(-1). The linear correlation between PO4(3-) -P release in the anaerobic compartment and PO4(3-) -P uptake in the aerobic compartment indicates that there is about 0.8 mg PO4(3-) -P release in the anaerobic compartment per mg PO34(3-) -P uptake in the aerobic compartment. The fates of volatile fatty acids (VFAs) and its short chain acids (SCAs) in the process were studied and discussed.     

Co-digestion of ruminal content and blood from slaughterhouse industries: influence of solid concentration and ammonium generation.

At the present time, organic solid wastes from industries and agricultural activities are considered to be promising substrates for biogas production via anaerobic digestion. Moreover solids stabilisation is required before reutilization or disposal. Slaughterhouses are among the most important industries in Uruguay and produce 150,000 tons of ruminal content (RC) and 30,000 tons of blood per year. In order to determine the influence of the solids and blood contents, the ammonia inhibition and the inoculum adaptation co-digestion batch tests were performed. A set of experiences with TS concentration of 2.5%, 5% and 7.5% and different ratios of RC/blood were carried out using an inoculum from an UASB reactor. In all experiences fast blood hydrolisation was observed. A higher methane production was detected in the experiences with higher TS content. However, the fraction of solids degradation was lower in these experiences. A plateau in the biogas production was found. The free ammonia level, which was above the reported inhibitory levels, could explain this behaviour. After the inhibition period the biogas production restarted probably due to the biomass acclimatisation to the ammonia. In order to determine the inoculum adaptation a new experiment was performed. The inoculum used was the sludge coming from the first set of experiences. Based upon batch tests a 3.5 m3 pilot reactor was designed and started up. Ammonia inhibition was avoided by the start-up strategy and in two weeks the biogas production was 3.5 m3/d. The VS stabilisation with a solid retention time of 20 days was of 43%. The pilot reactor working at steady state had a TS concentration of 3-4% with a ratio of RC/blood of 10:1 at the entrance.     

Catalytic aminolysis of epoxide by alumina prepared from amine-protected Al precursor

The catalytic activities of alumina prepared from an Al alkoxide-amine adduct monomer for the reaction of cyclopentene oxide with piperidine was determined after various pretreatments, including calcination and exposure to moisture. They were compared with the activity of alumina prepared by the conventional hydrolysis method. It was found that the as-prepared sample from the alkoxide-amine monomer preparation was five times more active than a conventional preparation, suggesting that it has a higher density of surface Lewis acid sites. However, its activity was much more severely suppressed by exposure to moisture.     

Stability analysis of a feedback-controlled resonant DC-DC converter

This paper reports on the stability analysis of one member of a dual-channel resonant DC-DC converter family. The study is confined to the buck configuration in symmetrical operation. The output voltage of the converter is controlled by a closed loop applying constant-frequency pulsewidth modulation. The dynamic analysis reveals that a bifurcation cascade develops as a result of increasing the loop gain. The trajectory of the variable-structure piecewise-linear nonlinear system pierces through the Poincare plane at the fixed point in state space when the loop gain is small. For stability criterion the positions of the characteristic multipliers of the Jacobian matrix belonging to the Poincare map function defined around the fixed point located in the Poincare plane is applied. In addition to the stability analysis, a bifurcation diagram is developed showing the four possible states of the feedback loop: the periodic, the quasi-periodic, the subharmonic, and the chaotic states. Simulation and test results verify the theory.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Start-up and steady-state results of a full-scale UASB reactor treating malting wastewater.

An Imhoff tank was reconstructed into a 250 m3 UASB reactor in order to treat a malting plant wastewater. The UASB was inoculated with sludge from an anaerobic lagoon used for slaughterhouse wastewater treatment. After two months of operation the reactor achieved full load with an HRT of 17 h, a COD removal higher than 80% and a biogas production of 300 m3/day (77% average methane content), with an organic loading rate of 3.6 kgCOD/m3.d (0.24 kgCOD/kgVSS.d). A yield coefficient of 0.09 gVSS/gCODrem was found from a mass balance. The fat present in the inoculated sludge (48 mg/gSSV) did not affect the start up performance. Sludge from the inoculum with high content of fat (270 mg/gSSV), was separated by flotation in the first week of operation. The COD removal efficiency was scarcely influenced by the reactor operation temperature (17-25 degrees C).     

LiNbO3 optical waveguides formed in a new proton source

Proton-exchanged planar waveguides have been fabricated on Z-cut and X-cut lithium niobate crystals by using a new proton source formed by a mixture of benzoic and adipic acids. Waveguide index profiles and optical characteristics have been obtained at different values of the adipic-benzoic acid concentration ratio. The samples have been structurally characterized by Raman and infrared (IR) absorption spectroscopy and double-crystal X-ray diffraction. Good quality samples have been fabricated by using 30 mol% ratio dilution, showing very low scattering levels (<0.1 dB/cm), relatively high electrooptic coefficient (r₃₃=0.88 pm/V), and low relative percentage of interstitial protons (26%). The main factor limiting the waveguide optical properties is the substitutional-interstitial proton ratio, which can be easily controlled to produce good quality waveguides. A demonstration of the repeatability of the exchange process in the acid mixture is also provided     

Application of neural networks and machine learning in networkdesign

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END's efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies