Mathematisch-statistische Simulierung der mechanischen Eigenschaften von Bauspanplatten

Physical and process manufacturing factors affecting the properties of particleboard were examined and mathematical relationships were derived to predict board modulus of elasticity and internal bond. The equations, derived from a series of previous laboratory investigations, allow the simulation of the effects of various process conditions on final properties of 1/2-inch (12-mm) boards.     

Simulation of the initial stages of nucleation and growth of Au/NaCl(100)

The results of a computer simulation of the initial stages of the nucleation and growth of gold on NaCl(100) are presented. A potential energy scaling Monte Carlo model employing a 50 × 50 array, mobile monomers, dimers and trimers, and gold atom vertical “roll up” was used. The parameters in the model were obtained from the work of Robinson and Robins, other published sources and/or found by calculation. Simulations of the migration of single gold adatoms over the surface permitted the determination of the diffusion coefficient as a function of the reciprocal temperature which returned the same activation energy given by the potential field, thus indicating the consistency of the model. Initial cluster densities were determined using deposition rates of R_d = 10¹⁵cm^-2s^-1 and R_d = 10¹⁴cm^-2s^-1 over the temperature range T=200–425 K. Initial cluster growth was found to occur primarily by surface phase transport and resulted in clusters that were shaped like very thin disks. Using the equations from the work of Velfe and coworkers, calculations were made to extrapolate the computer simulation data in order to permit an indirect comparison with the data of Robinson and Robins. Good agreement was achieved. Initial condensation coefficients determined over a 250 ms interval showed that α ≈ 0 at T > 425 K and α ≈ 1 at T < 325 K for a deposition rate of R_d=10¹⁵ cm^-2 s^-1.     

Effects of flux enhancing polymer on the characteristics of sludge in membrane bioreactor process.

A newly developed membrane performance enhancer (MPE) was used to prevent membrane fouling in a membrane bioreactor (MBR) process. It transpired that 1,000 mg/l of MPE reduced polysaccharide levels from 41 mg/I to 21 mg/I on average under the experimental condition. Repeated experiments also confirmed that 50-1,000 mg/l of MPE could reduce membrane fouling significantly and increase the intervals between membrane cleanings. Depending on MPE dosages and experimental conditions, trans-membrane pressure (TMP) increase was suppressed for 20-30 days, while baseline TMP surged within a few days. In addition, MPE allowed MBR operation even at 50,000 mg/l of total solid and reduced permeate COD. However, no evidence of toxicity for sludge was found from respiratory works.     

An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet.

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.     

Corrosion Behavior of 316LN and 316 Stainless Steels During Long-term Exposure to Aerated 0.5 M NaCl Using Electrochemical Noise Technique

In the present work 316LN as well as 316 stainless steel (SS) coupons each of dimensions (0.025 × 0.018 × 0.006 m³) in well-polished condition were used as two nominal electrodes which were immersed in the aerated solution of 0.5 M NaCl. Correlated current and potential electrochemical noise (EN) signals were collected at 1 Hz sampling frequency for 1 h daily over a period of 30 days. The detrended EN data were used to calculate the noise resistance (R _N) as well as the spectral noise resistance at zero frequency (R _SN^o) values and other statistical parameters. To study the nature of pits and distribution of their diameters as well as depths, extensive observations of the pitted and the blank specimens were carried out using Confocal Laser Scanning Microscopy (CLSM). The current and the potential records of the two alloys showed distinct differences in their corrosion behavior. It was observed that within less than 4 h of immersion, 316SS showed signals indicative of unstable pitting and onset of stable pitting was noticed after 48 h of exposure. However, until about 24 h, 316LN showed just the random signals and unstable pitting was observed after 28 h. The signals clearly indicated continuous growth of the stable pits in 316SS as against the repassivation of the unstable pits in 316LN after 7 days exposure. It was observed that R _N values showed a continuous decrease in the case of 316SS, but were quite stable in the case of 316LN over the exposure period. Concurrent to these observations it was observed that 316SS specimen was extensively pitted. The frequency distributions of pit diameters as well pit depths were observed to be highest at 10-20 μm and 5-10 μm, respectively. However, pits with as large as 70-80 μm diameter and as deep as 20-25 μm too were observed. No pits were observed in case of 316LN even after 30 days of exposure, an observation that corroborates well with the stable R _N values. Thus, in the present investigation, the long-term tests using EN technique coupled with CLSM studies conclusively prove that many unstable pits initiated in 316SS turn into stable ones resulting in insidious localized corrosion attack whereas the unstable pits initiated in 316LN get passivated in the simulated coastal environment.     

Perfect Blind-Channel Shortening for Multicarrier Systems

In multicarrier systems, when the order of a channel impulse response is larger than the length of the cyclic prefix (CP), there is a significant performance degradation due to interblock interference (IBI). This paper proposes a blind-channel shortening method in which the equalizer parameter vector is formed by the noise subspace of the received signal correlation matrix so that the output power is maximized. The proposed method can not only shorten the effective channel impulse response to within the CP length but also maximize the output signal-to-interference-and-noise ratio while eliminating the IBI. We point out that the performance depends on the choice of a decision delay and propose a simple method for determining the appropriate delay. We propose both a batch algorithm and an adaptive algorithm and show by simulation that they are superior to the conventional algorithms.     

An order-specific clustering algorithm for the determination of representative demand curves

Data clustering consists of a group of procedures used to collect similar entries or data points within a set into clusters. No existing clustering technique considers entries sequentially in time. In some cases, it is desirable to generate clusters that represent a segment of a time-ordered data set. For these purposes, an order-specific clustering algorithm is proposed. The proposed algorithm employs representative load curves to describe the clusters it generates. The capabilities of the order-specific clustering algorithm are demonstrated on a case study using electricity demand data for the province of Ontario, Canada. Two different applications of the clustering algorithm on this data set are given to demonstrate the effect of error threshold values on the formation of clusters. An analysis of the error for each of these clustering applications is presented.