Extended kalman filter based nonlinear geometric control of a seeded batch cooling crystallizer

A nonlinear dynamic model of a seeded potash alum batch cooling crystallizer is presented. The model of the batch crystallizer is based on the conservation principles of mass, energy and population. In order to maintain constant supersaturation, a nonlinear geometric feedback controller is implemented. It is shown that compared to a natural and a simplified optimal cooling policies, the nonlinear geometric control (NCC) leads to a substantial improvement of the final crystal quality. An extended Kalman filter (EKF) is used as a closed loop observer for this nonlinear system to predict the non‐measurable state variables. It is found that the EKF is capable of effectively predicting the first four leading moments of the population density function. The effectiveness of the EKF based nonlinear geometric controller in the presence of plant/model mismatch is also studied. Simulation results show that the EKF based nonlinear geometric controller is reasonably robust in the presence of modeling error.     

Cascade closed-loop optimization and control of batch reactors

In this paper, a cascade closed-loop optimization and control strategy for batch reactors is proposed. Based on the reduction of a physical conservation model a cascade system is developed, which can effectively combine optimization and control to achieve good on-line optimization and tracking performance under the common condition where incomplete knowledge of the reaction system exists. A two-tier estimation scheme using a nonlinear observer for heat production rate and reaction rates is also developed. In the reaction rate estimation, calorimetric information is used. The on-line closed-loop optimization strategy uses a descending horizon dynamic optimization algorithm based on nonlinear programming and an additive unknown disturbance for feedback. A simple adaptive nonlinear tracking system is designed based on the generic model control concept. The efficiency of this strategy is demonstrated through simulations on a batch reactor under various operation conditions, such as noisy measurements, varying initial states and model mismatch.     

Measurement of solid concentration of a soluble compound in a saturated slurry

A method is proposed to measure the solid concentration of a soluble compound in a saturated slurry. The solution is gradually heated up while its temperature and monochromatic light transmittance are continuously being measured. The temperature at which the measured transmittance of the solution reaches a plateau is used to determine the solid concentration by using the solubility data of the solution. The method is successfully applied to the measurement of crystal concentration of a pure KCl slurry. The crystal concentration of two industrial slurries obtained from overflow of potash crystallizers have also been predicted. The technique has proven to be accurate in the absence of other soluble heat sensitive compounds.     

Numerical Modeling of Combined Radiation and Conduction Heat Transfer in Mineral Wool Insulations

This article addresses numerical modeling of coupled heat conduction and radiation in mineral wools under steady-state condition for prediction of its effective thermal conductivity. The radiative heat transfer is modeled using the Monte Carlo Ray-Trace Method. The radiation model is based on a random distribution of fibers in the media. The radiation distribution factor is employed in order to compute the fraction of the total radiation emitted from one fiber that is absorbed by another, due to both direct radiation and to all possible reflections within the enclosure. The radiation model is coupled with the nonlinear heat conduction equation. The results obtained by the proposed model compare well with experimental measurements of the heat flow meter apparatus. The method is easy to code, and the number of calculations during each iteration is considerably reduced.     

Drying Stress and Strain in Tension Wood: A Conventional Kiln Schedule to Efficiently Dry Mixed Tension/Normal Wood Boards in Poplar

Orthotropic drying stresses of tension and normal wood in poplar were evaluated. The degree of residual stresses was interpreted by prong and slice cutting tests. A strain gauge was employed to determine longitudinal drying stresses. Mixed tension/normal wood boards were also dried using three different schedules, T₈ F₄, T₈ F₅, and T₉ F₄ to find the best schedule. Results revealed more intense drying stress in the longitudinal and radial directions of tension wood. Despite a high susceptibility of the mixed tension/normal wood boards to drying defects, the quality of the boards dried by the schedule of T₉ F₄ was satisfactory.     

A novel method for victim block selection for NAND flash-based solid state drives based on scoring

The Journal of Supercomputing - The NAND flash memories have endurance issues in a high-performance computing (HPC) environment because of their blocks’ limited lifetime. Hence, the NAND...     

An intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks

Overlapping is one of the topics in wireless sensor networks that is considered by researchers in the last decades. An appropriate overlapping management system can prolong network lifetime and decrease network recovery time. This paper proposes an intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks, called IKOCP. This protocol uses some of the intelligent and knowledge‐based systems to construct a robust overlapping strategy for sensor networks. The overall network is partitioned to several regions by a proposed multicriteria decision‐making controller to monitor both small‐scale and large‐scale areas. Each region is managed by a sink, where the whole network is managed by a base station. The sensor nodes are categorized by various clusters using the low‐energy adaptive clustering hierarchy (LEACH)‐improved protocol in a way that the value of p is defined by a proposed support vector machine–based mechanism. A proposed fuzzy system determines that noncluster heads associate with several clusters in order to manage overlapping conditions over the network. Cluster heads are changed into clusters in a period by a suggested utility function. Since network lifetime should be prolonged and network traffic should be alleviated, a data aggregation mechanism is proposed to transmit only crucial data packets from cluster heads to sinks. Cluster heads apply a weighted criteria matrix to perform an inner‐cluster routing for transmitting data packets to sinks. Simulation results demonstrate that the proposed protocol surpasses the existing methods in terms of the number of alive nodes, network lifetime, average time to recover, dead time of first node, and dead time of last node.     

Stochastic support vector regression with probabilistic constraints

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, we introduce a novel model of SVR in which any training samples containing inputs and outputs are considered the random variables with known or unknown distribution functions. Constraints occurrence have a probability density function which helps to obtain maximum margin and achieve robustness. The optimal hyperplane regression can be obtained by solving a quadratic optimization problem. The proposed method is illustrated by several experiments including artificial data sets and real-world benchmark data sets.