Kinetics of Pressure Cycling Extraction of Solute from Leaves of Mate (Ilex paraguariensis) Dispersed in Water

A set of seven extraction experiments was performed to investigate the influence of pressure cycles on the kinetics of solute removal from leaves of mate dispersed in water. The mass ratio of liquid to dry solid (40), the temperature (32°C), and time of extraction (3600?s) were not varied. Five extraction runs were under cyclic pressurization (1?cycle?=?300?s at 91.4?kPa?+?300?s at 182.8?kPa) and stirring speeds (S) of 0, 150, 500, 1500, and 2000?rpm, while the two other ones were at constant pressure (182.8?kPa) and S close to 1500 and 2000?rpm. Based on seven pairs of parameters of a reliable second-order kinetic model (R²?≥?0.967), cyclic pressurization had no effect on equilibrium and kinetics of extraction (p?>?0.05) when the role of convection on solute transfer was negligible (S?≥?500?rpm). In the stirring speed range from 500 to 2000?rpm, the operation was controlled by diffusion (Bi >?1.7?×?10³), so a transient two-dimensional diffusion model was able to describe correctly the changes of solute concentration with time. Below 500?rpm, solute transfer was governed by a combination of diffusion and convection with the external resistance to mass transfer as a function of S (16?≤?Bi?≤?28).     

A functional test platform for the Community Land Model

The realistic representation of key biogeophysical and biogeochemical functions is the fundamental of process-based ecosystem models. A functional test platform is designed to create direct linkages between site measurements and the process-based ecosystem model within the Community Earth System Models (CESM). The platform consists of three major parts: 1) interactive user interfaces, 2) functional test models and 3) observational datasets. It provides much needed integration interfaces for both field experimentalists and ecosystem modelers to improve the model's representation of ecosystem processes within the CESM framework without large software overhead.     

Decentralized and centralized model predictive control to reduce the bullwhip effect in supply chain management

Mitigating the bullwhip effect is one of crucial problems in supply chain management. In this research, centralized and decentralized model predictive control strategies are applied to control inventory positions and to reduce the bullwhip effect in a benchmark four-echelon supply chain. The supply chain under consideration is described by discrete dynamic models characterized by balance equations on product and information flows with an ordering policy serving as the control schemes. In the decentralized control strategy, a MPC-EPSAC (Extended Prediction Self-Adaptive Control) approach is used to predict the changes in the inventory position levels. A closed-form solution of an optimal ordering decision for each echelon is obtained by locally minimizing a cost function, which consists of the errors between predicted inventory position levels and their setpoints, and a weighting function that penalizes orders. The single model predictive controller used in centralized control strategy optimizes globally and finds an optimal ordering policy for each echelon. The controller relies on a linear discrete-time state-space model to predict system outputs. But the predictions are approached by either of two multi-step predictors depending on whether the states of the controller model are directly observed or not. The objective function takes a quadratic form and thus the resulting optimization problem can be solved via standard quadratic programming method. The comparisons on performances of the two MPC strategies are illustrated with a numerical example.     

Robust guaranteed cost ILC with dynamic feedforward and disturbance compensation for accurate PMSM position control

This contribution presents a robust ILC control design based on guaranteed costs. By combining this ILC design with dynamic feedforward control and an observer-based disturbance compensation, the initial tracking errors in an early learning stage can be reduced. The benefits of the proposed design approach are pointed out at the example of a robust position control of a Permanent Magnet Synchronous Motor (PMSM), which is subject to uncertain model parameters. The paper is concluded with convincing experimental results from a dedicated test rig. Moreover, a comparison with a classical observer-based tracking control is provided.     

Reliable fault-tolerant model predictive control of drinking water transport networks

This paper proposes a reliable fault-tolerant model predictive control applied to drinking water transport networks. After a fault has occurred, the predictive controller should be redesigned to cope with the fault effect. Before starting to apply the fault-tolerant control strategy, it should be evaluated whether the predictive controller will be able to continue operating after the fault appearance. This is done by means of a structural analysis to determine loss of controllability after the fault complemented with feasibility analysis of the optimization problem related to the predictive controller design, so as to consider the fault effect in actuator constraints. Moreover, by evaluating the admissibility of the different actuator-fault configurations, critical actuators regarding fault tolerance can be identified considering structural, feasibility, performance and reliability analyses. On the other hand, the proposed approach allows a degradation analysis of the system to be performed. As a result of these analyses, the predictive controller design can be modified by adapting constraints such that the best achievable performance with some pre-established level of reliability will be achieved. The proposed approach is tested on the Barcelona drinking water transport network.     

Comparison of three control strategies for optimization of spray dryer operation

Spray drying is the preferred process to reduce the water content of many chemicals, pharmaceuticals, and foodstuffs. A significant amount of energy is used in spray drying to remove water and produce a free flowing powder product. In this paper, we present and compare the performance of three controllers for operation of a four-stage spray dryer. The three controllers are a proportional-integral (PI) controller that is used in industrial practice for spray dryer operation, a linear model predictive controller with real-time optimization (MPC with RTO, MPC-RTO), and an economically optimizing nonlinear model predictive controller (E-NMPC). The MPC with RTO is based on the same linear state space model in the MPC and the RTO layer. The E-NMPC consists of a single optimization layer that uses a nonlinear system of ordinary differential equations for its predictions. The PI control strategy has a fixed target that is independent of the disturbances, while the MPC-RTO and the E-NMPC adapt the operating point to the disturbances. The goal of spray dryer operation is to optimize the profit of operation in the presence of feed composition and ambient air humidity variations; i.e. to maximize the production rate, while minimizing the energy consumption, keeping the residual moisture content of the powder below a maximum limit, and avoiding that the powder sticks to the chamber walls. We use an industrially recorded disturbance scenario in order to produce realistic simulations and conclusions. The key performance indicators such as the profit of operation, the product flow rate, the specific energy consumption, the energy efficiency, and the residual moisture content of the produced powder are computed and compared for the three controllers. In this simulation study, we find that the economic performance of the MPC with RTO as well as the E-NMPC is considerably improved compared to the PI control strategy used in industrial practice. The MPC with RTO improves the profit of operation by 8.61%, and the E-NMPC improves the profit of operation by 9.66%. The energy efficiency is improved by 6.21% and 5.51%, respectively.     

Investigations and model validation of a ground-coupled heat pump for the combination with solar collectors

The operation of ground-coupled heat pumps in combination with solar collectors requires comprising knowledge of the heat pump behavior under non-standard conditions. Especially higher temperatures and varying flow rates in comparison to non-solar systems have to be taken into account. Furthermore the dynamic behavior becomes more important.At ISFH, steady-state and dynamic tests of a typical brine/water heat pump have been carried out in order to analyze its behavior under varying operation conditions. It has been shown, that rising source temperatures do only significantly increase the coefficient of performance (COP), if the source temperature is below 10–20 °C, depending on the temperature lift between source and sink. The flow rate, which has been varied both on the source and the sink side, only showed a minor influence on the exergetic efficiency. Additionally a heat pump model for TRNSYS has been validated under non-standard conditions. The results are assessed by means of TRNSYS simulations.     

Framework for sensitivity and uncertainty quantification in the flutter assessment of bridges

The phenomenon of aerodynamic instability caused by wind is usually a major design criterion for long-span cable-supported bridges. If the wind speed exceeds the critical flutter speed of the bridge, this constitutes an Ultimate Limit State. The prediction of the flutter boundary therefore requires accurate and robust models. The state-of-the-art theory concerning determination of the flutter stability limit is presented. Usually bridge decks are bluff and therefore the aeroelastic forces under wind action have to be experimentally evaluated in wind tunnels or numerically computed through Computational Fluid Dynamics (CFD) simulations. The self-excited forces are modelled using aerodynamic derivatives obtained through CFD forced vibration simulations on a section model. The two-degree-of-freedom flutter limit is computed by solving the Eigenvalue problem.A probabilistic flutter analysis utilizing a meta-modelling technique is used to evaluate the effect of parameter uncertainty. A bridge section is numerically modelled in the CFD simulations. Here flutter derivatives are considered as random variables. A methodology for carrying out sensitivity analysis of the flutter phenomenon is developed. The sensitivity with respect to the uncertainty of flutter derivatives and structural parameters is considered by taking into account the probability distribution of the flutter limit. A significant influence on the flutter limit is found by including uncertainties of the flutter derivatives due to different interpretations of scatter in the CFD simulations. The results indicate that the proposed probabilistic flutter analysis provides extended information concerning the accuracy in the prediction of flutter limits.The final aim is to set up a method to estimate the flutter limit with probabilistic input parameters. Such a tool could be useful for bridge engineers at early design stages. This study shows the difficulties in this regard which have to be overcome but also highlights some interesting and promising results.     

Alloying and surface composition of model Pd–Ag films synthesized by electroless deposition

PdAg model films and real composite membranes were prepared by sequential electroless deposition on top of porous stainless steel supports. Their surface properties were investigated by X-ray photoelectron spectroscopy (XPS), Angle resolved XPS and sputtering depth profile. It was shown that the surface of the alloy was strongly enriched in silver after the annealing treatment up to 500 °C on hydrogen stream. A relationship between the Ag 3d_5/2 core-level binding energy shift and the silver surface composition was observed from the XPS data obtained with the model samples. The surface composition of real membranes after both hydrogen permeation and reaction experiments showed silver enrichment, in agreement with the data obtained from the model sample.