ACTIVE VIBRATION SUPPRESSION VIA LINEARIZING HYSTERESIS OF PIEZOCERAMIC ACTUATORS

A novel active vibration control technique on the basis of linearized piezoelectric actuators is presented.An experimental apparatus consisting of a cantilever beam to which are attached strain patches and piezocoramic actuators to be used for active vibration suppression is described.A dy- namical model of the cantilever beam using Lagrange's equation and two coordinate systems are presented.Based on the Lyapunov's direct method,an active vibration controller with hysteresis compensation is designed.The controller is designed so that it guarantees the global stability of the overall system.The controller developed is assessed experimentally.     

Synthesis and characterization of new proton exchange membrane deriving from sulfonated polyether sulfone using ionic crosslinking for electrodialysis applications

In this research work, the synthesis and characterization of new ion exchange membranes made from sulfonated polyether sulfone (S PES) crosslinked by aminated PES (NH2 PES) crosslinking reagent have been investigated for electrodialysis (ED) applications. Sulfonated and aminated PES have similar chemical structures that allow a good compatibility, the only difference between them is their functional groups. This membrane (called HNH2) has been obtained by reaction between S PES with 1.3 SO₃H groups per monomer unit and the calculated equivalent amount of NH2 PES. Three HNH2 membranes have been fabricated with different degrees of sulfonation. The HNH2 membranes properties have been evaluated using different characterization analysis. The results have shown that HNH2 membranes appear to be very promising candidates for electrochemical applications.     

ECONOMIC OPTIMIZATION OF EOR PROCESSES USING KNOWLEDGE-BASED SYSTEM: CASE STUDIES

The main challenge of Enhanced Oil Recovery (EOR) processes at the prevailing low oil prices is to reduce the cost. An optimization methodology, combined with an economic model, is implemented into an expert system for optimizing the net present value of full field development with an EOR process. The approach is automated and combines an economic package and existing numerical reservoir simulators to optimize the design of a selected EOR process using sensitivity analysis. The EOR expert system includes three stages of consultations: (1) select an appropriate EOR process on the basis of the reservoir characteristics, (2) prepare appropriate input data sets to design the selected EOR process using existing numerical simulators, and (3) apply the discounted-cash-flow methods to the optimization of the selected EOR process to find out under what conditions at current oil prices this EOR process might be profitable. The project profitability measures were used as the decision-making variables in an iterative approach to optimize the design of the EOR process. The economic analysis is based on the estimated recovery, residual oil in-place, oil price, and operating costs. Two case studies are presented for two reservoirs that have already been produced to their economic limits and are potential candidates for surfactant/polymer flooding, and carbon-dioxide flooding, respectively, or otherwise subject to abandonment. The effect of several design parameters on the project profitability of these EOR processes was investigated.     

Constructal design of a PCM cylindrical heat sink with three-branched,two-stages dendritic tubes

Amputees who use prosthetic limbs suffer from the problem of high contact temperature between the socket of the prosthetic limb and the amputated part and lack of evaporation of sweat. These conditions lead to discomfort and failure to perform functions properly. In addition, these conditions help generate ulcers and accumulate harmful bacteria in this area. This paper presents a heatsink design to extract heat from the contact area. A cylindrical heat sink is designed for phase-changing materials with three branched tubes in two stages. The current heat sink is used to cool the contact area between the amputated part and the socket in the lower prostheses. Three distributions of pipe branches are proposed. The distribution and pipe lengths were obtained using a constructal design method. In the constructal design, the lengths of the branched tubes were the degrees of freedom, the objective function was the minimization of the inlet temperature to the heat sink, and the constraint was the volume of the cylindrical heat sink. The metabolic heat transfer during exercise was estimated and its value was used to calculate the size of the cylindrical heatsink and the selection of the phase change material by testing three of them: water, tridecane, and dodecane. It was found that water gives the highest latent heat of melting and the lowest volume in addition to its availability. On the other hand, two cooling fluids were tested: water and air. It was found that water as a cooling fluid gave the lowest flow and the largest heat capacity. Constructal theory was used to design a cylindrical heat sink using branched tubes for the coolant in two steps: the first with three branches, and the second with nine branches. The degree of freedom for constructal theory was the length of the branches through the choice of their end locations. It was found that the branches of the highest length led to a reduction in temperature from 40°C to 15.48°C compared with the single tube, which reduced the temperature to 23.87°C. All tests recorded a pressure drop within the acceptable range of 3.1–5.43 Pa for the branches examined. The research demonstrated that using constructal theory achieved the best thermal dissipation within a restricted volume.     

A hybrid ontology-based semantic and machine learning model for the prediction of spring breakup

River ice breakups carry the potential for high flows and flooding and are of great interest to accurately predict. A challenge in forecasting these events is the management of the massive amounts of data associated with an ice season. This study couples ontological and machine learning models in a new hybrid modeling framework to predict spring breakup on a national scale. The Ice Season Ontology sorts the data and allows for a user-friendly means of analyzing any ice season, providing insight on which variables are most and least central. With this, a refined variable selection is able to be made for machine learning models. The most successful developed model, a random forest, produced highly accurate forecasts when applied to a national scale case study, with a mean absolute error of 10.85 days and an R² of .884. This new modeling framework provides a means for decision-making support for river bound communities and a new methodology for modeling applications in other fields.     

Production of cellulose nanofibers from Alfa grass and application as reinforcement for polyvinyl alcohol

The work reported demonstrates an simple method of extracting cellulose nanofibers (CNF) from cellulose microfibers (CMF) obtained from the plant Stipatenacissima. Here, a method for the production of CNF from CMF extracted from Alfa grass by exfoliation in polyvinyl alcohol (PVA) solution, is demonstrated. The CMF were produced in powder form and exfoliated in PVA aqueous solution to produce composites with 2, 4, 5 and 10?wt-% of CNF. Scanning Electron Microscopy demonstrated exfoliation of CMF, dispersion of the CNF and wetting by the polymer. The composites were characterised by thermogravimetry, differential scanning calorimetry, X-ray diffraction and tensile testing. The addition of CNF to PVA reduced the crystallinity degree of PVA. The large increase of the Young’s modulus from 38 to 113% (relative to pure PVA) for composites with 2 to 10?wt-% of CNF incorporation is consistent with the extensive exfoliation of CMF into CNF and its excellent interface with PVA.     

The effect of thermal treatment on the properties of expanded polystyrene

Expanded polystyrene (EPS) is a commonly used polymer in the packaging industry and for the thermal insulation of buildings. It has poor mechanical properties, which limit its application in some areas. A heat treatment was carried out on a sample of EPS, in order to improve its mechanical properties. The treatment consists of operations that combine the heating and cooling of the material. It is executed to improve the characteristics of the treated polymer and make it more favorable for use in new applications. In the case of EPS, this process changes the behavior of the polymer in a beneficial manner and maximizes its density and hardness. Indeed, the treated version shows interesting mechanical, tribological, and hygroscopic properties. This improvement was obtained mainly due to the morphological modification of the structure of EPS. Indeed, heat treatment leads to the creation of a polystyrene crust, which covers every EPS bead. This crust protects the cell structure of each bead against stretching and supports most of the load applied to the treated version of EPS. Thus, the treated EPS can be used not only for packaging and thermal insulation but also for more structural applications.     

Identification of coal seams suitability for carbon dioxide sequestration with enhanced coalbed methane recovery: a case study in South Sumatera Basin,Indonesia

Clean Technologies and Environmental Policy - Sequestering carbon dioxide (CO2) with enhanced coalbed methane recovery (ECBM) is a promising clean coal technology in Indonesia, which can reduce CO2...     

Study and improvement in the radio communication quality for rotating electrical machine

Electrical Engineering - The wireless communication for rotating electrical machines is beneficial for diagnosis purposes as well as real-time monitoring. The electromagnetic waves propagation...     

Optimal Systematic Determination of Models' Base for Multimodel Representation: Real Time Application

The multimodel approach is a powerful and practical tool to deal with analysis, modeling, observation, emulation and control of complex systems. In the modeling framework, we propose in this paper a new method for optimal systematic determination of models base for multimodel representation. This method is based on the classification of data set picked out of the considered system. The obtained cluster centers are exploited to provide the weighting functions and to deduce the corresponding dispersions and their models base. A simulation example and an experimental validation on a semi-batch reactor are presented to evaluate the effectiveness of the proposed method.