Density measurements of compressed dipropyl, dibutul, bis (2-ethylhexyl) adipates from (293 to 373K) at pressures up to about 68MPa

The article reports density measurements of dipropyl (DPA), dibutyl (DBA) and bis(2-ethylhexyl) (DEHA) adipates, using a vibrating U-tube densimeter, model DMA HP, from Anton Paar GmbH. The measurements were performed in the temperature range (293 to 373) K and at pressures up to about 68 MPa, except for DPA for which the upper limits were 363 K and 65 MPa, respectively. The density data for each liquid was correlated with the temperature and pressure using a modified Tait equation. The expanded uncertainty of the present density results is estimated as 0.2% at a 95% confidence level. No literature density data at pressures higher than 0.1 MPa could be found. DEHA literature data at atmospheric pressure agree with the correlation of the present measurements, in the corresponding temperature range, within +/- 0.11%. The isothermal compressibility and the isobaric thermal expansion were calculated by differentiation of the modified Tait correlation equation. These two parameters were also calculated for dimethyl adipate (DMA), from density data reported in a previous work. The uncertainties of isothermal compressibility and the isobaric thermal expansion are estimated to be less than +/- 1.7% and +/- 1.1%, respectively, at a 95% confidence level. Literature data of isothermal compressibility and isobaric thermal expansivity for DMA have an agreement within +/- 1% and +/- 2.4%, respectively, with results calculated in this work. (C) 2014 Elsevier B.V. All rights reserved.

Thermal Residual Stresses in Functionally Graded Structures: a Didactic Case Study

Conferência: 2nd Experiment at International Conference - 18-20 September 2013

Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Sistemas de arrefecimento de instalações frigoríficas utilizando três agentes frigoríficos

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Renewable power forecast to scheduling of thermal units

In this work is discussed the importance of the renewable production forecast in an island environment. A probabilistic forecast based on kernel density estimators is proposed. The aggregation of these forecasts, allows the determination of thermal generation amount needed to schedule and operating a power grid of an island with high penetration of renewable generation. A case study based on electric system of S. Miguel Island is presented. The results show that the forecast techniques are an imperative tool help the grid management.

Estágio curricular na empresa Consulfrio

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.

Reabilitação térmica e acústica de edifícios antigos

Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Monitoring the ex-vivo expansion of human mesenchymal stem/stromal cells in xeno-free microcarrier-based reactor systems by MIR spectroscopy

Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.

Pontes integrais: estado da arte

Dissertação para obtenção do grau de mestre em Engenharia Civil