Efficiency of integrated electrooxidation and anaerobic digestion of waste activated sludge.

BACKGROUND: Most of the organic content of waste activated sludge (WAS) comprises microbial cells hard to degrade, which must be pre-treated for energy recovery by anaerobic digestion (AD). Electrooxidation pre-treatment (EOP) with boron-doped diamond (BDD) electrode have been considered a promising novel technology that increase hydrolysis rate, by the disintegrating cell walls from WAS. Although electrochemical oxidation could efficiently solubilize organic substances of macromolecules, limited reports are available on EOP of WAS for improving AD. In this endeavour, the mathematical optimization study and the energy analysis of the effects of initial total solids concentrations [TS] of WAS and current density (CD) during EOP on the methane production and removal of chemical oxygen demand (COD) and volatile solids (VS) were investigated. Because limited reports are available on EOP of WAS for improving biogas production, it is not well understood; however, it has started to attract interest of scientists and engineers. RESULTS: In the present work, the energy recovery as biogas and WAS conversion were comprehensively affected by CD and [TS], in an integrated EOP and AD system. When working with WAS at 3% of [TS] pre-treated at current density of 24.1 mA/cm2, the highest COD and VS removal were achieved, making it possible to obtain the maximum methane (CH4) production of 305 N-L/kg VS and a positive energy balance of 1.67 kWh/kg VS. Therefore, the current densities used in BDD electrode are adequate to produce the strong oxidant (hydroxyl radical, ·OH) on the electrode surface, allow the oxidation of organic compounds that favours the solubilization of particulate matter and VS from WAS. CONCLUSIONS: The improvement of VS removal and COD solubilization were due to the effects of pre-treatments, which help to break down the microbial cells for faster subsequent degradation; this allows a decomposition reaction that leads to biodegrade more compounds during AD. The balance was positive, suggesting that even without any optimization the energy used as electricity could be recovered from the increased methane production. It is worth noting that this kind of analysis have not been sufficiently studied so far. It is therefore important to understand how operational parameters can influence the pre-treatment and AD performances. The current study highlights that the mathematical optimization and energy analysis can make the whole process more convenient and feasible.

A comparative study of the energy, exergetic and thermo-economic performance of a novelty combined Brayton S-CO2-ORC configurations as bottoming cycles.

This paper presents a comparative study on the energy, exergetic and thermo-economic performance of a novelty thermal power system integrated by a supercritical CO2 Brayton cycle, and a recuperative organic Rankine cycle (RORC) or a simple organic Rankine cycle (SORC). A thermodynamic model was developed applying the mass, energy and exergy balances to all the equipment, allowing to calculate the exergy destruction in the components. In addition, a sensitivity analysis allowed studying the effect of the primary turbine inlet temperature (TIT, PHIGH, rP and TC) on the net power generated, the thermal and exergy efficiency, and some thermo-economic indicators such as the payback period (PBP), the specific investment cost (SIC), and the levelized cost of energy (LCOE), when cyclohexane, acetone and toluene are used as working fluids in the bottoming organic Rankine cycle. The parametric study results show that cyclohexane is the organic fluid that presents the best thermo-economic performance, and the optimization with the PSO method conclude a 2308.91 USD/kWh in the SIC, 0.22 USD/kWh in the LCOE, and 9.89 year in the PBP for the RORC system. Therefore, to obtain technical and economic viability, and increase the industrial applications of these thermal systems, thermo-economic optimizations must be proposed to obtain lower values of the evaluated performance indicators.

Development of a new educational package based on e-learning to study engineering thermodynamics process: combustion, energy and entropy analysis.

This paper presents a new educational package based on e-learning called TermolabUA integrated by three programs, which are VOLCONTROL focused on the analysis of steady-state flow devices, CarnotCycle aimed to analyze reversible and irreversible processes, and CombustionUA to study combustion processes. The educational package was designed for both, to promote significant learning on some thermodynamic topics in undergraduate students, and to help the student to reach the cognitive competencies of interpreting, arguing and proposing, and interacting with the different graphical user interfaces to solve relevant cases studies. Also, the teaching-learning activity helps them to understand the influence of a specific variable on the energy and entropy behavior of the selected systems, which is traditionally studied manually in a classroom. The results of the t-Student tests showed that the average grades obtained by the students in the problems using the software were higher than the average grade without using the software. The estimate for the average grade difference was 0.56 with a P-value = 3.31E-13 for Problem 1 and 0.631 with a P-value = 3.31E-13 for Problem 2 in the Workshop- VOLCONTROL. Similar results were obtained for the problems reported in the CarnotCycle and CombustionUA Workshop with an estimate for average grade differences and P-values lower than 0.79 and 0.05, respectively. It means that the new software package significantly improved the learning skills of the students.

A comparative energy and exergy optimization of a supercritical-CO2 Brayton cycle and Organic Rankine Cycle combined system using swarm intelligence algorithms.

This article presents a multivariable optimization of the energy and exergetic performance of a power generation system, which is integrated by a supercritical Brayton Cycle using carbon dioxide, and a Simple Organic Rankine Cycle (SORC) using toluene, with reheater ( S - C O 2 R H - S O R C ), and without reheater ( S - C O 2 N R H - S O R C ) using the PSO algorithm. A thermodynamic model of the integrated system was developed from the application of mass, energy and exergy balances to each component, which allowed the calculation of the exergy destroyed a fraction of each equipment, the power generated, the thermal and exergetic efficiency of the system. In addition, through a sensitivity analysis, the effect of the main operational and design variables on thermal efficiency and total exergy destroyed was studied, which were the objective functions selected in the proposed optimization. The results show that the greatest exergy destruction occurs at the thermal source, with a value of 97 kW for the system without Reheater (NRH), but this is reduced by 92.28% for the system with Reheater (RH). In addition, by optimizing the integrated cycle for a particle number of 25, the maximum thermal efficiency of 55.53% (NRH) was achieved, and 56.95% in the RH system. Likewise, for a particle number of 15 and 20 in the PSO algorithm, exergy destruction was minimized to 60.72 kW (NRH) and 112.06 kW (RH), respectively. Comparative analyses of some swarm intelligence optimization algorithms were conducted for the integrated S-CO2-SORC system, evaluating performance indicators, where the PSO optimization algorithm was favorable in the analyses, guaranteeing that it is the ideal algorithm to solve this case study.

Techno-economic analysis of aniline production via amination of phenol.

The purpose of this research is to demonstrate through a techno-economic assessment that aniline can be industrially produced using a profitable and inherently safer process than the ones currently employed. The aniline production process was designed using process simulation software. From this, the mass and energy balances were determined, the equipment sizing was performed and the net present value (NPV) was calculated to be USD 93.5 million. Additionally, a heat integration analysis was carried out in order to improve process profitability, obtaining a new NPV of USD 97.5 million. The economic sensitivity analysis showed that the process could withstand fixed capital investment changes of up to +89%, weighted average cost of capital changes between 16-24% and a decrease in cyclohexylamine demand of up to 44%. The conceptual design is still profitable when aniline price is varied in a range of 1224-1840 $/t and phenol cost in a range of 815-1178 $/t.

Infrared intensity analysis of hydroxyl stretching modes in carboxylic acid dimers by means of the charge-charge flux-dipole flux model.

The Charge-Charge Flux-Dipole Flux (CCFDF) model in terms of multipoles from the quantum theory of atoms in molecules (QTAIM) was used to investigate the variations in infrared intensities of hydroxyl (OH) stretching modes during the dimerization of carboxylic acids. The hydrogen bond formation in these systems results into bathochromic shifts of vibrational frequencies for all the OH stretching modes along with huge infrared intensity increments for some of them. These bands become more intense on dimerization due mainly to changes in the cross-term contribution between charge and charge flux. In addition, interaction energies for the pair of atoms directly involved in individual hydrogen bonds (O…H) are linearly correlated to electron densities at their bond critical points (BCPs). Therefore, the hydrogen bonds between the carbonyl group (CO) of acetic acid and the hydroxyl group of halogenated monomers show the largest electron density values at their BCPs. The formation of these intermolecular interactions is also accompanied by ionic character enhancements of OH bonds and electron density decrements at their BCPs. We finally noticed that the hydrogen atom belonging to the hydroxyl group loses electronic charge, while the oxygen from the CO end becomes more negatively charged during dimerization. © 2019 Wiley Periodicals, Inc.

Classical-Equivalent Bayesian Portfolio Optimization for Electricity Generation Planning.

There are several electricity generation technologies based on different sources such as wind, biomass, gas, coal, and so on. The consideration of the uncertainties associated with the future costs of such technologies is crucial for planning purposes. In the literature, the allocation of resources in the available technologies has been solved as a mean-variance optimization problem assuming knowledge of the expected values and the covariance matrix of the costs. However, in practice, they are not exactly known parameters. Consequently, the obtained optimal allocations from the mean-variance optimization are not robust to possible estimation errors of such parameters. Additionally, it is usual to have electricity generation technology specialists participating in the planning processes and, obviously, the consideration of useful prior information based on their previous experience is of utmost importance. The Bayesian models consider not only the uncertainty in the parameters, but also the prior information from the specialists. In this paper, we introduce the classical-equivalent Bayesian mean-variance optimization to solve the electricity generation planning problem using both improper and proper prior distributions for the parameters. In order to illustrate our approach, we present an application comparing the classical-equivalent Bayesian with the naive mean-variance optimal portfolios.