Estudo da influência de compostos recalcitrantes na remoção de matéria orgânica biodegradável no tratamento de efluente de refinarias de petróleo

Petroleum Refinery wastewaters (PRW) have hart-to-degrade compounds, such as: phenols, ammonia, cyanides, sulfides, oils and greases and the mono and polynuclear aromatic hydrocarbons: benzene, toluene and xylene (BTX), acenaphthene, nitrobenzene and naphtalene. It is known that the microrganisms activity can be reduced in the presence of certain substances, adversely affecting the biological process of wastewater treatment. This research was instigated due the small number of studies regarding to this specific topic in the avaiable literature. This body of work ims to evaluate the effect of toxic substances on the biodegradability of the organic material found in PRW. Glucose was chosen as the model substrate due to its biodegradable nature. This study was divided into three parts: i) a survey of recalcitants compounds and the removal of phenol by using both biological and photochemical-biological processes; ii) biomass aclimation and iii) evaluation of the inhibitory effect certain compounds have on glucose biodegradation. The phenol degradation experiments were carried out in an activity sludge system and in a photochemical reactor. The results showed the photochemical-biological process to be more effective on phenol degradation, suggesting the superioruty of a combined photochemical-biological treatment when compared with a simple biological process for phenol removal from industry wastewaters. For the acclimation step, was used an activated sludge from industrial wastewaters. A rapid biomass aclimation to a synthetic solution composed of the main inhibitory compouns fpund in a PRW was obtained using the following operation condition: (pH = 7,0; DO ≥ 2,0 mg/L; RS = 20 days e qH = 31,2 and 20,4 hours), The last part was consisted of using respirometry evaluation toxicity effects of selected compounds over oxygen uptake rate to adaptated and non adaptated biomass in the presence of inhibitory compounds. The adaptated sludge showed greater degration capacity, with lower sensibility to toxic effects. The respirometry has proved to be very practical, as the techiniques used were simple and rapid, such as: Chemical Oxygen Demand (COD), Dissolved Oxygen (DO), and Volatile Suspended Solids (VSS). Using the latter it is possible to perform sludge selection to beggingthe process; thus allowing its use for aerobic treatment system`s behacior prediction

Algorítmo evolucionário para a distribuição de produtos de petróleo por redes de polidutos

The distribution of petroleum products through pipeline networks is an important problem that arises in production planning of refineries. It consists in determining what will be done in each production stage given a time horizon, concerning the distribution of products from source nodes to demand nodes, passing through intermediate nodes. Constraints concerning storage limits, delivering time, sources availability, limits on sending or receiving, among others, have to be satisfied. This problem can be viewed as a biobjective problem that aims at minimizing the time needed to for transporting the set of packages through the network and the successive transmission of different products in the same pipe is called fragmentation. This work are developed three algorithms that are applied to this problem: the first algorithm is discrete and is based on Particle Swarm Optimization (PSO), with local search procedures and path-relinking proposed as velocity operators, the second and the third algorithms deal of two versions based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed algorithms are compared to other approaches for the same problem, in terms of the solution quality and computational time spent, so that the efficiency of the developed methods can be evaluated

Distribuição de derivados de petróleo por redes de polidutos: uma abordagem através de algoritmos evolucionários híbridos para um problema triobjetivo

An important problem faced by the oil industry is to distribute multiple oil products through pipelines. Distribution is done in a network composed of refineries (source nodes), storage parks (intermediate nodes), and terminals (demand nodes) interconnected by a set of pipelines transporting oil and derivatives between adjacent areas. Constraints related to storage limits, delivery time, sources availability, sending and receiving limits, among others, must be satisfied. Some researchers deal with this problem under a discrete viewpoint in which the flow in the network is seen as batches sending. Usually, there is no separation device between batches of different products and the losses due to interfaces may be significant. Minimizing delivery time is a typical objective adopted by engineers when scheduling products sending in pipeline networks. However, costs incurred due to losses in interfaces cannot be disregarded. The cost also depends on pumping expenses, which are mostly due to the electricity cost. Since industrial electricity tariff varies over the day, pumping at different time periods have different cost. This work presents an experimental investigation of computational methods designed to deal with the problem of distributing oil derivatives in networks considering three minimization objectives simultaneously: delivery time, losses due to interfaces and electricity cost. The problem is NP-hard and is addressed with hybrid evolutionary algorithms. Hybridizations are mainly focused on Transgenetic Algorithms and classical multi-objective evolutionary algorithm architectures such as MOEA/D, NSGA2 and SPEA2. Three architectures named MOTA/D, NSTA and SPETA are applied to the problem. An experimental study compares the algorithms on thirty test cases. To analyse the results obtained with the algorithms Pareto-compliant quality indicators are used and the significance of the results evaluated with non-parametric statistical tests.