George Arampatzis

A GIS-based decision support system for planning urban transportation policies

Abstract A decision support system (DSS) integrated in a geographical information system (GIS) for the analysis and evaluation of different transport policies is presented. The objective of the tool is to assist transport administrators enhance the efficiency of the transportation supply while improving environmental and energy indicators. The DDS works on three levels. The first performs the transport network analysis, the second assesses the energy consumption and pollutant emissions and the third evaluates the several policies selected. Road traffic is simulated using a deterministic, multi-modal traffic assignment model with capacity constraints. The model allows the estimation of traffic flow patterns within each link of the road network starting from the knowledge of the network characteristics and traffic demand. Energy consumption and pollutant emission calculations are based on the methodology developed by the CORINAIR working group. The evaluation of each policy scenario is based on a number of traffic, environmental and energy indicators. A multi-criteria analysis, where decision is based upon judging over appropriate weighted criteria, is adopted. Models are integrated in a GIS environment, which serves as the repository of the data as well as the user interface of the tool. The use of the tool is demonstrated through characteristic case studies on the Greater Athens Area in Greece. Two policy measures, one concerning the extension of the region where half of the private cars are prohibited from entering to the Municipality of Athens and the other the reduction of parking places in the same region by 50% are evaluated.

Water supply modeling towards sustainable environmental management in small islands: the case of Paros, Greece

Abstract The present approach has a two-fold emphasis. On one hand, water supply options are modeled and the optimal combination is presented through the identification of the least cost water supply scheme. On the other hand the results may be used towards the delineation of sustainable environmental policy options, particularly in the vulnerable system of small islands. Hence an optimization model has been developed that minimizes the Net Present Value (NPV) of water supply projected costs for the period 2002–2030 for Paros Island, Greece. The non-linear generalized reduced gradient method is used, taking the capacity of water supply options as the decision variable. The model incorporates the operation of groundwater wells and boreholes, surface storage reservoirs, conventional and wind-powered desalination and water hauling by ships. Finally, it estimates the monthly water production as well as the water supply costs. The identified solution involves the combined use of all water supply options and may provide the optimal contribution of each one of the supply sources, on a monthly time step. The results indicate that conventional water supply topped by versatile desalination schemes used for the particularly demanding water consumption peaks may be the focal area of responses for the island of Paros, and by extension for other areas around the world facing similar problems.

Using hybrid neural networks in scaling up an FCC model from a pilot plant to an industrial unit

The scaling up of a pilot plant fluid catalytic cracking (FCC) model to an industrial unit with use of artificial neural networks is presented in this paper. FCC is one of the most important oil refinery processes. Due to its complexity the modeling of the FCC poses great challenge. The pilot plant model is capable of predicting the weight percent of conversion and coke yield of an FCC unit. This work is focused in determining the optimum hybrid approach, in order to improve the accuracy of the pilot plant model. Industrial data from a Greek petroleum refinery were used to develop and validate the models. The hybrid models developed are compared with the pilot plant model and a pure neural network model. The results show that the hybrid approach is able to increase the accuracy of prediction especially with data that is out of the model range. Furthermore, the hybrid models are easier to interpret and analyze.

Enhancement of the momentum interpolation method on non-staggered grids

A novel interpretation of the momentum interpolation method (MIM) is presented in this paper. A revised method using quadratic interpolating polynomials for the calculation of the cell-face velocities is proposed. The performance of the proposed method (referred to as QMIM) is examined and its application to the well-known lid-driven flow in a square enclosure problem is tested. The computed results are compared with standard reported benchmark solutions for a wide range of flow conditions. The numerical experiments show clearly the superiority of the new approach over the original MIM, in terms of numerical accuracy, rate of convergence towards the grid-independent solution, and computational efficiency

Modelling of an Industrial Fluid Catalytic Cracking Unit Using Neural Networks

An artificial neural network (ANN) model for determining the steady-state behaviour of an industrial Fluid Catalytic Cracking (FCC) unit is presented in this paper. Industrial data from a Greek petroleum refinery were used to develop, train and check the model. FCC is one of the most important oil refinery processes. Due to its complexity the modelling of the FCC poses a great challenge. The proposed model is capable of predicting the volume percent of conversion based on six input variables. This work is focused on determining the optimum architecture of the ANN, in order to gain good generalization properties. The results show that the ANN is able to accurately predict the measured data. The prediction errors in both training and validation data sets are almost the same, indicating the capabilities of the model to accurately generalize when presented with unseen data. The neural model developed is also compared to an existing non-linear statistical model. The comparison shows that the neural model is superior to the statistical model.

A Computer-Aided Tool for the Simulation and Optimization of the Combined HDS–FCC Processes

A computer-aided tool for the simulation, optimization and analysis of the combined operation of the hydrodesulphurization (HDS) and fluid catalytic cracking (FCC) processes in an oil refinery is presented. The optimization of these processes is an important yet difficult engineering task, because of the complexity in the integration of the two units, the large number of interacting variables, the product quality specifications and the financial benefits associated. The proposed tool is developed in a user-friendly Visual Basic environment and operates in two different modes: the modelling-prediction mode and the optimization-sensitivity analysis mode. The modelling of the processes is based on short form’ models, which were created following statistical and neural network approaches. This kind of model usually has short computing time requirements, which is critical for the optimization mode. The optimization algorithm is based on a financial objective function with a flexible form, which gives the user the option to explore a variety of scenarios. Industrial runs have verified the modelling accuracy of the tool. The optimization scenarios examined include the contemporary needs of modern refineries for LPG and gasoline maximization, subject to strict quality specifications. The demonstration of this tool aims to give an insight into the system dependencies and add knowledge on the possibility of a more profitable operation of such a complex process.

Quality characteristics and hydrogeochemistry of irrigation waters from three major olive groves in Greece

AbstractSurface and groundwater samples were collected from three key olive grove regions in Greece in order to assess their overall quality and outline major hydrogeochemical characteristics. The three study areas were selected for their significance to the national olive production as well as for their diverse physiographic characteristics and imposed cultivation practices. Results suggest that quality status in general is acceptable with few exceptions; however, issues related with salinization were identified which in turn could potentially lead to environmental degradation. Hydrogeochemical characteristics are affected by geogenic (natural) factors and anthropogenic influences to some extent. Results were confirmed by PoS index which classified samples according to their quality status. Overall, the controlling factors appear to be the geological setup, the hydrogeological regime, as well as the irrational cultivation practices and groundwater overexploitation. Environmental sustainability in the thr...

Improving the eco-efficiency of an agricultural water use system

AbstractDuring the last two decades, the concept of eco-efficiency has been recognized as a suitable measure of progress towards a greener and more sustainable economy. The prefix “eco-” refers to both economic and ecological (environmental) performance. The need for improving eco-efficiency leads to the challenge of identifying the most promising alternative solutions which improve both the economic and the environmental performance of a given system (“eco-innovations”). Therefore, it becomes critical to develop eco-efficiency metrics for measuring environmental and economic performance of a system. The current paper presents a methodological framework that attempts to explore the use of eco-efficiency indicators in meso-level water use systems and through them to assess the impact of innovative technologies in such systems. The assessment of the environmental performance follows a life cycle-oriented approach using the midpoint impact categories while the economic performance is measured using the total...

Water scarcity and inputs of nutrients from irrigation in olive groves of Crete Island, Greece

Abstract Water availability is an important factor for irrigated agriculture in the Mediterranean countries, because it affects significantly crop production. Surface soil samples were collected in Merambelo area located in Eastern Crete and analyzed. High values for exchangeable potassium and magnesium values were recorded and can be attributed to intensive fertilization and soil heredity factors. Groundwater quality based on two sampling campaigns performed during two irrigation periods. Three different scenarios were taken into account regarding the height of water application by means of irrigation. The contribution and the effects of nutrients and micronutrients from irrigation water to the soil was calculated, on the basis of the mean determined concentrations and the volume of applied irrigation. Significant variation was recorded in most soil properties, and these differences may be attributed to different mobility of nutrients, erosion factors, fertilization practices, and hydraulic soil properties.

Data for moisture measurements during vertical absorption in building porous materials such as brick and limestone

This article contains the datasets obtained from experiments in laboratory related to moisture propagation in building porous materials. The datasets contain moisture measurements and corresponding time measurements during vertical infiltration experiment in brick and limestone samples. Moisture measurements were carried out using a γ-ray device and water volume absorption was recorded by a computer controlled digital scale.