R. Bettocchi

Set Up of an Experimental Facility for the Investigation of Wet Compression on a Multistage Compressor

At present, inlet fogging and wet compression are two of the most widely used approaches to enhance gas turbine performance, especially during hot seasons. However, potentially negative effects of these practices on long-term operational integrity of gas turbines should be evaluated carefully; in particular, wet compression may lead to the erosion of first compressor stages, due to the impact of water droplets within the flow at compressor intake. This issue is still controversial in technical literature, since only limited historical field operating data and information are available. Therefore, a test facility was specifically set up in the laboratories of the University of Ferrara, to evaluate the effects of wet compression on a small-size compressor. This paper presents the experimental facility developed for wet compression investigation and some preliminary results.Copyright

Set Up of a Robust Neural Network for Gas Turbine Simulation

In this paper, Neural Network (NN) models for the real-time simulation of gas turbines are studied and developed. The analyses carried out are aimed at the selection of the most appropriate NN structure for gas turbine simulation, in terms of both computational time of the NN training phase and accuracy and robustness with respect to measurement uncertainty. In particular, feed-forward NNs, with a single hidden layer and different numbers of neurons, trained by using a back-propagation learning algorithm are considered and tested. Finally, a general procedure for the validation of computational codes is adapted and applied to the validation of the developed NN models.© 2004 ASME

Assessment of the Performance and of the Profitability of CHP Energy Systems Fed by Vegetable Oils

In this paper, energy and economic analyses of vegetable oil fed energy systems are presented. The paper focuses on the process from oil to energy, while the economic costs of the transformation process of the biomass from field to oil is assumed embodied in the cost of the oils. Five different oils are considered (sunflower, rapeseed, soybean, palm and waste fried oil) as fuels for cogenerative Internal Combustion Engines, also running in combined cycle configuration. In particular, the considered combined cycle is composed of Internal Combustion Engines and Organic Rankine Cycle modules. Energy analyses allow the evaluation of the installed power, of the produced energies, and of the primary energy saving index for different yearly oil mass values. The results of the economic analyses as a function of yearly oil mass are also presented. The cost sources are highlighted in order to point out the major contributors. Moreover, analyses of the limit value of incentive and oil price, in order to guarantee plant profitability, are carried out.© 2009 ASME

Artificial Intelligence for the Diagnostics of Gas Turbines: Part I — Neural Network Approach

In the paper, Neural Network (NN) models for gas turbine diagnostics are studied and developed. The analyses carried out are aimed at the selection of the most appropriate NN structure for gas turbine diagnostics, in terms of computational time of the NN training phase, accuracy and robustness with respect to measurement uncertainty. In particular, feed-forward NNs with a single hidden layer trained by using a back-propagation learning algorithm are considered and tested. Moreover, Multi-Input/Multi-Output NN architectures (i.e. NNs calculating all the system outputs) are compared to Multi-Input/Single-Output NNs, each of them calculating a single output of the system. The results obtained show that NNs are robust with respect to measurement uncertainty, if a sufficient number of training patterns are used. Moreover, Multi-Input/Multi-Output NNs trained with data corrupted with measurement errors seem to be the best compromise between the computational time required for NN training phase and the NN accuracy in performing gas turbine diagnostics.Copyright

A System for Health State Determination of Natural Gas Compression Gas Turbines

This paper illustrates the policy and objectives in compression system maintenance and describes a system for the health state determination of natural gas compression gas turbines based on “Gas Path Analysis”. Some results of the application of the diagnostic system to gas turbines working in a natural gas compression plant are presented.Copyright

Evaluation of the Performance of a Sirocco Fan Driven by a Diesel Engine in Mist Sprayer Applications

The coupling of a sirocco fan, used to supply air to a mist sprayer, and a Diesel engine is studied in order to enhance the performance of the integrated system. In this case, the main problem for the correct design of the fan arises from the fact that it is not possible to define a priori the operating point. In fact, the rotational speed is not fixed as in the case of an electric motor driven fan, but is determined as an equilibrium of the power supplied by the engine and the power absorbed by the fan to recover the pressure drops of the mist sprayer system. In this paper, the experimental campaign performed to characterize the existent fans is presented. Moreover, the sprayer duct is characterized by using literature correlations and by performing numerical simulations. Then, the collected data are elaborated in order to scale the fans in order to enhance the performance of the system.Copyright

Energetic and Economic Analyses of Integrated Biogas-Fed Energy Systems

The process which includes production, collection, carriage and transformation of biomass into renewable fuels and then into energy (both electrical and thermal) involves a large number of decisions to select the most efficient plant layout. In order to identify the optimal solutions, models which simulate the whole process represent a useful and practical tool. In this paper, the energetic and economic analysis of the entire process from biomass to energy production is presented. Among the different transformation processes, the thermophilic batch anaerobic digestion is considered in this paper. A sensitivity analysis on system profitability is carried out with respect to the mass of biomass, number of batch digesters and retention time of the biomass inside each digester. Moreover, two different types of biomass (ensiled corn and organic fraction of municipal solid wastes) and two different energy systems (Micro Gas Turbine and Internal Combustion Engine) are considered.© 2008 ASME

Artificial Intelligence for the Diagnostics of Gas Turbines: Part II — Neuro-Fuzzy Approach

In the paper, Neuro-Fuzzy Systems (NFSs) for gas turbine diagnostics are studied and developed. The same procedure used previously for the set up of Neural Network (NN) models was used. In particular, the same database of patterns was used for both training and testing the NFSs. This database was obtained by running a Cycle Program, calibrated on a 255 MW single shaft gas turbine working in the ENEL combined cycle power plant of La Spezia (Italy). The database contains the variations of the Health Indices (which are the characteristic parameters that are indices of gas turbine health state, such as efficiencies and characteristic flow passage areas of compressor and turbine) and the corresponding variations of the measured quantities with respect to the values in new and clean conditions. The analyses carried out are aimed at the selection of the most appropriate NFS structure for gas turbine diagnostics, in terms of computational time of the NFS training phase, accuracy and robustness towards measurement uncertainty during simulations. In particular, Adaptive Neuro-Fuzzy Inference System (ANFIS) architectures were considered and tested, and their performance was compared to that obtainable by using the NN models. An analysis was also performed in order to identify the most significant ANFIS inputs. The results obtained show that ANFISs are robust with respect to measurement uncertainty, and, in all the cases analyzed, the performance (in terms of accuracy during simulations and time spent for the training phase) proved to be better than that obtainable by MIMO and MISO Neural Networks trained and tested on the same data.Copyright

A Multi-Stage Compressor Test Facility: Uncertainty Analysis and Preliminary Test Results

A multi-stage compressor test-facility, fully instrumented with its dedicated data acquisition and processing system, has been developed to conduct experimental research work at the University of Ferrara. This paper provides a systematic description of the uncertainty analysis procedures required for compressor testing, including preliminary performance test results, in addition to a brief description of the test facility and its capabilities.Copyright

A PROGRAM FOR THE EVALUATION OF POLLUTANT EMISSIONS IN COMBINED CYCLE POWER PLANTS WITH SUPPLEMENTARY FIRING

In this paper, a one-dimensional program for evaluating pollutant emissions in combined cycle power plant with supplementary firing is presented. The program uses Chemical Reactors analysis based on a Perfectly Stirred Reactor approach in conjunction with an emission model that simulates a detailed chemical kinetic scheme for combustion process modelling. The program allows the evaluation of the main pollutant emissions deriving from natural gas and oil combustion. In order to simulate combustion systems that can be found in a fired combined cycle power plant, the developed program presents some extended features with respect to programs developed for gas turbine combustors only. In order to reproduce a wide typology of combustors, the combustor geometry is represented using two characteristic dimensions (hydraulic diameter and length) and the considered domain is divided into reactors in series (along the axial direction) and in parallel (along the radial direction). The temperature in each reactor is determined taking into account both the convective and the radiative heat transfer between hot gases and walls. The program has been applied to two cases. In the first the numerical predictions have been compared with available experimental data relative to two gas turbine combustors. In the second case the program has been instead applied to a cylindrical test burner designed in accordance with EN 267 European Standard. The obtained results are acceptable from an engineering point of view and have been considered sufficiently accurate for this preliminary set-up phase of the model. NOMENCLATURE