Metaheuristic Algorithm-Based Vibration Response Model for a Gas Microturbine.

Data acquisition and processing are areas of research in fault diagnosis in rotating machinery, where the rotor is a fundamental component that benefits from dynamic analysis. Several intelligent algorithms have been used to optimize investigations of this nature. However, the Jaya algorithm has only been applied in a few instances. In this study, measurements of the amplitude of vibration in the radial direction in a gas microturbine were analyzed using different rotational frequency and temperature levels. A response surface model was generated using a polynomial tuned by the Jaya metaheuristic algorithm applied to the averages of the measurements, and another on the whole sample, to determine the optimal operating conditions and the effects that temperature produces on vibrations. Several tests with different orders of the polynomial were carried out. The fifth-order polynomial performed better in terms of MSE. The response surfaces were presented fitting the measured points. The roots of the MSE, as a percentage, for the 8-point and 80-point fittings were 3.12% and 10.69%, respectively. The best operating conditions were found at low and high rotational frequencies and at a temperature of 300 ∘C. High temperature conditions produced more variability in the measurements and caused the minimum value of the vibration amplitude to change in terms of rotational frequency. Where it is feasible to undertake experiments with minimal variations, the model that uses only the averages can be used. Future work will examine the use of different error functions which cannot be conveniently implemented in a common second-order model. The proposed method does not require in-depth mathematical analysis or high computational capabilities.

Knowledge-Driven Manufacturing Process Innovation: A Case Study on Problem Solving in Micro-Turbine Machining.

Micromachining techniques have been applied widely to many industrial sectors, including aerospace, automotive, and precision instruments. However, due to their high-precision machining requirements, and the knowledge-intensive characteristics of miniaturized parts, complex manufacturing process problems often hinder production. To solve these problems, a systematic scheme for structured micromachining process problem solving and an innovation support system is required. This paper presents a knowledge-based holistic framework that enables process planners to achieve micromachining innovation design. By analyzing innovation design procedures and available knowledge sources, an open multi-source Machining Process Innovation Knowledge (MPIK) acquisition paradigm is presented, including knowledge units and a knowledge network. Further, a MPIK network-driven structured process problem-solving and heuristic innovation design method was explored. Subsequently, a knowledge-driven heuristic design system for machining process innovation was integrated in the Computer-Aided Process Innovation (CAPI) platform. Finally, a case study involving specific process problem-solving and innovation scheme design for micro-turbine machining was studied to validate the proposed approach.

Techno-economic assessment of landfill gas (LFG) to electric energy: Selection of the optimal technology through field-study and model simulation.

Landfill Gas (LFG) is a renewable energy resource. LFG quality and production rate are determined factors for the selection of the optimal technology for electric energy production. Environmental legislation, flue gas emissions, carbon footprint and maturity of technology should also be considered. The most common process for electric energy production from LFG is by Internal Combustion Engines (ICEs), which require approximately 40% minimum methane concentration. Microturbines have been also employed for electric energy production from LFG, requiring minimum methane concentration of approximately 35%. On the other hand, a relatively novel process, Gradual Oxidation (GO), can produce electric energy from LFG at methane concentrations as low as 1.5%. The present study examines the applicability of the above technologies for electric energy production from LFG, from various cells, at the landfill of Heraklion, Crete, Greece, from an economic point of view. The LandGEM (EPA) simulation model has been modified to account for the long them reduction of methane concentration in LFG, and has been adjusted, based on field measurements. The Net Present Values (NPVs) (for 15-years and 25-years from installation) for three distinct scenarios, with total electric energy production capacity of 800 kW, per scenario (using just ICEs, combination of ICE and GO or just microturbines), were calculated. The results indicated that the most profitable scenario (among the ones studied) was the one with the use of two microturbines with capacity 400 kW, each, yielding 15-years and 25-yeasr NPVs of 2.68 and 3.69 M€, respectively, for initial capital investment of 2.24 M€.

Hydrodynamic water tunnel for characterization of hydrokinetic microturbines designs.

ABSTRACT: The enormous inroads made by renewable energy in recent years have been the key to the development of new technologies designed to obtain energy from a range of resources. Hydrokinetic microturbines used to harness kinetic energy from rivers, tidal and marine currents epitomize such developments. As the reservoir is dispensed with, the water footprint normally associated with conventional hydroelectric generation is minimized. The new prototypes being developed require laboratories with water tunnel infrastructures where they can be accurately reproduced under controlled conditions. However, the construction of a water tunnel demands considerable investment, which prevents many research groups from completing their prototype design work. This paper charts the design of a low-cost hydrodynamic water tunnel at the University of Oviedo, indicating the mechanical and electronic elements as well as the software developments that make up the facility. This construction is a part of a research strategy focused on making the study of new hydrokinetic microturbines designs economically feasible. Moreover, it includes a description of a special software application used to perform the characterization of a hydrokinetic microturbine model in the water tunnel and a demonstration of the scope of the facility in the experimental study of a unit with a Darrieus rotor.

Designing the microturbine engine for waste-derived fuels.

Presented paper deals with adaptation procedure of a microturbine (MGT) for exploitation of refuse derived fuels (RDF). RDF often possess significantly different properties than conventional fuels and usually require at least some adaptations of internal combustion systems to obtain full functionality. With the methodology, developed in the paper it is possible to evaluate the extent of required adaptations by performing a thorough analysis of fuel combustion properties in a dedicated experimental rig suitable for testing of wide-variety of waste and biomass derived fuels. In the first part key turbine components are analyzed followed by cause and effect analysis of interaction between different fuel properties and design parameters of the components. The data are then used to build a dedicated test system where two fuels with diametric physical and chemical properties are tested - liquefied biomass waste (LW) and waste tire pyrolysis oil (TPO). The analysis suggests that exploitation of LW requires higher complexity of target MGT system as stable combustion can be achieved only with regenerative thermodynamic cycle, high fuel preheat temperatures and optimized fuel injection nozzle. Contrary, TPO requires less complex MGT design and sufficient operational stability is achieved already with simple cycle MGT and conventional fuel system. The presented approach of testing can significantly reduce the extent and cost of required adaptations of commercial system as pre-selection procedure of suitable MGT is done in developed test system. The obtained data can at the same time serve as an input for fine-tuning the processes for RDF production.