283 resultados para Organic Rankine Cycle (ORC)

em Queensland University of Technology - ePrints Archive


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Optimisation of organic Rankine cycles(ORCs for binary cycle applications could play a major role in determining the competitiveness of low to moderate renewable sources. An important aspect of the optimisation is to maximise the turbine output power for a given resource. This requires careful attention to the turbine design notably through numerical simulations. Challenges in the numerical modelling of radial-inflow turbines using high-density working fluids still need to be addressed in order to improve the turbine design and better optimise ORCs. Thispaper presents preliminary 3D numerical simulations of a high-density radial-inflow ORC turbine in sensible geothermal conditions. Following extensive investigation of the operating conditions and thermodynamic cycle analysis, therefrigerant R143a is chosen as the high-density working fluid. The 1D design of the candidate radial-inflow turbine is presented in details. Furthermore, commercially-available software Ansys-CFX is used to perform preliminary steady-state 3D CFD simulations of the candidate R143a radial-inflow turbine for a number of operating conditions including off-design conditions. The real-gas properties are obtained using the Peng–Robinson equations of state.The thermodynamic ORC cycle is presented. The preliminary design created using dedicated radial-inflow turbine software Concepts-Rital is discussed and the 3D CFD results are presented and compared against the meanline analysis.

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Optimisation of Organic Rankine Cycle (ORCs) for binary-cycle geothermal applications could play a major role in determining the competitiveness of low to moderate temperature geothermal resources. Part of this optimisation process is matching cycles to a given resource such that power output can be maximised. Two major and largely interrelated components of the cycle are the working fluid and the turbine. Both components need careful consideration: the selection of working fluid and appropriate operating conditions as well as optimisation of the turbine design for those conditions will determine the amount of power that can be extracted from a resource. In this paper, we present the rationale for the use of radial-inflow turbines for ORC applications and the preliminary design of several radial-inflow machines based on a number of promising ORC systems that use five different working fluids: R134a, R143a, R236fa, R245fa and n-Pentane. Preliminary meanline analysis lead to the generation of turbine designs for the various cycles with similar efficiencies (77%) but large differences in dimensions (139–289 mm rotor diameter). The highest performing cycle, based on R134a, was found to produce 33% more net power from a 150 °C resource flowing at 10 kg/s than the lowest performing cycle, based on n-Pentane.

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Optimisation of Organic Rankine Cycles (ORCs) for binary-cycle geothermal applications could play a major role in the competitiveness of low to moderate temperature geothermal resources. Part of this optimisation process is matching cycles to a given resource such that power output can be maximised. Two major and largely interrelated components of the cycle are the working fluid and the turbine. Both components need careful consideration. Due to the temperature differences in geothermal resources a one-size-fits-all approach to surface power infrastructure is not appropriate. Furthermore, the traditional use of steam as a working fluid does not seem practical due to the low temperatures of many resources. A variety of organic fluids with low boiling points may be utilised as ORC working fluids in binary power cycle loops. Due to differences in thermodynamic properties, certain fluids are able to extract more heat from a given resource than others over certain temperature and pressure ranges. This enables the tailoring of power cycle infrastructure to best match the geothermal resource through careful selection of the working fluid and turbine design optimisation to yield the optimum overall cycle performance. This paper presents the rationale for the use of radial-inflow turbines for ORC applications and the preliminary design of several radial-inflow turbines based on a selection of promising ORC cycles using five different high-density working fluids: R134a, R143a, R236fa, R245fa and n-Pentane at sub- or trans-critical conditions. Numerous studies published compare a variety of working fluids for various ORC configurations. However, there is little information specifically pertaining to the design and implementation of ORCs using realistic radial turbine designs in terms of pressure ratios, inlet pressure, rotor size and rotational speed. Preliminary 1D analysis leads to the generation of turbine designs for the various cycles with similar efficiencies (77%) but large differences in dimensions (139289 mm rotor diameter). The highest performing cycle (R134a) was found to produce 33% more net power from a 150°C resource flowing at 10 kg/s than the lowest performing cycle (n-Pentane).

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Optimisation is a fundamental step in the turbine design process, especially in the development of non-classical designs of radial-inflow turbines working with high-density fluids in low-temperature Organic Rankine Cycles (ORCs). The present work discusses the simultaneous optimisation of the thermodynamic cycle and the one-dimensional design of radial-inflow turbines. In particular, the work describes the integration between a 1D meanline preliminary design code adapted to real gases and the performance estimation approach for radial-inflow turbines in an established ORC cycle analysis procedure. The optimisation approach is split in two distinct loops; the inner operates on the 1D design based on the parameters received from the outer loop, which optimises the thermodynamic cycle. The method uses parameters including brine flow rate, temperature and working fluid, shifting assumptions such as head and flow coefficients into the optimisation routine. The discussed design and optimisation method is then validated against published benchmark cases. Finally, using the same conditions, the coupled optimisation procedure is extended to the preliminary design of a radial-inflow turbine with R143a as working fluid in realistic geothermal conditions and compared against results from commercially-available software RITAL from Concepts-NREC.

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Optimisation of Organic Rankine Cycles (ORCs) for binary cycle applications could play a major role in determining the competitiveness of low to moderate renewable sources. An important aspect of the optimisation is to maximise the turbine output power for a given resource. This requires careful attention to the turbine design notably through numerical simulations. Challenges in the numerical modelling of radial-inflow turbines using high-density working fluids still need to be addressed in order to improve the turbine design and better optimise ORCs. This paper presents preliminary 3D numerical simulations of a radial-inflow turbine working with high-density fluids in realistic geothermal ORCs. Following extensive investigation of the operating conditions and thermodynamic cycle analysis, the refrigerant R143a is chosen as the high-density working fluid. The 1D design of the candidate radial-inflow turbine is presented in details. Furthermore, commercially-available software Ansys-CFX is used to perform the 3D CFD simulations for a number of operating conditions including off-design conditions. The real-gas properties are obtained using the Peng-Robinson equations of state. The preliminary design created using dedicated radial-inflow turbine software Concepts-Rital is discussed and the 3D CFD results are presented and compared against the meanline analysis.

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The system for high utilization of LNG cold energy is proposed by use of process simulator. The proposed design is a closed loop system, and composed by a Hampson type heat exchanger, turbines, pumps and advanced humid air turbine (AHAT) or Gas turbine combined cycle (GTCC). Its heat sources are Boil-off gas and cooling water for AHAT or GTCC. The higher cold exergy recovery to power can be about 38 to 56% as compared to the existing cold power generation of about 20% with a Rankine cycle of a single component. The advantage of the proposed system is to reduce the number of heat exchangers. Furthermore, the environmental impact is minimized because the proposed design is a closed loop system. A life cycle comparative cost is calculated to demonstrate feasibility of the proposed design. The development of the Hampson type exchangers is expected to meet the key functional requirements and will result in much higher LNG cold exergy recovery and the overall system performance i.e. re-gasification. Additionally, the proposed design is expected to provide flexibility to meet different gas pressure suited for the deregulation of energy system in Japan and higher reliability for an integrated boil-off gas system.

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The relationship between organic matter (OM) lability and temperature sensitivity is disputed, with recent observations suggesting that responses of relatively more resistant OM to increased temperature could be greater than, equivalent to, or less than responses of relatively more labile OM. This lack of clear understanding limits the ability to forecast carbon (C) cycle responses to temperature changes. Here, we derive a novel approach (denoted Q(10-q)) that accounts for changes in OM quality during decomposition and use it to analyze data from three independent sources. Results from new laboratory soil incubations (labile Q(10-q)=2.1 +/- 0.2; more resistant Q(10-q)=3.8 +/- 0.3) and reanalysis of data from other soil incubations reported in the literature (labile Q(10-q)=2.3; more resistant Q(10-q)=3.3) demonstrate that temperature sensitivity of soil OM decomposition increases with decreasing soil OM lability. Analysis of data from a cross-site, field litter bag decomposition study (labile Q(10-q)=3.3 +/- 0.2; resistant Q(10-q)=4.9 +/- 0.2) shows that litter OM follows the same pattern, with greater temperature sensitivity for more resistant litter OM. Furthermore, the initial response of cultivated soils, presumably containing less labile soil OM (Q(10-q)=2.4 +/- 0.3) was greater than that for undisturbed grassland soils (Q(10-q)=1.7 +/- 0.1). Soil C losses estimated using this approach will differ from previous estimates as a function of the magnitude of the temperature increase and the proportion of whole soil OM comprised of compounds sensitive to temperature over that temperature range. It is likely that increased temperature has already prompted release of significant amounts of C to the atmosphere as CO2. Our results indicate that future losses of litter and soil C may be even greater than previously supposed.

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Until now health impact assessment and environmental impact assessment are two different issues, often not addressed together. Both issues have to be dealt with for sustainable building. The aim of this paper is to link healthy and sustainable housing in life cycle assessment. Two strategies are studied: clean air as a functional unity and health as a quality indicator. The strategies are illustrated with an example on the basis of Eco-Quantum, which is a Dutch whole-building assessment tool. It turns out that both strategies do not conflict with the LCA methodology. The LCA methodology has to be refined for this purpose.

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The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.