Robust design and optimisation of a radial turbine within a supercritical CO2 solar Brayton Cycle

The generation of solar thermal power is dependent upon the amount of sunlight exposure,as influenced by the day-night cycle and seasonal variations. In this paper, robust optimisation is applied to the design of a power block and turbine, which is generating 30 MWe from a concentrated solar resource of 560oC. The robust approach is important to attain a high average performance (minimum efficiency change) over the expected operating ranges of temperature, speed and mass flow. The final objective function combines the turbine performance and efficiency weighted by the off-design performance. The resulting robust optimisation methodology as presented in the paper gives further information that greatly aids in the design of non-classical power blocks through considering off-design conditions and resultant performance.

Stochastic analysis of a radial-inflow turbine in the presence of parametric uncertainties

This paper presents an uncertainty quantification study of the performance analysis of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multi-purpose Small Power Unit. A deterministic 3D volume-averaged Computational Fluid Dynamics (CFD) solver is coupled with a non-statistical generalized Polynomial Chaos (gPC) representation based on a pseudo-spectral projection method. One of the advantages of this approach is that it does not require any modification of the CFD code for the propagation of random disturbances in the aerodynamic and geometric fields. The stochastic results highlight the importance of the blade thickness and trailing edge tip radius on the total-to-static efficiency of the turbine compared to the angular velocity and trailing edge tip length. From a theoretical point of view, the use of the gPC representation on an arbitrary grid also allows the investigation of the sensitivity of the blade thickness profiles on the turbine efficiency. The gPC approach is also applied to coupled random parameters. The results show that the most influential coupled random variables are trailing edge tip radius coupled with the angular velocity.

Steam-cured stabilised soil blocks for masonry construction

Energy-efficient, economical and durable building materials are essential for sustainable construction practices. The paper deals with production and properties of energy-efficient steam-cured stabilised soil blocks used fbr masonry construction. Problems of mixing expansive soil and lime, and production of blocks using soil-lime mixtures have been discussed briefly. Details of steam curing of stabilised soil blocks and properties of such blocks are given. A comparison of energy content of steam-cured soil blocks and burnt bricks is presented. It has been shown that energy-efficient steam cured soil blocks (consuming 35% less thermal energy compared to burnt clay bricks) having high compressive strength can be easily produced in a decentralised manner.

Evaluation of super-heated steam vacuum drying viability and development of a predictive drying model for four Australian hardwood species.

The results of drying trials show that vacuum drying produces material of the same or better quality than is currently being produced by conventional methods within 41 to 66 % of the drying time, depending on the species. Economic analysis indicates positive or negative results depending on the species and the size of drying operation. Definite economic benefits exist by vacuum drying over conventional drying for all operation sizes, in terms of drying quality, time and economic viability, for E. marginata and E. pilularis. The same applies for vacuum drying C. citriodora and E. obliqua in larger drying operations (kiln capacity 50 m3 or above), but not for smaller operations at this stage. Further schedule refinement has the ability to reduce drying times further and may improve the vacuum drying viability of the latter species in smaller operations.

The potential benefits of divergent thinking and metacognitive skills in STEAM learning: A discussion paper

In the wake of an almost decade long economic downturn and increasing competition from developing economies, a new agenda in the Australian Government for science, technology, engineering, and mathematics (STEM) education and research has emerged as a national priority. However, to art and design educators, the pervasiveness and apparent exclusivity of STEM can be viewed as another instance of art and design education being relegated to the margins of curriculum (Greene, 1995). In the spirit of interdisciplinarity, there have been some recent calls to expand STEM education to include the arts and design, transforming STEM into STEAM in education (Maeda, 2013). As with STEM, STEAM education emphasises the connections between previously disparate disciplines, meaning that education has been conceptualised in different ways, such as focusing on the creative design thinking process that is fundamental to engineering and art (Bequette & Bequette, 2012). In this article, we discuss divergent creative design thinking process and metacognitive skills, how, and why they may enhance learning in STEM and STEAM.

Pilot-scale cellulosic ethanol production using eucalyptus biomass pre-treated by dilute acid and steam explosion

The widespread deployment of commercial-scale cellulosic ethanol currently hinges on developing and evaluating scalable processes whilst broadening feedstock options. This study investigates whole Eucalyptus grandis trees as a potential feedstock and demonstrates dilute acid pre-treatment (with steam explosion) followed by pre-saccharification simultaneous saccharification fermentation process (PSSF) as a suitable, scalable strategy for the production of bioethanol. Biomass was pre-treated in dilute H2SO4 at laboratory scale (0.1 kg) and pilot scale (10 kg) to evaluate the effect of combined severity factor (CSF) on pre-treatment effectiveness. Subsequently, pilot-scale pre-treated residues (15 wt.%) were converted to ethanol in a PSSF process at 2 L and 300 L scales. Good polynomial correlations (n = 2) of CSF with hemicellulose removal and glucan digestibility with a minimum R2 of 0.91 were recorded. The laboratory-scale 72 h glucan digestibility and glucose yield was 68.0% and 51.3%, respectively, from biomass pre-treated at 190 °C /15 min/ 4.8 wt.% H2SO4. Pilot-scale pre-treatment (180 °C/ 15 min/2.4 wt.% H2SO4 followed by steam explosion) delivered higher glucan digestibility (71.8%) and glucose yield (63.6%). However, the ethanol yields using PSSF were calculated at 82.5 and 113 kg/ton of dry biomass for the pilot and the laboratory scales, respectively. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

Analysis Of The Hvdc Turbine Generator Torsional Interactions

In the recent past it has been found that HVDC transmission systems and turbine-generator shaft torsional dynamics can interact in an unfavourable manner. This paper presents a detailed linearised state space model of AC/DC system to study this torsional interaction. The model developed is used to study the effect of various system parameters, such as, dc line loading, converter firing angle, the firing scheme employed. The results obtained are compared with those given in[3].

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Breakup of drops around the edges of Rushton turbine

A detailed experimental and simulation study has been carried out in the present work to understand drop breakup in regions around the edge of the Rushton turbine in agitated vessels. The effect of impeller speed, impeller size, interfacial tension, and the viscosities of the two phases is studied on drop breakup through their effect on dmax, the size of the largest drop in the system, and the whole size distribution. The measurements were carried out using Galai particle size analyser and optical microscope. Experimental analysis shows that the dmax, maximum stable drop diameter varies with impeller tip velocity to the power -1. The variation of dmax with interfacial tension is studied using different surfactants. The effect of viscosity ratio, achieved by changing the dispersed phase viscosity, on dmax is captured. For the same dmax values obtained from two different dispersed phases show that the wider drop size distribution is observed for higher dispersed phase viscosity.

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

Fuzzy logic intelligent system for gas turbine module and system fault isolation

A fuzzy logic intelligent system is developed for gas-turbine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. These four measurements are also called the cockpit parameters and are typically found in almost all older and newer jet engines. The fuzzy logic system uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. It automates the reasoning process of an experienced powerplant engineer. Tests with simulated data show that the fuzzy system isolates faults with an accuracy of 89% with only the four cockpit measurements. However, if additional pressure and temperature probes between the compressors and before the burner, which are often found in newer jet engines, are considered, the fault isolation accuracy rises to as high as 98%. In addition, the additional sensors are useful in keeping the fault isolation system robust as quality of the measured data deteriorates.

Properties of lime stabilised steam-cured blocks for masonry

The paper addresses certain issues pertaining to the technology of lime-stabilised steam-cured blocks used for masonry construction. Properties of lime-stabilised steam-cured blocks using expansive soils and tank bed soils have been examined. Influence of parameters like steam curing period, lime content and fly ash content on wet strength of blocks is studied. Steam curing of lime stabilised blocks at 80degreesC for about 20 hours at atmospheric pressure leads to considerably higher strengths when compared with curing under wet cloth at ambient temperatures. Clay-fly ash fractions of the mix control the optimum lime content yielding maximum strength. Long-term strength behaviour of steam-cured blocks has been monitored. The results indicate a favourable lime-clay ratio for stable long-term strength. A small-scale steam cured block production system has been designed and implemented to construct a load bearing masonry structure, thus demonstrating the potential of steam-cured block as a material for masonry construction.