A novel hybrid simulation-optimization approach for the optimal design of multicomponent distillation columns

Póster presentado en Escape 22, European Symposium on Computer Aided Process Engineering, University College London, UK, 17-20 June 2012.

Comparison among monitoring strategies to assess water flow dynamic and soil hydraulic properties in agricultural soils

Irrigated agriculture is usually performed in semi-arid regions despite scarcity of water resources. Therefore, optimal irrigation management by monitoring the soil is essential, and assessing soil hydraulic properties and water flow dynamics is presented as a first measure. For this purpose, the control of volumetric water content, θ, and pressure head, h, is required. This study adopted two types of monitoring strategies in the same experimental plot to control θ and h in the vadose zone: i) non-automatic and more time-consuming; ii) automatic connected to a datalogger. Water flux was modelled with Hydrus-1D using the data collected from both acquisition strategies independently (3820 daily values for the automatic; less than 1000 for the non-automatic). Goodness-of-fit results reported a better adjustment in case of automatic sensors. Both model outputs adequately predicted the general trend of θ and h, but with slight differences in computed annual drainage (711 mm and 774 mm). Soil hydraulic properties were inversely estimated from both data acquisition systems. Major differences were obtained in the saturated volumetric water content, θs, and the n and α van Genuchten model shape parameters. Saturated hydraulic conductivity, Ks, shown lower variability with a coefficient of variation range from 0.13 to 0.24 for the soil layers defined. Soil hydraulic properties were better assessed through automatic data acquisition as data variability was lower and accuracy was higher.

Rowing Biomechanics: Technique Changes with an Increase of Power Demand

The sport of rowing has become more popular in the past decade. While it is a relatively low impact sport, injuries can occur, specifically to the ribs (Karlson K. A., 1998) and more often in female athletes (Hickey, Fricker, & McDonald , 1997). It has been proposed that as the athlete rows, applying a cyclical load to the body, the mid trapezius fatigues and is unable to resist the force produced during the drive phase (Warden S. J., Gutschlag, Wajswelner, & Crossley, 2002). Once this happens, the scapulae are then pulled anterio-laterally which increases the compression force on the ribs, increasing the risk of injury. The rowing motion of 12 female varsity and club rowers was tracked as they completed a fatiguing rowing test on a rowing ergometer. Results showed that the curvature of thoracic spine changed throughout the rowing cycle but did not change with increasing power level. The transverse shoulder angle decreased (the upper back was less straight) as power level increased (R2=-0.69±19), suggesting that the scapula moved anterio-laterally. This may be that as it tired, the mid-trapezius was unable to hold the scapulae in position. The decreasing transverse shoulder angle when the power level is increased indirectly supports the fatiguing of the retractor muscles as a mechanism of injury. It would be valuable to understand the limitations of each athlete and to be able to prescribe the optimal training zone to reduce the risk of injury.

Impacts of coal-fired power plants on local ground-water systems : Wisconsin power plant impact study /

Mode of access: Internet.

Operations and Planning in Sustainable Power Systems

Thesis (Ph.D.)--University of Washington, 2016-06

Handing over the keys : Contingency, power and resistance in the context of section 3LA of the Australian Crimes Act 1914

Using the work and ideas of French theorist Michel Foucault the writer examines s 3LA of the Crimes Act, which provides law enforcement officers with power to compel a person to reveal their private encryption keys and other personal information, and concludes that such a section creates fear, redirects flow of power between law enforcement agencies and citizens, and creates resistance.

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.

Whole genome analysis reveals a high incidence of non-optimal codons in secretory signal sequences of Escherichia coli

Translational pausing may occur due to a number of mechanisms, including the presence of non-optimal codons, and it is thought to play a role in the folding of specific polypeptide domains during translation and in the facilitation of signal peptide recognition during see-dependent protein targeting. In this whole genome analysis of Escherichia coli we have found that non-optimal codons in the signal peptide-encoding sequences of secretory genes are overrepresented relative to the mature portions of these genes; this is in addition to their overrepresentation in the 5'-regions of genes encoding non-secretory proteins. We also find increased non-optimal codon usage at the 3' ends of most E. coli genes, in both non-secretory and secretory sequences. Whereas presumptive translational pausing at the 5' and 3' ends of E. coli messenger RNAs may clearly have a general role in translation, we suggest that it also has a specific role in sec-dependent protein export, possibly in facilitating signal peptide recognition. This finding may have important implications for our understanding of how the majority of non-cytoplasmic proteins are targeted, a process that is essential to all biological cells. (C) 2004 Elsevier Inc. All rights reserved.

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.

Optimal strategies in political elections

In the Majoritarian Parliamentary System, the government has a constitutional right to call an early election. This right provides the government a control to achieve its objective to remain in power for as long as possible. We model the early election problem mathematically using opinion polls data as a stochastic process to proxy the government's probability of re-election. These data measure the difference in popularity between the government and the opposition. We fit a mean reverting Stochastic Differential Equation to describe the behaviour of the process and consider the possibility for the government to use other control tools, which are termed 'boosts' to induce shocks to the opinion polls by making timely policy announcements or economic actions. These actions improve the government's popularity and have some impact upon the early-election exercise boundary. © Austral. Mathematical Soc. 2005.

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

Optimal control and operation of drum granulation processes

Process optimisation and optimal control of batch and continuous drum granulation processes are studied in this paper. The main focus of the current research has been: (i) construction of optimisation and control relevant, population balance models through the incorporation of moisture content, drum rotation rate and bed depth into the coalescence kernels; (ii) investigation of optimal operational conditions using constrained optimisation techniques; (iii) development of optimal control algorithms based on discretized population balance equations; and (iv) comprehensive simulation studies on optimal control of both batch and continuous granulation processes. The objective of steady state optimisation is to minimise the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation-rate, bed depth (material charge), and moisture content of solids are practical decision (design) parameters for system optimisation. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray-rate is the most effective control (manipulative) variable. Although other possible manipulative variables, such as feed flow-rate and additional powder flow-rate have been investigated in the complete research project, only the single input problem with the binder spray rate as the manipulative variable is addressed in the paper to demonstrate the methodology. It can be shown from simulation results that the proposed models are suitable for control and optimisation studies, and the optimisation algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational conditions and dynamic trajectories with good convergence properties. (c) 2005 Elsevier Ltd. All rights reserved.

Sheet flow sediment transport under waves with acceleration skewness and boundary layer streaming

The effect of acceleration skewness on sheet flow sediment transport rates (q) over bar (s) is analysed using new data which have acceleration skewness and superimposed currents but no boundary layer streaming. Sediment mobilizing forces due to drag and to acceleration (similar to pressure gradients) are weighted by cosine and sine, respectively, of the angle phi(.)(tau)phi(tau) = 0 thus corresponds to drag dominated sediment transport, (q) over bar (s)similar to vertical bar u(infinity)vertical bar u(infinity), while phi(tau) = 90 degrees corresponds to total domination by the pressure gradients, (q) over bar similar to du(infinity)/dt. Using the optimal angle, phi = 51 degrees based on that data, good agreement is subsequently found with data that have strong influence from boundary layer streaming. Good agreement is also maintained with the large body of U-tube data simulating sine waves with superimposed currents and second-order Stokes waves, all of which have zero acceleration skewness. The recommended model can be applied to irregular waves with arbitrary shape as long as the assumption negligible time lag between forcing and sediment transport rate is valid. With respect to irregular waves, the model is much easier to apply than the competing wave-by-wave models. Issues for further model developments are identified through a comprehensive data review.

Optimum switching point assessment of parallel braking resistor and serial current limiter for power system stability enhancement

A new control algorithm using parallel braking resistor (BR) and serial fault current limiter (FCL) for power system transient stability enhancement is presented in this paper. The proposed control algorithm can prevent transient instability during first swing by immediately taking away the transient energy gained in faulted period. It can also reduce generator oscillation time and efficiently make system back to the post-fault equilibrium. The algorithm is based on a new system energy function based method to choose optimal switching point. The parallel BR and serial FCL resistor can be switched at the calculated optimal point to get the best control result. This method allows optimum dissipation of the transient energy caused by disturbance so to make system back to equilibrium in minimum time. Case studies are given to verify the efficiency and effectiveness of this new control algorithm.

Power generation investment opportunities evaluation: A comparison between net present value and real options approach

To evaluate an investment project in the competitive electricity market, there are several key factors that affects the project's value: the present value that the project could bring to investor, the possible future course of actions that investor has and the project's management flexibility. The traditional net present value (NPV) criteria has the ability to capture the present value of the project's future cash flow, but it fails to assess the value brought by market uncertainty and management flexibility. By contrast with NPV, the real options approach (ROA) method has the advantage to combining the uncertainty and flexibility in evaluation process. In this paper, a framework for using ROA to evaluate the generation investment opportunity has been proposed. By given a detailed case study, the proposed framework is compared with NPV and showing a different results