Coordinated Design of Phase Measurement Unit and Power System Stabilisers in Large Scale Power System

This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

Fluid Shear Induces Conformation Change in Human Blood Protein von Willebrand Factor in Solution

Many of the physiological functions of von Willebrand Factor (VWF), including its binding interaction with blood platelets, are regulated by the magnitude of applied fluid/hydrodynamic stress. We applied two complementary strategies to study the effect of fluid forces on the solution structure of VWF. First, small-angle neutron scattering was used to measure protein conformation changes in response to laminar shear rates (G) up to 3000/s. Here, purified VWF was sheared in a quartz Couette cell and protein conformation was measured in real time over length scales from 2-140 nm. Second, changes in VWF structure up to 9600/s were quantified by measuring the binding of a fluorescent probe 1,1'-bis(anilino)-4-,4'-bis(naphtalene)-8,8'-disulfonate (bis-ANS) to hydrophobic pockets exposed in the sheared protein. Small angle neutron scattering studies, coupled with quantitative modeling, showed that VWF undergoes structural changes at G < 3000/s. These changes were most prominent at length scales <10 nm (scattering vector (q) range >0.6/nm). A mathematical model attributes these changes to the rearrangement of domain level features within the globular section of the protein. Studies with bis-ANS demonstrated marked increase in bis-ANS binding at G > 2300/s. Together, the data suggest that local rearrangements at the domain level may precede changes at larger-length scales that accompany exposure of protein hydrophobic pockets. Changes in VWF conformation reported here likely regulate protein function in response to fluid shear.

An Integrated Approach to Quantifying Groundwater and Surface Water Contributions of Stream Flow

The management of water resources in Ireland prior to the Water Framework Directive (WFD) has focussed on surface water and groundwater as separate entities. A critical element to the successful implementation of the
WFD is to improve our understanding of the interaction between the two and flow mechanisms by which groundwaters discharge to surface waters. An improved understanding of the contribution of groundwater to surface water is required for the classification of groundwater body status and the determination of groundwater quality thresholds. The results of the study will also have a wider application to many areas of the WFD.
A subcommittee of the WFD Groundwater Working Group (GWWG) has been formed to develop a methodology to estimate the groundwater contribution to Irish Rivers. The group has selected a number of analytical techniques to quantify components of stream flow in an Irish context (Master Recession Curve, Unit Hydrograph, Flood Studies Report methodologies and
hydrogeological analytical modelling). The components of stream flow that can be identified include deep groundwater, intermediate and overland. These analyses have been tested on seven pilot catchments that have a variety of hydrogeological settings and have been used to inform and constrain a mathematical model. The mathematical model used was the NAM (NedbØr-AfstrØmnings-Model) rainfall-runoff model which is a module of DHIs MIKE 11 modelling suite. The results from these pilot catchments have been used to develop a decision model based on catchment descriptors from GIS datasets for the selection of NAM parameters. The datasets used include the mapping of aquifers, vulnerability and subsoils, soils, the Digital Terrain Model, CORINE and lakes. The national coverage of the GIS datasets has allowed the extrapolation of the mathematical model to regional catchments across Ireland.

How does Oyster work? The simple interpretation of Oyster mathematics

Oyster® is a surface-piercing flap-type device designed to harvest wave energy in the nearshore environment. Established mathematical theories of wave energy conversion, such as 3D point-absorber and 2D terminator theory, are inadequate to accurately describe the behaviour of Oyster, historically resulting in distorted conclusions regarding the potential of such a concept to harness the power of ocean waves. Accurately reproducing the dynamics of Oyster requires the introduction of a new reference mathematical model, the “flap-type absorber”. A flap-type absorber is a large thin device which extracts energy by pitching about a horizontal axis parallel to the ocean bottom. This paper unravels the mathematics of Oyster as a flap-type absorber. The main goals of this work are to provide a simple–yet accurate–physical interpretation of the laws governing the mechanism of wave power absorption by Oyster and to emphasise why some other, more established, mathematical theories cannot be expected to accurately describe its behaviour.

Micro- and Nano-scale Tribo-Corrosion of Cast CoCrMo

Previous studies have established that some of the wear damage seen on cast CoCrMo joint surface is caused by entrained third-body hard particles. In this study, wet-cell micro-indentation and nano-scratch tests have been carried out with the direct aim of simulating wear damage induced by single abrasive particles entrained between the surfaces of cast CoCrMo hip implants. In situ electrochemical current noise measurements were uniquely performed to detect and study the wear-induced corrosion as well as the repassivation kinetics under the micro-/nano-scale tribological process. A mathematical model has been explored for the CoCrMo repassivation kinetics after surface oxide film rupture. Greater insights into the nature of the CoCrMo micro-/nano-scale wear-corrosion mechanisms and deformation processes are determined, including the identification of slip band formation, matrix/carbide deformation, nanocrystalline structure formation and strain-induced phase transformation. The electrochemical current noise provides evidence of instantaneous transient corrosion activity at the wearing surface resulting from partial oxide rupturing and stripping, concurrent with the indent/scratch.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Experimental design and batch experiments for optimization of Cr(VI) removal from aqueous solutions by hydrous cerium oxide nanoparticles

Hydrous cerium oxide (HCO) was synthesized by intercalation of solutions of cerium(III) nitrate and sodium hydroxide and evaluated as an adsorbent for the removal of hexavalent chromium from aqueous solutions. Simple batch experiments and a 2⁵ factorial experimental design were employed to screen the variables affecting Cr(VI) removal efficiency. The effects of the process variables; solution pH, initial Cr(VI) concentration, temperature, adsorbent dose and ionic strength were examined. Using the experimental results, a linear mathematical model representing the influence of the different variables and their interactions was obtained. Analysis of variance (ANOVA) demonstrated that Cr(VI) adsorption significantly increases with decreased solution pH, initial concentration and amount of adsorbent used (dose), but slightly decreased with an increase in temperature and ionic strength. The optimization study indicates 99% as the maximum removal at pH 2, 20 °C, 1.923 mM of metal concentration and a sorbent dose of 4 g/dm³. At these optimal conditions, Langmuir, Freundlich and Redlich–Peterson isotherm models were obtained. The maximum adsorption capacity of Cr(VI) adsorbed by HCO was 0.828 mmol/g, calculated by the Langmuir isotherm model. Desorption of chromium indicated that the HCO adsorbent can be regenerated using NaOH solution 0.1 M (up to 85%). The adsorption interactions between the surface sites of HCO and the Cr(VI) ions were found to be a combined effect of both anion exchange and surface complexation with the formation of an inner-sphere complex.

Interspecific competition in honeybee intracellular gut parasites is asymmetric and favours the spread of an emerging infectious disease

There is increasing appreciation that hosts in natural populations are subject to infection by multiple parasite species. Yet the epidemiological and ecological processes determining the outcome of mixed infections are poorly understood. Here, we use two intracellular gut parasites (Microsporidia), one exotic and one co-evolved in the western honeybee (Apis mellifera), in an experiment in which either one or both parasites were administered either simultaneously or sequentially. We provide clear evidence of within-host competition; order of infection was an important determinant of the competitive outcome between parasites, with the first parasite significantly inhibiting the growth of the second, regardless of species. However, the strength of this ‘priority effect’ was highly asymmetric, with the exotic Nosema ceranae exhibiting stronger inhibition of Nosema apis than vice versa. Our results reveal an unusual asymmetry in parasite competition that is dependent on order of infection. When incorporated into a mathematical model of disease prevalence, we find asymmetric competition to be an important predictor of the patterns of parasite prevalence found in nature. Our findings demonstrate the wider significance of complex multi-host–multi-parasite interactions as drivers of host–pathogen community structure

A Review of Directional Modulation Technology

Directional modulation (DM) is an emerging technology for securing wireless communications at the physical layer. This promising technology, unlike the conventional key-based cryptographic methods and the key-based physical layer security approaches, locks information signals without any requirements of keys. The locked information can only be fully recovered by the legitimate receiver(s) priory known by DM transmitters. This paper reviews the origin of the DM concept and, particularly, its development in recent years, including its mathematical model, assessment metrics, synthesis approaches, physical realizations, and finally its potential aspects for future studies.

Accurate image capturing control of bottle caps based on iterative learning control and Kalman filtering

This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.

Economical and coordinated dispatch of CHP based microgrid with renewable energy resources

The advantages of high energy efficiency and economic benefit promote the wide application of combined heat and power system (CHP) based microgrid. Firstly, a mathematical model of the CHP based microgrid is developed. Then, a cost function for the coordination of heat and electric load is proposed. Finally, an optimal dispatch model is developed to achieve the economical and coordinated operation of the CHP based microgrid system. Simulation results verify effectiveness of the proposed dispatch model, which is a powerful tool for the energy management of CHP based microgrid with renewable energy resources.

The Evolution of Extreme Cooperation via Shared Dysphoric Experiences

Willingness to lay down one’s life for a group of non-kin, well documented in the
historical and ethnographic records, represents an evolutionary puzzle. Here we
present a novel explanation for the willingness to fight and die for a group, combining evolutionary theorizing with empirical evidence from real-world human groups. Building on research in social psychology, we develop a mathematical model showing how conditioning cooperation on previous shared experience can allow extreme (i.e., life-threatening) pro-social behavior to evolve. The model generates a series of predictions that we then test empirically in a range of special sample populations (including military veterans, college fraternity/sorority members, football fans, martial arts practitioners, and twins). Our results show that sharing painful experiences produces “identity fusion” – a visceral sense of oneness – more so even than bonds of kinship, in turn motivating extreme pro-group behavior, including willingness to fight and die for the group. These findings have theoretical and practical relevance. Theoretically, our results speak to the origins of human cooperation, as we offer an explanation of extremely costly actions left unexplained by existing models.
Practically, our account of how shared dysphoric experiences produce identity fusion, which produces a willingness to fight and die for a non-kin group, helps us better understand such pressing social issues as suicide terrorism, holy wars, sectarian violence, gang-related violence, and other forms of intergroup conflict.