Measurements and modelling of airflows in houses using passive sampling and HAM software

Passive samplers have been predominantly used to monitor environmental conditions in single volumes. However, measurements using a calibrated passive sampler- Solid Phase Microextraction (SPME) fibre, in three houses with cold pitched roof, successfully demonstrated the potential of the SPME fibre as a device for monitoring air movement in two volumes. The roofs monitored were pitched at 15° - 30° with insulation thickness varying between 200-300 mm on the ceiling. For effective analysis, two constant sources of volatile organic compounds were diffused steadily in the house. Emission rates and air movement from the house to the roof was predicted using developed algorithms. The airflow rates which were calibrated against conventional tracer gas techniques were introduced into a HAM software package to predict the effects of air movement on other varying parameters. On average it was shown from the in situ measurements that about 20-30% of air entering the three houses left through gaps and cracks in the ceiling into the roof. Although these field measurements focus on the airflows, it is associated with energy benefits such that; if these flows are reduced then significantly energy losses would also be reduced (as modelled) consequently improving the energy efficiency of the house. Other results illustrated that condensation formation risks were dependent on the airtightness of the building envelopes including configurations of their roof constructions.

Analysis and modeling of active occupancy of the residential sector in Spain: an indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Stochastic growth and monetary policy: the impacts on the term structure of interest rates

This paper builds a simple, empirically-verifiable rational expectations model for term structure of nominal interest rates analysis. It solves an stochastic growth model with investment costs and sticky inflation, susceptible to the intervention of the monetary authority following a policy rule. The model predicts several patterns of the term structure which are in accordance to observed empirical facts: (i) pro-cyclical pattern of the level of nominal interest rates; (ii) countercyclical pattern of the term spread; (iii) pro-cyclical pattern of the curvature of the yield curve; (iv) lower predictability of the slope of the middle of the term structure; and (v) negative correlation of changes in real rates and expected inflation at short horizons.

Mathematical analysis and simulations involving chemotherapy and surgery on large human tumours under a suitable cell-kill functional response

Dosage and frequency of treatment schedules are important for successful chemotherapy. However, in this work we argue that cell-kill response and tumoral growth should not be seen as separate and therefore are essential in a mathematical cancer model. This paper presents a mathematical model for sequencing of cancer chemotherapy and surgery. Our purpose is to investigate treatments for large human tumours considering a suitable cell-kill dynamics. We use some biological and pharmacological data in a numerical approach, where drug administration occurs in cycles (periodic infusion) and surgery is performed instantaneously. Moreover, we also present an analysis of stability for a chemotherapeutic model with continuous drug administration. According to Norton & Simon [22], our results indicate that chemotherapy is less eficient in treating tumours that have reached a plateau level of growing and that a combination with surgical treatment can provide better outcomes.

Integrated analysis and design of optimization and up-scaling of inductively coupled plasma synthesis of nanoparticles

This study is focused on radio-frequency inductively coupled thermal plasma (ICP) synthesis of nanoparticles, combining experimental and modelling approaches towards process optimization and industrial scale-up, in the framework of the FP7-NMP SIMBA European project (Scaling-up of ICP technology for continuous production of Metallic nanopowders for Battery Applications). First the state of the art of nanoparticle production through conventional and plasma routes is summarized, then results for the characterization of the plasma source and on the investigation of the nanoparticle synthesis phenomenon, aiming at highlighting fundamental process parameters while adopting a design oriented modelling approach, are presented. In particular, an energy balance of the torch and of the reaction chamber, employing a calorimetric method, is presented, while results for three- and two-dimensional modelling of an ICP system are compared with calorimetric and enthalpy probe measurements to validate the temperature field predicted by the model and used to characterize the ICP system under powder-free conditions. Moreover, results from the modeling of critical phases of ICP synthesis process, such as precursor evaporation, vapour conversion in nanoparticles and nanoparticle growth, are presented, with the aim of providing useful insights both for the design and optimization of the process and on the underlying physical phenomena. Indeed, precursor evaporation, one of the phases holding the highest impact on industrial feasibility of the process, is discussed; by employing models to describe particle trajectories and thermal histories, adapted from the ones originally developed for other plasma technologies or applications, such as DC non-transferred arc torches and powder spherodization, the evaporation of micro-sized Si solid precursor in a laboratory scale ICP system is investigated. Finally, a discussion on the role of thermo-fluid dynamic fields on nano-particle formation is presented, as well as a study on the effect of the reaction chamber geometry on produced nanoparticle characteristics and process yield.

Dynamic characterisation of four nine-story large-panel R.C. buildings in Bishkek (Kyrgyzstan): A comparison between experimental ambient vibration analysis and numerical finite element modeling

With the outlook of improving seismic vulnerability assessment for the city of Bishkek (Kyrgyzstan), the global dynamic behaviour of four nine-storey r.c. large-panel buildings in elastic regime is studied. The four buildings were built during the Soviet era within a serial production system. Since they all belong to the same series, they have very similar geometries both in plan and in height. Firstly, ambient vibration measurements are performed in the four buildings. The data analysis composed of discrete Fourier transform, modal analysis (frequency domain decomposition) and deconvolution interferometry, yields the modal characteristics and an estimate of the linear impulse response function for the structures of the four buildings. Then, finite element models are set up for all four buildings and the results of the numerical modal analysis are compared with the experimental ones. The numerical models are finally calibrated considering the first three global modes and their results match the experimental ones with an error of less then 20%.

Uncovering the dynamics of cardiac systems using stochastic pacing and frequency domain analyses

Alternans of cardiac action potential duration (APD) is a well-known arrhythmogenic mechanism which results from dynamical instabilities. The propensity to alternans is classically investigated by examining APD restitution and by deriving APD restitution slopes as predictive markers. However, experiments have shown that such markers are not always accurate for the prediction of alternans. Using a mathematical ventricular cell model known to exhibit unstable dynamics of both membrane potential and Ca2+ cycling, we demonstrate that an accurate marker can be obtained by pacing at cycle lengths (CLs) varying randomly around a basic CL (BCL) and by evaluating the transfer function between the time series of CLs and APDs using an autoregressive-moving-average (ARMA) model. The first pole of this transfer function corresponds to the eigenvalue (λalt) of the dominant eigenmode of the cardiac system, which predicts that alternans occurs when λalt≤−1. For different BCLs, control values of λalt were obtained using eigenmode analysis and compared to the first pole of the transfer function estimated using ARMA model fitting in simulations of random pacing protocols. In all versions of the cell model, this pole provided an accurate estimation of λalt. Furthermore, during slow ramp decreases of BCL or simulated drug application, this approach predicted the onset of alternans by extrapolating the time course of the estimated λalt. In conclusion, stochastic pacing and ARMA model identification represents a novel approach to predict alternans without making any assumptions about its ionic mechanisms. It should therefore be applicable experimentally for any type of myocardial cell.

Markers Models in Survival Analysis and Applications to Issues Associated with AIDS

Jewell and Kalbfleisch (1992) consider the use of marker processes for applications related to estimation of the survival distribution of time to failure. Marker processes were assumed to be stochastic processes that, at a given point in time, provide information about the current hazard and consequently on the remaining time to failure. Particular attention was paid to calculations based on a simple additive model for the relationship between the hazard function at time t and the history of the marker process up until time t. Specific applications to the analysis of AIDS data included the use of markers as surrogate responses for onset of AIDS with censored data and as predictors of the time elapsed since infection in prevalent individuals. Here we review recent work on the use of marker data to tackle these kinds of problems with AIDS data. The Poisson marker process with an additive model, introduced in Jewell and Kalbfleisch (1992) may be a useful "test" example for comparison of various procedures.

Dissolution-Precipitation in Porous Media: Experiments and Modelling

The evolution of porosity due to dissolution/precipitation processes of minerals and the associated change of transport parameters are of major interest for natural geological environments and engineered underground structures. We designed a reproducible and fast to conduct 2D experiment, which is flexible enough to investigate several process couplings implemented in the numerical code OpenGeosys-GEM (OGS-GEM). We investigated advective-diffusive transport of solutes, effect of liquid phase density on advective transport, and kinetically controlled dissolution/precipitation reactions causing porosity changes. In addition, the system allowed to investigate the influence of microscopic (pore scale) processes on macroscopic (continuum scale) transport. A Plexiglas tank of dimension 10 × 10 cm was filled with a 1 cm thick reactive layer consisting of a bimodal grain size distribution of celestite (SrSO4) crystals, sandwiched between two layers of sand. A barium chloride solution was injected into the tank causing an asymmetric flow field to develop. As the barium chloride reached the celestite region, dissolution of celestite was initiated and barite precipitated. Due to the higher molar volume of barite, its precipitation caused a porosity decrease and thus also a decrease in the permeability of the porous medium. The change of flow in space and time was observed via injection of conservative tracers and analysis of effluents. In addition, an extensive post-mortem analysis of the reacted medium was conducted. We could successfully model the flow (with and without fluid density effects) and the transport of conservative tracers with a (continuum scale) reactive transport model. The prediction of the reactive experiments initially failed. Only the inclusion of information from post-mortem analysis gave a satisfactory match for the case where the flow field changed due to dissolution/precipitation reactions. We concentrated on the refinement of post-mortem analysis and the investigation of the dissolution/precipitation mechanisms at the pore scale. Our analytical techniques combined scanning electron microscopy (SEM) and synchrotron X-ray micro-diffraction/micro-fluorescence performed at the XAS beamline (Swiss Light Source). The newly formed phases include an epitaxial growth of barite micro-crystals on large celestite crystals (epitaxial growth) and a nano-crystalline barite phase (resulting from the dissolution of small celestite crystals) with residues of celestite crystals in the pore interstices. Classical nucleation theory, using well-established and estimated parameters describing barite precipitation, was applied to explain the mineralogical changes occurring in our system. Our pore scale investigation showed limits of the continuum scale reactive transport model. Although kinetic effects were implemented by fixing two distinct rates for the dissolution of large and small celestite crystals, instantaneous precipitation of barite was assumed as soon as oversaturation occurred. Precipitation kinetics, passivation of large celestite crystals and metastability of supersaturated solutions, i.e. the conditions under which nucleation cannot occur despite high supersaturation, were neglected. These results will be used to develop a pore scale model that describes precipitation and dissolution of crystals at the pore scale for various transport and chemical conditions. Pore scale modelling can be used to parameterize constitutive equations to introduce pore-scale corrections into macroscopic (continuum) reactive transport models. Microscopic understanding of the system is fundamental for modelling from the pore to the continuum scale.

Organic-walled dinoflagellate cysts analysis and statistical analysis of 116 surface sediment samples from the eastern Indian Ocean

Assemblages of organic-walled dinoflagellate cysts (dinocysts) from 116 marine surface samples have been analysed to assess the relationship between the spatial distribution of dinocysts and modern local environmental conditions [e.g. sea surface temperature (SST), sea surface salinity (SSS), productivity] in the eastern Indian Ocean. Results from the percentage analysis and statistical methods such as multivariate ordination analysis and end-member modelling, indicate the existence of three distinct environmental and oceanographic regions in the study area. Region 1 is located in western and eastern Indonesia and controlled by high SSTs and a low nutrient content of the surface waters. The Indonesian Throughflow (ITF) region (Region 2) is dominated by heterotrophic dinocyst species reflecting the region's high productivity. Region 3 is encompassing the area offshore north-west and west Australia which is characterised by the water masses of the Leeuwin Current, a saline and nutrient depleted southward current featuring energetic eddies.

Analysis and 2D Simulation of a Hexapod Robot Leg for Remote Exploration

A walking machine is a wheeled rover alternative, well suited for work in an unstructured environment and specially in abrupt terrain. They have some drawback like speed and power consumption, but they can achieve complex movements and protrude very little the environment they are working on. The locomotion system is determined by the terrain conditions and, in our case, this legged design has been chosen based in a working area like Rio Tinto in the South of Spain, which is a river area with abrupt terrain. A walking robot with so many degrees of freedom can be a challenge when dealing with the analysis and simulations of the legs. This paper shows how to deal with the kinematical analysis of the equations of a hexapod robot based on a design developed by the Center of Astrobiology INTA-CSIC following the classical formulation of equations

Analysis and design of a thrombectomy device by using simulation techniques

Purpose: In this work, we present the analysis, design and optimization of one experimental device recently developed in the UK, called the 'GP' Thrombus Aspiration Device (GPTAD). This device has been designed to remove blood clots without the need to make contact with the clot itself thereby potentially reducing the risk of problems such as downstream embolisation. Method: To obtain the minimum pressure necessary to extract the clot and to optimize the device, we have simulated the performance of the GPTAD analysing the resistances, compliances and inertances effects. We model a range of diameters for the GPTAD considering different forces of adhesion of the blood clot to the artery wall, and different lengths of blood clot. In each case we determine the optimum pressure required to extract the blood clot from the artery using the GPTAD, which is attached at its proximal end to a suction pump. Result: We then compare the results of our mathematical modelling to measurements made in laboratory using plastic tube models of arteries of comparable diameter. We use abattoir porcine blood clots that are extracted using the GPTAD. The suction pressures required for such clot extraction in the plastic tube models compare favourably with those predicted by the mathematical modelling. Discussion & Conclusion: We conclude therefore that the mathematical modelling is a useful technique in predicting the performance of the GPTAD and may potentially be used in optimising the design of the device.

Analysis and Quality Control from ARIMA Modeling

In this paper, we use ARIMA modelling to estimate a set of characteristics of a short-term indicator (for example, the index of industrial production), as trends, seasonal variations, cyclical oscillations, unpredictability, deterministic effects (as a strike), etc. Thus for each sector and product (more than 1000), we construct a vector of values corresponding to the above-mentioned characteristics, that can be used for data editing.