An explicit scheme for coupling temperature and concentration fields in solidification models

A numerical scheme for coupling temperature and concentration fields in a general solidification model is presented. A key feature of this scheme is an explicit time stepping used in solving the governing thermal and solute conservation equations. This explicit approach results in a local point-by-point coupling scheme for the temperature and concentration and avoids the multi-level iteration required by implicit time stepping schemes. The proposed scheme is validated by predicting the concentration field in a benchmark solidification problem. Results compare well with an available similarity solution. The simplicity of the proposed explicit scheme allows for the incorporation of complex microscale models into a general solidification model. This is demonstrated by investigating the role of dendrite coarsening on the concentration field in the solidification benchmark problem.

Accuracy of turbulence models and CFD for thermal characterisation of electronic systems

A major percentage of the heat emitted from electronic packages can be extracted by air cooling whether by means of natural or forced convection. This flow of air throughout an electronic system and the heat extracted is highly dependable on the nature of turbulence present in the flow field. This paper will discuss results from an investigation into the accuracy of turbulence models to predict air cooling for electronic packages and systems.

The study of flow and temperature fields in conducting droplets suspended in a DC/AC combination field

Electromagnetic Levitation (EML) is a valuable method for measuring the thermo-physical properties of metals - surface tensions, viscosity, thermal/electrical conductivity, specific heat, hemispherical emissivity, etc. – beyond their melting temperature. In EML, a small amount of the test specimen is melted by Joule heating in a suspended AC coil. Once in liquid state, a small perturbation causes the liquid envelope to oscillate and the frequency of oscillation is then used to compute its surface tension by the well know Rayleigh formula. Similarly, the rate at which the oscillation is dampened relates to the viscosity. To measure thermal conductivity, a sinusoidally varying laser source may be used to heat the polar axis of the droplet and the temperature response measured at the polar opposite – the resulting phase shift yields thermal conductivity. All these theoretical methods assume that convective effects due to flow within the droplet are negligible compared to conduction, and similarly that the flow conditions are laminar; a situation that can only be realised under microgravity conditions. Hence the EML experiment is the method favoured for Spacelab experiments (viz. TEMPUS). Under terrestrial conditions, the full gravity force has to be countered by a much larger induced magnetic field. The magnetic field generates strong flow within the droplet, which for droplets of practical size becomes irrotational and turbulent. At the same time the droplet oscillation envelope is no longer ellipsoidal. Both these conditions invalidate simple theoretical models and prevent widespread EML use in terrestrial laboratories. The authors have shown in earlier publications that it is possible to suppress most of the turbulent convection generated in the droplet skin layer, through use of a static magnetic field. Using a pseudo-spectral discretisation method it is possible compute very accurately the dynamic variation in the suspended fluid envelope and simultaneously compute the time-varying electromagnetic, flow and thermal fields. The use of a DC field as a dampening agent was also demonstrated in cold crucible melting, where suppression of turbulence was achieved in a much larger liquid metal volume and led to increased superheat in the melt and reduction of heat losses to the water-cooled walls. In this paper, the authors describe the pseudo-spectral technique as applied to EML to compute the combined effects of AC and DC fields, accounting for all the flow-induced forces acting on the liquid volume (Lorentz, Maragoni, surface tension, gravity) and show example simulations.

Predicting HCl concentrations in fire enclosures using an HCl decay model coupled to a CFD-based fire field model

The amount of atmospheric hydrogen chloride (HCl) within fire enclosures produced from the combustion of chloride-based materials tends to decay as the fire effluent is transported through the enclosure due to mixing with fresh air and absorption by solids. This paper describes an HCl decay model, typically used in zone models, which has been modified and applied to a computational fluid dynamics (CFD)-based fire field model. While the modified model still makes use of some empirical formulations to represent the deposition mechanisms, these have been reduced from the original three to two through the use of the CFD framework. Furthermore, the effect of HCl flow to the wall surfaces on the time to reach equilibrium between HCl in the boundary layer and on wall surfaces is addressed by the modified model. Simulation results using the modified HCl decay model are compared with data from three experiments. The model is found to be able to reproduce the experimental trends and the predicted HCl levels are in good agreement with measured values

Levitated liquid droplets in AC and DC magnetic field

Electromagnetic levitation of liquid metal droplets can be used to measure the properties of highly reactive liquid materials. Two independent numerical models, the commercial COMSOL and the spectral-collocation based free surface code SPHINX, have been applied to solve the transient electromagnetic, fluid flow and thermodynamic equations, which describe the levitated liquid motion and heating processes. The SPHINX model incorporates free surface deformation to accurately model the oscillations that result from the interaction between the electromagnetic and gravity forces, temperature dependent surface tension, magnetically controlled turbulent momentum transport. The models are adapted to incorporate periodic laser heating at the top of the droplet, which is used to measure the thermal conductivity of the material. Novel effects in the levitated droplet of magnetically damped turbulence and nonlinear growth of velocities in high DC magnetic field are analysed.

Models for magnetohydrodynamics of aluminium electrolysis cells

The electric current and the associated magnetic field in aluminium electrolysis cells create effects limiting the cell productivity and possibly cause instabilities: surface waving, ‘anode effects’, erosion of pot lining, feed material sedimentation, etc. The instructive analysis is presented via a step by step inclusion of different physical coupling factors affecting the magnetic field, electric current, velocity and wave development in the electrolysis cells. The full time dependent model couples the nonlinear turbulent fluid dynamics and the extended electromagnetic field in the cell, and the whole bus bar circuit with the ferromagnetic effects. Animated examples for the high amperage cells are presented. The theory and numerical model of the electrolysis cell is extended to the cases of variable cell bottom of aluminium layer and the variable thickness of the electrolyte due to the anode non-uniform burn-out process and the presence of the anode channels. The problem of the channel importance is well known Moreau-Evans model) for the stationary interface and the velocity field, and was validated against measurements in commercial cells, particularly with the recently published ‘benchmark’ test for the MHD models of aluminium cells [1]. The presence of electrolyte channels requires also to reconsider the previous magnetohydrodynamic instability theories and the dynamic wave development models. The results indicate the importance of a ‘sloshing’ parametrically excited MHD wave development in the aluminium production cells.

Multiple attractors of host-parasitoid models with integrated pest management strategies: eradication, persistence and outbreak

Host-parasitoid models including integrated pest management (IPM) interventions with impulsive effects at both fixed and unfixed times were analyzed with regard to host-eradication, host-parasitoid persistence and host-outbreak solutions. The host-eradication periodic solution with fixed moments is globally stable if the host's intrinsic growth rate is less than the summation of the mean host-killing rate and the mean parasitization rate during the impulsive period. Solutions for all three categories can coexist, with switch-like transitions among their attractors showing that varying dosages and frequencies of insecticide applications and the numbers of parasitoids released are crucial. Periodic solutions also exist for models with unfixed moments for which the maximum amplitude of the host is less than the economic threshold. The dosages and frequencies of IPM interventions for these solutions are much reduced in comparison with the pest-eradication periodic solution. Our results, which are robust to inclusion of stochastic effects and with a wide range of parameter values, confirm that IPM is more effective than any single control tactic.

Start-up and running forces on bulk solids feeders: experimental findings versus available models

Many different models have been postulated over the years for sizing of feeder drives; these models have different bases, some rationally based and others more rule-of-thumb. Experience of Jenike & Johanson and likewise of The Wolfson Centre in trouble-shooting feeder drives has shown that drive powers are often poorly matched, so there is clearly still some way to go towards establishing a universally-used reliable approach. This paper presents an on-going programme of work designed to measure feeder forces experimentally on a purpose designed testing rig, and to compare these against some of the best known available models, and also against a full size installation. One aspect which is novel is the monitoring of the transition between the “filling stress field” load on the feeder and the “flowing stress field” load.

Parameterisation of bivalve functional traits for mechanistic eco-physiological dynamic energy budget (DEB) models

Mechanistic models such as those based on dynamic energy budget (DEB) theory are emergent ecomechanics tools to investigate the extent of fitness in organisms through changes in life history traits as explained by bioenergetic principles. The rapid growth in interest around this approach originates from the mechanistic characteristics of DEB, which are based on a number of rules dictating the use of mass and energy flow through organisms. One apparent bottleneck in DEB applications comes from the estimations of DEB parameters which are based on mathematical and statistical methods (covariation method). The parameterisation process begins with the knowledge of some functional traits of a target organism (e. g. embryo, sexual maturity and ultimate body size, feeding and assimilation rates, maintenance costs), identified from the literature or laboratory experiments. However, considering the prominent role of the mechanistic approach in ecology, the reduction of possible uncertainties is an important objective. We propose a revaluation of the laboratory procedures commonly used in ecological studies to estimate DEB parameters in marine bivalves. Our experimental organism was Brachidontes pharaonis. We supported our proposal with a validation exercise which compared life history traits as obtained by DEBs (implemented with parameters obtained using classical laboratory methods) with the actual set of species traits obtained in the field. Correspondence between the 2 approaches was very high (>95%) with respect to estimating both size and fitness. Our results demonstrate a good agreement between field data and model output for the effect of temperature and food density on age-size curve, maximum body size and total gamete production per life span. The mechanistic approach is a promising method of providing accurate predictions in a world that is under in creasing anthropogenic pressure.

Changes in significant and maximum wave heights in the Norwegian Sea

This paper analyses 10 years of in-situ measurements of significant wave height (Hs) and maximum wave height (Hmax) from the ocean weather ship Polarfront in the Norwegian Sea. The 30-minute Ship-Borne Wave Recorder measurements of Hmax and Hs are shown to be consistent with theoretical wave distributions. The linear regression between Hmax and Hs has a slope of 1.53. Neither Hs nor Hmax show a significant trend in the period 2000–2009. These data are combined with earlier observations. The long-term trend over the period 1980–2009 in annual Hs is 2.72 ± 0.88 cm/year. Mean Hs and Hmax are both correlated with the North Atlantic Oscillation (NAO) index during winter. The correlation with the NAO index is highest for the more frequently encountered (75th percentile) wave heights. The wave field variability associated with the NAO index is reconstructed using a 500-year NAO index record. Hs and H max are found to vary by up to 1.42 m and 3.10 m respectively over the 500-year period. Trends in all 30-year segments of the reconstructed wave field are lower than the trend in the observations during 1980–2009. The NAO index does not change significantly in 21st century projections from CMIP5 climate models under scenario RCP85, and thus no NAO-related changes are expected in the mean and extreme wave fields of the Norwegian Sea.

Comparison of new and primary production models using SeaWiFS data in contrasting hydrographic zones of the northern North Atlantic.

The accuracy of two satellite models of marine primary (PP) and new production (NP) were assessed against 14C and 15N uptake measurements taken during six research cruises in the northern North Atlantic. The wavelength resolving model (WRM) was more accurate than the Vertical General Production Model (VGPM) for computation of both PP and NP. Mean monthly satellite maps of PP and NP for both models were generated from 1997 to 2010 using SeaWiFS data for the Irminger basin and North Atlantic. Intra- and inter-annual variability of the two models was compared in six hydrographic zones. Both models exhibited similar spatio-temporal patterns: PP and NP increased from April to June and decreased by August. Higher values were associated with the East Greenland Current (EGC), Iceland Basin (ICB) and the Reykjanes Ridge (RKR) and lower values occurred in the Central Irminger Current (CIC), North Irminger Current (NIC) and Southern Irminger Current (SIC). The annual PP and NP over the SeaWiFS record was 258 and 82 gC m-2 yr-1 respectively for the VGPM and 190 and 41 gC m-2 yr-1 for the WRM. Average annual cumulative sum in the anomalies of NP for the VGPM were positively correlated with the North Atlantic Oscillation (NAO) in the EGC, CIC and SIC and negatively correlated with the multivariate ENSO index (MEI) in the ICB. By contrast, cumulative sum of the anomalies of NP for the WRM were significantly correlated with NAO only in the EGC and CIC. NP from both VGPM and WRM exhibited significant negative correlations with Arctic Oscillation (AO) in all hydrographic zones. The differences in estimates of PP and NP in these hydrographic zones arise principally from the parameterisation of the euphotic depth and the SST dependence of photo-physiological term in the VGPM, which has a greater sensitivity to variations in temperature than the WRM. In waters of 0 to 5C PP using the VGPM was 43% higher than WRM, from 5 to 10C the VGPM was 29% higher and from 10 to 15C the VGPM was 27% higher.

Trait-based representation of diatom functional diversity in a plankton functional type model of the eutrophied southern North Sea

We introduce a trait-based description of diatom functional diversity to an existing plankton functional type (PFT) model, implemented for the eutrophied coastal ecosystem in the Southern Bight of the North Sea. The trait-based description represents a continuum of diatom species, each characterized by a distinct cell volume, and includes size dependence of four diatom traits: the maximum growth rate, the half-saturation constants for nutrient uptake, the photosynthetic efficiency, and the relative affinity of copepods for diatoms. Through competition under seasonally varying forcing, the fitness of each diatom varies throughout time, and the outcome of competition results in a changing community structure. The predicted seasonal change in mean cell volume of the community is supported by field observations: smaller diatoms, which are more competitive in terms of resource acquisition, prevail during the first spring bloom, whereas the summer bloom is dominated by larger species which better resist grazing. The size-based model is used to determine the ecological niche of diatoms in the area and identifies a range of viable sizes that matches observations. The general trade-off between small, competitive diatoms and large, grazing-resistant species is a convenient framework to study patterns in diatom functional diversity. PFT models and trait-based approaches constitute promising complementary tools to study community structure in marine ecosystems.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-abased models

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.

Genetic maternity and paternity in a local population of armadillos assessed by microsatellite DNA markers and field data.

Genetic data from polymorphic microsatellite loci were employed to estimate paternity and maternity in a local population of nine-banded armadillos (Dasypus novemcinctus) in northern Florida. The parentage assessments took advantage of maximum likelihood procedures developed expressly for situations when individuals of neither gender can be excluded a priori as candidate parents. The molecular data for 290 individuals, interpreted alone and in conjunction with detailed biological and spatial information for the population, demonstrate high exclusion probabilities and reasonably strong likelihoods of genetic parentage assignment in many cases; low mean probabilities of successful reproductive contribution to the local population by individual armadillo adults in a given year; and statistically significant microspatial associations of parents and their offspring. Results suggest that molecular assays of highly polymorphic genetic systems can add considerable power to assessments of biological parentage in natural populations even when neither parent is otherwise known.