Dynamic simulation for closed loops in heating systems with decision-making support

Nowadays utilising the proper HVAC system is essential both in extreme weather conditions and dense buildings design. Hydraulic loops are the most common parts in all air conditioning systems. This article aims to investigate the performance of different hydraulic loop arrangements in variable flow systems. Technical, economic and environmental assessments have been considered in this process. A dynamic system simulation is generated to evaluate the system performance and an economic evaluation is conducted by whole life cost assessment. Moreover, environmental impacts have been studied by considering the whole life energy consumption, CO2 emission, the embodied energy and embodied CO2 of the system components. Finally, decision-making in choosing the most suitable hydraulic system among five well-known alternatives has been proposed.

Dynamic hydrological modeling in drylands with TRMM based rainfall

This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

Dynamic causal modeling applied to fMRI data shows high reliability

Sensitivity, specificity, and reproducibility are vital to interpret neuroscientific results from functional magnetic resonance imaging (fMRI) experiments. Here we examine the scan–rescan reliability of the percent signal change (PSC) and parameters estimated using Dynamic Causal Modeling (DCM) in scans taken in the same scan session, less than 5 min apart. We find fair to good reliability of PSC in regions that are involved with the task, and fair to excellent reliability with DCM. Also, the DCM analysis uncovers group differences that were not present in the analysis of PSC, which implies that DCM may be more sensitive to the nuances of signal changes in fMRI data.

Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.

Dynamic simulation studies of structural formation and transition in electro-magneto-rheological fluids

The computer simulation method has been used to study the structural formation and transition of electro-magneto-rheological (EMR) fluids under compatible electric and magnetic fields. When the fields are applied simultaneously and perpendicularly to each other, the particles rapidly arrange into two-dimensional close-packed layer structures parallel to both fields. The layers then combine together to form thicker sheet-like structures, which finally relax into three-dimensional close-packed structures with the help of the thermal fluctuations. On the other hand, if the electric field is applied firstly to induce the body-centered tetragonal (BCT) columns in the system, and then the magnetic field is applied in the perpendicular direction. the BCT to face-centered cubic (FCC) structure transition is observed in very short time. Following that. the structure keeps on evolving due to the demagnetization effect and finally form the three-dimensional close-packed structures.

Characterising the energy performance of centralised HVAC&R systems in the UK

Heating, ventilation, air conditioning and refrigeration (HVAC&R) systems account for more than 60% of the energy consumption of buildings in the UK. However, the effect of the variety of HVAC&R systems on building energy performance has not yet been taken into account within the existing building energy benchmarks. In addition, the existing building energy benchmarks are not able to assist decision-makers with HVAC&R system selection. This study attempts to overcome these two deficiencies through the performance characterisation of 36 HVAC&R systems based on the simultaneous dynamic simulation of a building and a variety of HVAC&R systems using TRNSYS software. To characterise the performance of HVAC&R systems, four criteria are considered; energy consumption, CO2 emissions, thermal comfort and indoor air quality. The results of the simulations show that, all the studied systems are able to provide an acceptable level of indoor air quality and thermal comfort. However, the energy consumption and amount of CO2 emissions vary. One of the significant outcomes of this study reveals that combined heating, cooling and power systems (CCHP) have the highest energy consumption with the lowest energy related CO2 emissions among the studied HVAC&R systems.

Dynamic data reconciliation for sequential modular simulators

In this paper the implementation of dynamic data reconciliation techniques for sequential modular models is described. The paper is organised as follows. First, an introduction to dynamic data reconciliation is given. Then, the online use of rigorous process models is introduced. The sequential modular approach to dynamic simulation is briefly discussed followed by a short review of the extended Kalman filter. The second section describes how the modules are implemented. A simulation case study and its results are also presented.

Cool roofs for passive cooling: performance in different climates and for different insulation levels in Italy

Roofs are severely hit by solar radiation in summer; hence the use of cool materials on the finishing layer provides a significant reduction in the heat flow entering the building, with sensible attenuation in the building cooling load. In this paper, a case study is presented, based on the dynamic simulation of an existing office building in Catania (southern Italy). Here, a part of the roof has been recently treated with a commercial cool paint, with the aim of improving thermal comfort in summer. Hence, the simulations represent a preliminary study that will allow assessing the expected effectiveness of the intervention. More in detail, the results of the simulations will be discussed in terms of both thermal comfort and energy savings, through the evaluation of parameters such as the roof surface temperature, the operative temperature and the cooling load for both conditions, i.e. with and without the cool paint. The paper also discusses the potential increase in the energy needs for winter heating, and looks at the overall annual balance in terms of primary energy; this is made by considering different climatic conditions and envelope characteristics. These aspects are usually not well highlighted in the current scientific literature.

Controlling nitrate pollution: an integrated approach

The introduction of the EU Water Framework Directive requires policy to address non-point source pollution as part of an overall integrated strategy to improve the ecological status of water bodies. In this paper, we combine an economic optimisation framework with a dynamic simulation model of N transport in the Kennet Catchment to link decisions taken at the farm level to reductions in nitrate concentrations in the River Kennet. We examine a variety of policies targeted at reducing fertiliser use and changing the way in which farm land is used. We find that a tax on nitrogen emerges as the best policy both in terms of cost- and environmental effectiveness. Such a policy involves a considerable reduction in fertiliser use, as well as, a restructuring of land-use away from arable towards increased use of set-aside. Budgetary implications of such a radical move towards set-aside would be huge and hence unlikely to be politically palatable given the objective of reducing the EU budgetary allocation to agriculture. Additionally, the current rise in world demand for food may also mitigate calls for increasing the proportion of land taken out of agricultural production. Although the study succeeds in establishing a link between actions on the farm and nitrate concentrations in the stream water, further work is required to explore the effect of the retention of nitrates in the unsaturated zone and groundwater on this link.

Coronal mass ejections and magnetic flux buildup in the heliosphere

To test for magnetic flux buildup in the heliosphere from coronal mass ejections (CMEs), we simulate heliospheric flux as a constant background open flux with a time-varying interplanetary CME (ICME) contribution. As flux carried by ejecta can only contribute to the heliospheric flux budget while it remains closed, the ICME flux opening rate is an important factor. Two separate forms for the ICME flux opening rate are considered: (1) constant and (2) exponentially decaying with time. Coronagraph observations are used to determine the CME occurrence rates, while in situ observations are used to estimate the magnetic flux content of a typical ICME. Both static equilibrium and dynamic simulations, using the constant and exponential ICME flux opening models, require flux opening timescales of ∼50 days in order to match the observed doubling in the magnetic field intensity at 1 AU over the solar cycle. Such timescales are equivalent to a change in the ICME closed flux of only ∼7–12% between 1 and 5 AU, consistent with CSE signatures; no flux buildup results. The dynamic simulation yields a solar cycle flux variation with high variability that matches the overall variability of the observed magnetic field intensity remarkably well, including the double peak forming the Gnevyshev gap.

An integrated mathematical model to evaluate nutrient partition in dairy cattle between the animal and its environment

In the past decade, a number of mechanistic, dynamic simulation models of several components of the dairy production system have become available. However their use has been limited due to the detailed technical knowledge and special software required to run them, and the lack of compatibility between models in predicting various metabolic processes in the animal. The first objective of the current study was to integrate the dynamic models of [Brit. J. Nutr. 72 (1994) 679] on rumen function, [J. Anim. Sci. 79 (2001) 1584] on methane production, [J. Anim. Sci. 80 (2002) 2481 on N partition, and a new model of P partition. The second objective was to construct a decision support system to analyse nutrient partition between animal and environment. The integrated model combines key environmental pollutants such as N, P and methane within a nutrient-based feed evaluation system. The model was run under different scenarios and the sensitivity of various parameters analysed. A comparison of predictions from the integrated model with the original simulation models showed an improvement in N excretion since the integrated model uses the dynamic model of [Brit. J. Nutr. 72 (1994) 6791 to predict microbial N, which was not represented in detail in the original model. The integrated model can be used to investigate the degree to which production and environmental objectives are antagonistic, and it may help to explain and understand the complex mechanisms involved at the ruminal and metabolic levels. A part of the integrated model outputs were the forms of N and P in excreta and methane, which can be used as indices of environmental pollution. (C) 2004 Elsevier B.V All rights reserved.

Prefrontal inhibition of threat processing reduces working memory interference

Bottom-up processes can interrupt ongoing cognitive processing in order to adaptively respond to emotional stimuli of high potential significance, such as those that threaten wellbeing. However it is vital that this interference can be modulated in certain contexts to focus on current tasks. Deficits in the ability to maintain the appropriate balance between cognitive and emotional demands can severely impact on day-to-day activities. This fMRI study examined this interaction between threat processing and cognition; 18 adult participants performed a visuospatial working memory (WM) task with two load conditions, in the presence and absence of anxiety induction by threat of electric shock. Threat of shock interfered with performance in the low cognitive load condition; however interference was eradicated under high load, consistent with engagement of emotion regulation mechanisms. Under low load the amygdala showed significant activation to threat of shock that was modulated by high cognitive load. A directed top-down control contrast identified two regions associated with top-down control; ventrolateral PFC and dorsal ACC. Dynamic causal modeling provided further evidence that under high cognitive load, top-down inhibition is exerted on the amygdala and its outputs to prefrontal regions. Additionally, we hypothesized that individual differences in a separate, non-emotional top-down control task would predict the recruitment of dorsal ACC and ventrolateral PFC during top-down control of threat. Consistent with this, performance on a separate dichotic listening task predicted dorsal ACC and ventrolateral PFC activation during high WM load under threat of shock, though activation in these regions did not directly correlate with WM performance. Together, the findings suggest that under high cognitive load and threat, top-down control is exerted by dACC and vlPFC to inhibit threat processing, thus enabling WM performance without threat-related interference.

Modelling of control options for an outbreak of Mycoplasma gallisepticum in egg production: a decision support tool

Mycoplasma gallisepticum (MG) is a bacterium that causes respiratory disease in chickens, leading to reduced egg production. A dynamic simulation model was developed that can be used to assess the costs and benefits of control using antimicrobials or vaccination in caged or free range systems. The intended users are veterinarians and egg producers. A user interface is provided for input of flock specific parameters. The economic consequence of an MG outbreak is expressed as a reduction in expected egg output. The model predicts that either vaccination or microbial treatment can approximately halve potential losses from MG in some circumstances. Sensitivity analysis is used to test assumptions about infection rate and timing of an outbreak. Feedback from veterinarians points to the value of the model as a discussion tool with producers.

Molecular dynamics study on the equilibrium magnetization properties and structure of ferrofluids

We investigate in detail the initial susceptibility, magnetization curves, and microstructure of ferrofluids in various concentration and particle dipole moment ranges by means of molecular dynamics simulations. We use the Ewald summation for the long-range dipolar interactions, take explicitly into account the translational and rotational degrees of freedom, coupled to a Langevin thermostat. When the dipolar interaction energy is comparable with the thermal energy, the simulation results on the magnetization properties agree with the theoretical predictions very well. For stronger dipolar couplings, however, we find systematic deviations from the theoretical curves. We analyze in detail the observed microstructure of the fluids under different conditions. The formation of clusters is found to enhance the magnetization at weak fields and thus leads to a larger initial susceptibility. The influence of the particle aggregation is isolated by studying ferro-solids, which consist of magnetic dipoles frozen in at random locations but which are free to rotate. Due to the artificial suppression of clusters in ferrosolids the observed susceptibility is considerably lowered when compared to ferrofluids.