928 resultados para Process Modelling
Resumo:
Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis
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Earthworms are significant ecosystem engineers and are an important component of the diet of many vertebrates and invertebrates, so the ability to predict their distribution and abundance would have wide application in ecology, conservation and land management. Earthworm viability is known to be affected by the availability and quality of food resources, soil water conditions and temperature, but has not yet been modelled mechanistically to link effects on individuals to field population responses. Here we present a novel model capable of predicting the effects of land management and environmental conditions on the distribution and abundance of Aporrectodea caliginosa, the dominant earthworm species in agroecosystems. Our process-based approach uses individual based modelling (IBM), in which each individual has its own energy budget. Individual earthworm energy budgets follow established principles of physiological ecology and are parameterised for A. caliginosa from experimental measurements under optimal conditions. Under suboptimal conditions (e.g. food limitation, low soil temperatures and water contents) reproduction is prioritised over growth. Good model agreement to independent laboratory data on individual cocoon production and growth of body mass, under variable feeding and temperature conditions support our representation of A. caliginosa physiology through energy budgets. Our mechanistic model is able to accurately predict A. caliginosa distribution and abundance in spatially heterogeneous soil profiles representative of field study conditions. Essential here is the explicit modelling of earthworm behaviour in the soil profile. Local earthworm movement responds to a trade-off between food availability and soil water conditions, and this determines the spatiotemporal distribution of the population in the soil profile. Importantly, multiple environmental variables can be manipulated simultaneously in the model to explore earthworm population exposure and effects to combinations of stressors. Potential applications include prediction of the population-level effects of pesticides and changes in soil management e.g. conservation tillage and climate change.
A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture
Resumo:
The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.
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The classic vertical advection-diffusion (VAD) balance is a central concept in studying the ocean heat budget, in particular in simple climate models (SCMs). Here we present a new framework to calibrate the parameters of the VAD equation to the vertical ocean heat balance of two fully-coupled climate models that is traceable to the models’ circulation as well as to vertical mixing and diffusion processes. Based on temperature diagnostics, we derive an effective vertical velocity w∗ and turbulent diffusivity k∗ for each individual physical process. In steady-state, we find that the residual vertical velocity and diffusivity change sign in mid-depth, highlighting the different regional contributions of isopycnal and diapycnal diffusion in balancing the models’ residual advection and vertical mixing. We quantify the impacts of the time-evolution of the effective quantities under a transient 1%CO2 simulation and make the link to the parameters of currently employed SCMs.
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This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.
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During the last few years Enterprise Architecture (EA) has received increasing attention among industry and academia. By adopting EA, organisations may gain a number of benefits such as better decision making,increased revenues and cost reduction, and alignment of business and IT. However, EA adoption has been found to be difficult. In this paper a model to explain resistance during EA adoption process (REAP) is introduced and validated. The model reveals relationships between strategic level of EA, resulting organisational changes, and sources of resistance. By utilising REAP model, organisations may anticipate and prepare for the organisational change resistance during EA adoption.
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Over the last decade the English planning system has placed greater emphasis on the financial viability of development. ‘Calculative’ practices have been used to quantify and capture land value uplifts. Development viability appraisal (DVA) has become a key part of the evidence base used in planning decision-making and informs both ‘site-specific’ negotiations about the level of land value capture for individual schemes and ‘area-wide’ planning policy formation. This paper investigates how implementation of DVA is governed in planning policy formation. It is argued that the increased use of DVA raises important questions about how planning decisions are made and operationalised, not least because DVA is often poorly understood by some key stakeholders. The paper uses the concept of governance to thematically analyse semi-structured interviews conducted with the producers of DVAs and considers key procedural issues including (in)consistencies in appraisal practices, levels of stakeholder consultation and the potential for client and producer bias. Whilst stakeholder consultation is shown to be integral to the appraisal process in order to improve the quality of the appraisals and to legitimise the outputs, participation is restricted to industry experts and excludes some interest groups, including local communities. It is concluded that, largely because of its recent adoption and knowledge asymmetries between local planning authorities and appraisers, DVA is a weakly governed process characterised by emerging and contested guidance and is therefore ‘up for grabs’.
Resumo:
Nutrient enrichment and drought conditions are major threats to lowland rivers causing ecosystem degradation and composition changes in plant communities. The controls on primary producer composition in chalk rivers are investigated using a new model and existing data from the River Frome (UK) to explore abiotic and biotic interactions. The growth and interaction of four primary producer functional groups (suspended algae, macrophytes, epiphytes, sediment biofilm) were successfully linked with flow, nutrients (N, P), light and water temperature such that the modelled biomass dynamics of the four groups matched that of the observed. Simulated growth of suspended algae was limited mainly by the residence time of the river rather than in-stream phosphorus concentrations. The simulated growth of the fixed vegetation (macrophytes, epiphytes, sediment biofilm) was overwhelmingly controlled by incoming solar radiation and light attenuation in the water column. Nutrients and grazing have little control when compared to the other physical controls in the simulations. A number of environmental threshold values were identified in the model simulations for the different producer types. The simulation results highlighted the importance of the pelagic–benthic interactions within the River Frome and indicated that process interaction defined the behaviour of the primary producers, rather than a single, dominant driver. The model simulations pose interesting questions to be considered in the next iteration of field- and laboratory based studies.
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From a construction innovation systems perspective, firms acquire knowledge from suppliers, clients, universities and institutional environment. Building information modelling (BIM) involves these firms using new process standards. To understand the implications on interactive learning using BIM process standards, a case study is conducted with the UK operations of a multinational construction firm. Data is drawn from: a) two workshops involving the firm and a wider industry group, b) observations of practice in the BIM core team and in three ongoing projects, c) 12 semi-structured interviews; and d) secondary publications. The firm uses a set of BIM process standards (IFC, PAS 1192, Uniclass, COBie) in its construction activities. It is also involved in a pilot to implement the COBie standard, supported by technical and management standards for BIM, such as Uniclass and PAS1192. Analyses suggest that such BIM process standards unconsciously shapes the firm's internal and external interactive learning processes. Internally standards allow engineers to learn from each through visualising 3D information and talking around designs with operatives to address problems during construction. Externally, the firm participates in trial and pilot projects involving other construction firms, government agencies, universities and suppliers to learn about the standard and access knowledge to solve its specific design problems. Through its BIM manager, the firm provides feedback to standards developers and information technology suppliers. The research contributes by articulating how BIM process standards unconsciously change interactive learning processes in construction practice. Further research could investigate these findings in the wider UK construction innovation system.
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Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what essons may be learned from FireMIP.
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The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.
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In this work, thermodynamic models for fitting the phase equilibrium of binary systems were applied, aiming to predict the high pressure phase equilibrium of multicomponent systems of interest in the food engineering field, comparing the results generated by the models with new experimental data and with those from the literature. Two mixing rules were used with the Peng-Robinson equation of state, one with the mixing rule of van der Waals and the other with the composition-dependent mixing rule of Mathias et al. The systems chosen are of fundamental importance in food industries, such as the binary systems CO(2)-limonene, CO(2)-citral and CO(2)-linalool, and the ternary systems CO(2)-Limonene-Citral and CO(2)-Limonene-Linalool, where high pressure phase equilibrium knowledge is important to extract and fractionate citrus fruit essential oils. For the CO(2)-limonene system, some experimental data were also measured in this work. The results showed the high capability of the model using the composition-dependent mixing rule to model the phase equilibrium behavior of these systems.
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The subject of this paper is the secular behaviour of a pair of planets evolving under dissipative forces. In particular, we investigate the case when dissipative forces affect the planetary semimajor axes and the planets move inwards/outwards the central star, in a process known as planet migration. To perform this investigation, we introduce fundamental concepts of conservative and dissipative dynamics of the three-body problem. Based on these concepts, we develop a qualitative model of the secular evolution of the migrating planetary pair. Our approach is based on the analysis of the energy and the orbital angular momentum exchange between the two-planet system and an external medium; thus no specific kind of dissipative forces is invoked. We show that, under the assumption that dissipation is weak and slow, the evolutionary routes of the migrating planets are traced by the Mode I and Mode II stationary solutions of the conservative secular problem. The ultimate convergence and the evolution of the system along one of these secular modes of motion are determined uniquely by the condition that the dissipation rate is sufficiently smaller than the proper secular frequency of the system. We show that it is possible to reassemble the starting configurations and the migration history of the systems on the basis of their final states and consequently to constrain the parameters of the physical processes involved.
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Land use leads to massive habitat destruction and fragmentation in tropical forests. Despite its global dimensions the effects of fragmentation on ecosystem dynamics are not well understood due to the complexity of the problem. We present a simulation analysis performed by the individual-based model FORMIND. The model was applied to the Brazilian Atlantic Forest, one of the world`s biodiversity hot spots, at the Plateau of Sao Paulo. This study investigates the long-term effects of fragmentation processes on structure and dynamics of different sized remnant tropical forest fragments (1-100 ha) at community and plant functional type (PFT) level. We disentangle the interplay of single effects of different key fragmentation processes (edge mortality, increased mortality of large trees, local seed loss and external seed rain) using simulation experiments in a full factorial design. Our analysis reveals that particularly small forest fragments below 25 ha suffer substantial structural changes, biomass and biodiversity loss in the long term. At community level biomass is reduced up to 60%. Two thirds of the mid- and late-successional species groups, especially shade-tolerant (late successional climax) species groups are prone of extinction in small fragments. The shade-tolerant species groups were most strongly affected; its tree number was reduced more than 60% mainly by increased edge mortality. This process proved to be the most powerful of those investigated, explaining alone more than 80% of the changes observed for this group. External seed rain was able to compensate approximately 30% of the observed fragmentation effects for shade-tolerant species. Our results suggest that tropical forest fragments will suffer strong structural changes in the long term, leading to tree species impoverishment. They may reach a new equilibrium with a substantially reduced subset of the initial species pool, and are driven towards an earlier successional state. The natural regeneration potential of a landscape scattered with forest fragments appears to be limited, as external seed rain is not able to fully compensate for the observed fragmentation-induced changes. Our findings suggest basic recommendations for the management of fragmented tropical forest landscapes. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Canonical Monte Carlo simulations for the Au(210)/H(2)O interface, using a force field recently proposed by us, are reported. The results exhibit the main features normally observed in simulations of water molecules in contact with different noble metal surfaces. The calculations also assess the influence of the surface topography on the structural aspects of the adsorbed water and on the distribution of the water molecules in the direction normal to the metal surface plane. The adsorption process is preferential at sites in the first layer of the metal. The analysis of the density profiles and dipole moment distributions points to two predominant orientations. Most of the molecules are adsorbed with the molecular plane parallel to surface, while others adsorb with one of the O-H bonds parallel to the surface and the other bond pointing towards the bulk liquid phase. There is also evidence of hydrogen bond formation between the first and second solvent layers at the interface. (c) 2007 Elsevier B.V. All rights reserved.