A practical approach for training dynamic recurrent neural networks: use of Apriori information

Presents a technique for incorporating a priori knowledge from a state space system into a neural network training algorithm. The training algorithm considered is that of chemotaxis and the networks being trained are recurrent neural networks. Incorporation of the a priori knowledge ensures that the resultant network has behaviour similar to the system which it is modelling.

Dynamic input/output linearization using recurrent neural networks

A dynamic recurrent neural network (DRNN) is used to input/output linearize a control affine system in the globally linearizing control (GLC) structure. The network is trained as a part of a closed loop that involves a PI controller, the goal is to use the network, as a dynamic feedback, to cancel the nonlinear terms of the plant. The stability of the configuration is guarantee if the network and the plant are asymptotically stable and the linearizing input is bounded.

Identification of nonlinear systems with a dynamic recurrent neural network

Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant.

Dynamic stall for a Vertical Axis Wind Turbine in a two-dimensional study

The last few years have proved that Vertical Axis Wind Turbines (VAWTs) are more suitable for urban areas than Horizontal Axis Wind Turbines (HAWTs). To date, very little has been published in this area to assess good performance and lifetime of VAWTs either in open or urban areas. At low tip speed ratios (TSRs<5), VAWTs are subjected to a phenomenon called 'dynamic stall'. This can really affect the fatigue life of a VAWT if it is not well understood. The purpose of this paper is to investigate how CFD is able to simulate the dynamic stall for 2-D flow around VAWT blades. During the numerical simulations different turbulence models were used and compared with the data available on the subject. In this numerical analysis the Shear Stress Transport (SST) turbulence model seems to predict the dynamic stall better than the other turbulence models available. The limitations of the study are that the simulations are based on a 2-D case with constant wind and rotational speeds instead of considering a 3-D case with variable wind speeds. This approach was necessary for having a numerical analysis at low computational cost and time. Consequently, in the future it is strongly suggested to develop a more sophisticated model that is a more realistic simulation of a dynamic stall in a three-dimensional VAWT.

Discrete demand side control performance under dynamic building simulation: a heat pump application

This study presents the findings of applying a Discrete Demand Side Control (DDSC) approach to the space heating of two case study buildings. High and low tolerance scenarios are implemented on the space heating controller to assess the impact of DDSC upon buildings with different thermal capacitances, light-weight and heavy-weight construction. Space heating is provided by an electric heat pump powered from a wind turbine, with a back-up electrical network connection in the event of insufficient wind being available when a demand occurs. Findings highlight that thermal comfort is maintained within an acceptable range while the DDSC controller maintains the demand/supply balance. Whilst it is noted that energy demand increases slightly, as this is mostly supplied from the wind turbine, this is of little significance and hence a reduction in operating costs and carbon emissions is still attained.

Simulating dynamic crop growth with an adapted land surface model – JULES-SUCROS: model development and validation

The increasing demand for ecosystem services, in conjunction with climate change, is expected to signif- icantly alter terrestrial ecosystems. In order to evaluate the sustainability of land and water resources, there is a need for a better understanding of the relationships between crop production, land surface characteristics and the energy and water cycles. These relationships are analysed using the Joint UK Land Environment Simulator (JULES). JULES includes the full hydrological cycle and vegetation effects on the energy, water, and carbon fluxes. However, this model currently only simulates land surface processes in natural ecosystems. An adapted version of JULES for agricultural ecosystems, called JULES-SUCROS has therefore been developed. In addition to overall model improvements, JULES-SUCROS includes a dynamic crop growth structure that fully fits within and builds upon the biogeochemical modelling framework for natural vegetation. Specific agro-ecosystem features such as the development of yield-bearing organs and the phenological cycle from sowing till harvest have been included in the model. This paper describes the structure of JULES-SUCROS and evaluates the fluxes simulated with this model against FLUXNET measurements at 6 European sites. We show that JULES-SUCROS significantly improves the correlation between simulated and observed fluxes over cropland and captures well the spatial and temporal vari- ability of the growth conditions in Europe. Simulations with JULES-SUCROS highlight the importance of vegetation structure and phenology, and the impact they have on land–atmosphere interactions.

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models.

An integrated dynamic whole life costing analysis for air distribution systems

Air distribution systems are one of the major electrical energy consumers in air-conditioned commercial buildings which maintain comfortable indoor thermal environment and air quality by supplying specified amounts of treated air into different zones. The sizes of air distribution lines affect energy efficiency of the distribution systems. Equal friction and static regain are two well-known approaches for sizing the air distribution lines. Concerns to life cycle cost of the air distribution systems, T and IPS methods have been developed. Hitherto, all these methods are based on static design conditions. Therefore, dynamic performance of the system has not been yet addressed; whereas, the air distribution systems are mostly performed in dynamic rather than static conditions. Besides, none of the existing methods consider any aspects of thermal comfort and environmental impacts. This study attempts to investigate the existing methods for sizing of the air distribution systems and proposes a dynamic approach for size optimisation of the air distribution lines by taking into account optimisation criteria such as economic aspects, environmental impacts and technical performance. These criteria have been respectively addressed through whole life costing analysis, life cycle assessment and deviation from set-point temperature of different zones. Integration of these criteria into the TRNSYS software produces a novel dynamic optimisation approach for duct sizing. Due to the integration of different criteria into a well- known performance evaluation software, this approach could be easily adopted by designers in busy nature of design. Comparison of this integrated approach with the existing methods reveals that under the defined criteria, system performance is improved up to 15% compared to the existing methods. This approach is interpreted as a significant step forward reaching to the net zero emission building in future.