CFD-simulations of wave-wind interaction

Apart from solar energy, wind energy is the renewable energy which has the greatest potential. Offshore wind power is expected to have an annual growth of approximately 30 % in the decade to come. Even though the offshore wind industry tends to use larger turbines than over land, the standards used in designs, for the rotor-nacelle assembly, are similar to those used for onshore wind turbines. Recent studies by Kalvig et al. and Obhrai et al. (2012) reveal weaknesses in the simplifications made regarding the marine boundary layer (MBL) in the governing industry guidance and standards. Precise knowledge of wind speed is generally important for wind farm design and operations such as design basis, wind site assessment, energy yield assessment and power prediction. Wind profile and turbulence characteristics depend on the wave state, but this is usually ignored and the surface thought of as level and smooth. Field experiments and numerical simulations by Sullivan et al. (2008) and Smedman and Semedo et al. (2009) show that wave state need to be taken into account. The goal of this study was to develop and use OpenFOAM to improve the understanding of the interactions between atmospheric wind field and surface waves. A Reynold’s averaging Navier Stokes (RANS) standard k-ε model with the capability to resolve a moving sinusoidal wave at its lower boundary was implemented. It was set up as a 2-dimensional and grid independent case. It was used as a basis for testing several boundary conditions and averaging procedures. Since a transient model is used it is important to know what to do when interpreting the results. What can one get out of snapshots, what should be averaged and how is the averaging done? Interesting patterns in the velocity profile and the turbulence characteristics were looked for in sensitivity studies where different input parameters on the wind speed and wave state were used., A comparison with the LES experiments of Sullivan et al.’s (2008) was performed in order to investigated if the wave modified wind field will be captured with the simpler CFD code? In order to answer the questions in Kalvig’s PhD work to some extent the following research question was defined: “In which way does the sea state influence the wind field in the MBL?” The answer to this is that surface waves impact the flow field and “footprints” are visible in the whole height of the domain. A “knee” is present as a result of speed up over the wave trough, supported by measurements from Smedman et al. (1999, 2009) and simulations from Sullivan et al. (2008). A good way of averaging was found as there is a need for averaging when studying varying wave parameters and when examining high wind speeds and rough wave states. Wind opposed with the wave propagation is decelerated close to the surface in accordance with Sullivan et al. (2008) and Smedman et al. (1999) and Kudryavtsev and Makin (2004). This implies highest vertical wind and resulting in the highest turbulent kinetic energy in an opposed situation. Although the LES experiment gives the most precise picture, the k-ɛ model used highlights many of the same features. Using OpenFOAM requires a steep learning curve but the hard work pays off as there are no expensive licenses which other similar programs have. With the results from the sensitivity studies and comparisons with Sullivan et al. (2008) the interdependence of wave and winds, and the ability of the former to influence the flow field, are reflected. This can be used by wind park developers, professionals involved in the offshore industry, and last not least in the further PhD work of Kalvig

On-line monitoring for operational control of water distribution networks

This work concerns the concept of on-line monitoring and control for water distribution networks. The problem is simple to state. It is to produce a robust scheme that can continuously provide reliable information about the state of a water network in real-time and over extended periods with the minimum of operator interaction. This thesis begins by proposing a relational database schema to store 'asset data' for a water distribution network and asserts that asset data should be used as a basis for network modelling. It presents a topology determination algorithm and a demand allocation algorithm so that a mathematical model can be maintained on-line, with operator intervention only necessary to record the change of state of non-telemetered plant items such as switch valves. In order to provide a reliable on-line model of a distribution system, an investigation has been carried out into the methods available for modelling water networks and in particular, the inherent assumptions in these practices. As a result, new methods have been produced for network element combination and for demand allocation. These methods both support the database approach and enhance the robustness of the system by increasing the range of conditions for which the resulting model is applicable. For operational control, a new technique for state estimation is proposed which combines the advantages of weighted least squares estimation with those of weighted least absolute values estimation. The proposed method is tolerant to transducer noise and to the presence of large measurement outliers. However, the method is not limited in its application to water networks and could be applied to a wide range of measurement processing problems. Lastiy, a new topology based method for processing suspect data is proposed which can determine the likely causes using identifying templates. Thus a new approach to water network monitoring is proposed via an overall framework into which the various tasks of on-line operational control can be integrated. The exercise has resulted in the production of a core software package which could realistically be used in a control room to facilitate reliable operational control of water distribution systems

A Methodological Approach to Knowledge-Based Engineering Systems for Manufacturing

A survey of implementations of the knowledge-based engineering approach in different technological sectors is presented. The main objectives and techniques of examined applications are pointed out to illustrate the trends and peculiarities for a number of manufacturing field. Existing methods for the development of these engineering systems are then examined in order to identify critical aspects when applied to manufacturing. A new methodological approach is proposed to overcome some specific limitations that emerged from the above-mentioned survey. The aim is to provide an innovative method for the implementation of knowledge-based engineering applications in the field of industrial production. As a starting point, the field of application of the system is defined using a spatial representation. The conceptual design phase is carried out with the aid of a matrix structure containing the most relevant elements of the system and their relations. In particular, objectives, descriptors, inputs and actions are defined and qualified using categorical attributes. The proposed method is then applied to three case studies with different locations in the applicability space. All the relevant elements of the detailed implementation of these systems are described. The relations with assumptions made during the design are highlighted to validate the effectiveness of the proposed method. The adoption of case studies with notably different applications also reveals the versatility in the application of the method

A Numerical study of resistance in a rough walled channel flow where the ratio of roughness length scale to the depth of flow varies over a wide range

Numerical calculations were performed over a variety of two-dimensional rib roughness configurations in which the ratio of flow depth to roughness height was varied from 1.1 to 40. Periodically fully developed flow was achieved by employing periodic boundary conditions and the effect of turbulence was accounted for by a two-layer model. These calculations were used to test the hypothesis that any rough wall resistance may be reduced to an equivalent wall shear stress located on a plane wall. The position of the plane wall is determined by a novel method of prediction obtained by consideration of strearnwise force moments. The resistance is then determined by three dynamically significant length scales: the first (yo) specifies the position of the equivalent plane wall, the second is the depth of flow h and the third is similar to Nikuradse's sand grain roughness k,,. The latter length scale is however depth dependent and a universal relationship is postulated: ks y,, -,= F(Tkwhere ksw is the asymptotic value of ks at very large flow depths. For the calculation of friction factor, a resistance equation is proposed of the form typical of fully rough flows. These postulates are supported by the numerical model results though further work including physical experiments is required to confirm them. Before applying the two-layer model to this problem it was tested on smooth rectangular duct flows and Schlichting's (1936) long angle roughness experiments. The opportunity was taken to further explore these flows, and in addition calculations were carried out for Grass et al's ( 199 1) open channel rib roughness experiments. The periodic boundary conditions were also applied to a larninar counter-flow plate-fin heat exchanger.A novel source-sinka rrangemenfto r heat flux was developedi n order to implement these boundary conditions

Calibration of full-waveform airborne laser scanning data for 3D object segmentation

Phd ThesisAirborne Laser Scanning (ALS) is a fully commercial technology, which has seen rapid uptake from the photogrammetry and remote sensing community to classify surface features and enhance automatic object recognition and extraction processes. 3D object segmentation is considered as one of the major research topics in the field of laser scanning for feature recognition and object extraction applications. The demand for automatic segmentation has significantly increased with the emergence of full-waveform (FWF) ALS, which potentially offers an unlimited number of return echoes. FWF has shown potential to improve available segmentation and classification techniques through exploiting the additional physical observables which are provided alongside the standard geometric information. However, use of the FWF additional information is not recommended without prior radiometric calibration, taking into consideration all the parameters affecting the backscattered energy. The main focus of this research is to calibrate the additional information from FWF to develop the potential of point clouds for segmentation algorithms. Echo amplitude normalisation as a function of local incidence angle was identified as a particularly critical aspect, and a novel echo amplitude normalisation approach, termed the Robust Surface Normal (RSN) method, has been developed. Following the radar equation, a comprehensive radiometric calibration routine is introduced to account for all variables affecting the backscattered laser signal. Thereafter, a segmentation algorithm is developed, which utilises the raw 3D point clouds to estimate the normal for individual echoes based on the RSN method. The segmentation criterion is selected as the normal vector augmented by the calibrated backscatter signals. The developed segmentation routine aims to fully integrate FWF data to improve feature recognition and 3D object segmentation applications. The routine was tested over various feature types from two datasets with different properties to assess its potential. The results are compared to those delivered through utilizing only geometric information, without the additional FWF radiometric information, to assess performance over existing methods. The results approved the potential of the FWF additional observables to improve segmentation algorithms. The new approach was validated against manual segmentation results, revealing a successful automatic implementation and achieving an accuracy of 82%

New Elements of Heat Transfer Efficiency Improvement in Systems and Units

Zvýšení efektivity výměny tepla vede k poklesu spotřeby energie, což se následně projeví sníženými provozními náklady, poklesem produkce emisí a potažmo také snížením dopadu na životní prostředí. Běžné způsoby zefektivňování přenosu tepla jako např. přidání žeber či vestaveb do trubek ovšem nemusí být vždy vhodné nebo proveditelné -- zvláště při rekuperaci tepla z proudů s vysokou zanášivostí. Jelikož intenzita přestupu tepla závisí i na charakteru proudění, distribuci toku a zanášení, které lze všechny výrazně ovlivnit tvarem jednotlivých součástí distribučního systému, bylo sestaveno několik zjednodušených modelů pro rychlou a dostatečně přesnou predikci distribuce a také aplikace pro tvarovou optimalizaci distribučních systémů využívající právě tyto modely. Přesnost jednoho z modelů byla dále zvýšena pomocí dat získaných analýzou 282 distribučních systémů v softwaru ANSYS FLUENT. Vytvořené aplikace pak lze využít během návrhu zařízení na výměnu tepla ke zvýšení jejich výkonu a spolehlivosti.Improved heat transfer efficiency leads to decrease in energy consumption which then results in lower equipment operational cost, reduced emissions, and consequently also lower environmental impact. However, common enhancement approaches such as adding fins or tube inserts may not always be suitable or feasible -- especially in case of heat recovery from streams having a high fouling propensity. Since heat transfer rate depends also on flow field characteristics, fluid distribution, and fouling which can all be greatly influenced by the actual shapes of flow system components, several simplified models for fast and accurate enough prediction of fluid distribution as well as applications for shape optimization based on these models were developed. In addition, accuracy of one of the models was further increased by fine-tuning it using data obtained by evaluation of 282 flow systems in the fluid flow modelling software ANSYS FLUENT. The created applications can then be employed during the design of heat exchange units to improve their performance and reliability.

Similarity reasoning for local surface analysis and recognition

This thesis addresses the similarity assessment of digital shapes, contributing to the analysis of surface characteristics that are independent of the global shape but are crucial to identify a model as belonging to the same manufacture, the same origin/culture or the same typology (color, common decorations, common feature elements, compatible style elements, etc.). To face this problem, the interpretation of the local surface properties is crucial. We go beyond the retrieval of models or surface patches in a collection of models, facing the recognition of geometric patterns across digital models with different overall shape. To address this challenging problem, the use of both engineered and learning-based descriptions are investigated, building one of the first contributions towards the localization and identification of geometric patterns on digital surfaces. Finally, the recognition of patterns adds a further perspective in the exploration of (large) 3D data collections, especially in the cultural heritage domain. Our work contributes to the definition of methods able to locally characterize the geometric and colorimetric surface decorations. Moreover, we showcase our benchmarking activity carried out in recent years on the identification of geometric features and the retrieval of digital models completely characterized by geometric or colorimetric patterns

Sediment transport in wind-exposed shallow, vegetated aquatic systems

Ecosystems with submersed vegetation are relatively shallow, physically stable and of moderate hydrodynamic energy. Submersed vegetation affect hydrodynamic friction for currents and waves resulting in increased overall frictional loss. Seagrasses shelter the sediment bed and reduce wind-wave resuspension. Bed sheltering factors were estimated from previous flume data on Laguna Madre seagrass species. Data from Laguna Madre indicate that total suspended material levels for bare areas are about an order of magnitude higher than some areas with submersed vegetation. Waves in Laguna Madre at depths less than 2 m were found to be smaller than those expected for the same non-dimensional depths based on studies in slightly deeper waters. Waves were depth-limited and in the transition wave lengths between deep-water and shallow-water waves. A scaling of wave energy and wave period by atmospheric shear stress, rather than the conventional wind speed, was found to improve prediction of wave characteristics. Atmospheric roughness height was related to wave height and “age” (the ratio of wave celerity to atmospheric friction velocity). Modeling requires process descriptions to be organized and prioritized resulting in model structures which might be different for different aquatic systems. Model formulations were defined with a single grain-class and simultaneous erosion and deposition (type I), and single (type II) and multiple (type III) grain classes with mutually exclusive erosion and deposition. Model formulations were compared. A type I sediment resuspension model was developed for Florida Bay, validated, and coupled to a water quality/ecological model of the system. For Laguna Madre, a two-dimensional depth-averaged type III sediment model was developed to make annual simulations for fixed seagrass characteristics, with and without dredged material disposal. Dredged material disposal involves more sediment than the total natural sediment input to this system, and near-field deposit areas expose an appreciable sediment source to possible resuspension. Measurements near a dredge-pipeline discharge indicated that a highly-stratified fluid-mud underflow slowly moved material hundreds of meters downslope as sediment deposited. Underflow layer-averaged concentration did not change much with distance from the discharge