Construction and application of an algebraic dual basis and the Fine-Scale Greens’ Function for computing projections and reconstructing unresolved scales

In this paper, we build on the work of Hughes and Sangalli (2007) dealing with the explicit computation of the Fine-Scale Greens’ function. The original approach chooses a set of functionals associated with a projector to compute the Fine-Scale Greens’ function. The construction of these functionals, however, does not generalise to arbitrary...

Exploring the dilemma of enterprises participating in the old community renewal: Perspective of managers

The renewal of old communities (OCR) is a crucial component of China's urban renewal strategy. However, the huge funding gap, coupled with the unwillingness of enterprises to participate, has impeded the sustainable development of OCR in China. This issue has become a major practical challenge for the government. This study employed the...

Organizational structure and dynamic capabilities on business model innovation in project-driven enterprises: evidence from the construction industry

Purpose: Flexibility and efficiency are dual attributes of the organizational structure that are crucial for project-driven enterprises to achieve sustainable development in a dynamic environment. However, there is a lack of research on the patterns by which the dual attributes of a project-driven enterprise’s organizational structure affect...

Infrared thermography: philosophy, approaches, analysis—processing, and guidelines

The infrared thermography (IRT) technique has shown great potential with many applications in a variety of fields, such as aerospace, petroleum, civil engineering, and so forth. This chapter is designed to provide an overview of the method of IRT in non-destructive material evaluation. It begins with the general introduction and development...

Continuous Human Activity Classification from FMCW Radar with Bi-LSTM Networks

Recognition of human movements with radar for ambient activity monitoring is a developed area of research that yet presents outstanding challenges to address. In real environments, activities and movements are performed with seamless motion, with continuous transitions between activities of different duration and a large range of dynamic...

Image analysis for classification of damaged and undamaged areas on composite structures

Composite materials are susceptible to barely visible impact damages (BVID) due to low-velocity impact. Therefore, an automated damage detection and quantification technique is highly desirable for quick inspection of large number of composite structures. Among various different non-destructive techniques (NDTs), active thermography NDT can...

Non-Destructive Testing for Detection, Localization and Quantification of Damage on Composite Structures for Composite Repair Applications

Composite materials are being widely used for manufacturing aircraft components due to their superior material properties such as high strength, light weight, corrosion resistance, etc. However, compared to isotropic materials, composite materials exhibit complex damage characteristics. Moreover, when the composite material is impacted by a...

Characterization of microbial communities in raw and homogenized bentonite samples

World-wide appreciated strategy for the management and treatment of high level and long lived radioactive waste is to dispose it in a deep and stable geological formation. Microbial community present in the host or buffer material may compromise the effective performance and safety of waste disposal system. In the Czech Republic, bentonite from...

Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments

In operational hydrology, estimation of the predictive uncertainty of hydrological models used for flood modelling is essential for risk-based decision making for flood warning and emergency management. In the literature, there exists a variety of methods analysing and predicting uncertainty. However, studies devoted to comparing the performance...

Estimation of predictive hydrologic uncertainty using quantile regression and UNEEC methods and their comparison on contrasting catchments (discussion paper)

In operational hydrology, estimation of predictive uncertainty of hydrological models used for flood modelling is essential for risk based decision making for flood warning and emergency management. In the literature, there exists a variety of methods analyzing and predicting uncertainty. However, case studies comparing performance of these...

Structural Flexibility of Large Direct Drive Generators for Wind Turbines

The trend in wind energy is towards large offshore wind farms. This trend has led to the demand for high reliability and large single unit wind turbines. Different energy conversion topologies such as multiple stage geared generators, single stage geared generators and gearless (direct drive) generators have been coupled to the wind turbine in...

Impact of climate change on sediment yield in the Mekong River basin: A case study of the Nam Ou basin, Lao PDR

This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach....

Uncertainty analysis in rainfall-runoff modelling: Application of machine learning techniques

This thesis presents powerful machine learning (ML) techniques to build predictive models of uncertainty with application to hydrological models. Two different methods are developed and tested. First one focuses on parameter uncertainty analysis by emulating the results of Monte Carlo simulations of hydrological models using efficient ML...

A novel approach to parameter uncertainty analysis of hydrological models using neural networks

In this study, a methodology has been developed to emulate a time consuming Monte Carlo (MC) simulation by using an Artificial Neural Network (ANN) for the assessment of model parametric uncertainty. First, MC simulation of a given process model is run. Then an ANN is trained to approximate the functional relationships between the input...

Possible Solutions to Overcome Drawbacks of Direct-Drive Generator for Large Wind Turbines

Investigation on the Possible Use of Magnetic Bearings in Large Direct Drive Wind Turbines

A direct drive generator used in wind turbine has high energy yield compared to other drivetrain topologies and low maintenance is expected as the technology matures. On the other hand direct drive generator weight and size increases rapidly when scaled up to larger units. This paper will investigate the possibility of weight reduction of large...

Direct drive wind turbine generator with magnetic bearing

Implementation of a process-based catchment model in a poorly gauged, highly glacierized Himalayan headwater