Characterization of sea water ageing effects on mechanical properties of carbon/epoxy composites for tidal turbine blades

In recent years, many tidal turbine projects have been developed using composites blades. Tidal turbine blades are subject to ocean forces and sea water aggressions, and the reliability of these components is crucial to the profitability of ocean energy recovery systems. The majority of tidal turbine developers have preferred carbon/epoxy blades, so there is a need to understand how prolonged immersion in the ocean affects these composites. In this study the long term behaviour of different carbon/epoxy composites has been studied using accelerated ageing tests. A significant reduction of composite strengths has been observed after saturation of water in the material. For longer immersions only small further changes in these properties occur. No significant changes have been observed for moduli nor for composite toughness. The effect of sea water ageing on damage thresholds and kinetics has been studied and modelled. After saturation, the damage threshold is modified while kinetics of damage development remain the same.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

ANN inverse analysis based on stochastic small-sample training set simulation

A new approach of inverse analysis is proposed to obtain parameters of a computational model in order to achieve the best agreement with experimental data. The inverse analysis is based on the coupling of a stochastic simulation and an artificial neural network (ANN). The identification parameters play the role of basic random variables with a scatter reflecting the physical range of potential values. A novelty of the approach is the utilization of the efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for the stochastic preparation of the training set utilized in training the artificial neural network. Once the network has been trained, it represents an approximation consequently utilized to solve the key task: To provide the best possible set of model parameters for the given experimental data. The efficiency of the approach is shown using numerical examples from civil engineering computational mechanics.     

Structural Response of Nuclear Containment Shield Buildings with Construction Openings

Steam generator replacement at nuclear power plants requires large construction openings in nuclear containment structures. This study examines the effects of such openings placed in a 61?cm (2?ft) thick dome of a shield building. The dome is cast in two layers, and the limiting cases of the two layers acting as one and the lower layer carrying the entire load are considered. Without openings, the stresses due to dead load in the structure are very low when compared to the material strength. With openings, the loads are easily redistributed around the opening, and the maximum stresses for the conservative case are between three and four and one-half times larger than in the original structure with no openings. The extent of the affected area around the holes is relatively small. Smooth corners in the openings are necessary to avoid high local stress concentrations.     

Investigation of a miniature centrifugal fan

A centrifugal fan was designed with a matching centrifugal volute flow channel in order to investigate a numerical simulation with prototype manufacturing, and to compare with experimental results. The fan configuration was developed according to a fan-design theorem. A model P-60 turbojet engine compressor blade design was adopted for the fan aerodynamic analysis and design. The results were verified using the STAR-CD code. Also, based on the findings, a miniature centrifugal fan was designed and manufactured using a CNC five axes machine. The P–Q performance curves were tested using an AMCA standard 210-85 test chamber apparatus. From the numerical analysis results, the pressure on the suction and pressure surfaces will increase gradually from the inlet to one-half the distance of the hub’s camber line, however, it will increase more rapidly afterwards. In addition, stress-concentration phenomenon occurred at the tip of the suction and pressure surfaces. In other words, the tip was more prone to damage when the fan was operated. Experiments show that the designed fan maximum flow rate Q and static pressure P were 32% and 59%, respectively, which were lower than the commercial fan data at 2000 rpm rotational speed. However, when the rotational speed was increased to 4000 rpm, the maximum flow rate Q and static pressure P were increased to 38% and 82%. This study concluded that a centrifugal fan’s static pressure at high rotational speed is higher than that of an axial-flow fan. Therefore, a centrifugal fan should be chosen if high static pressure cooling or blowing is required. This advanced research investigation is to build up the capabilities of design, analysis, manufacturing, and measurement of a centrifugal fan with an outer diameter smaller than 10 cm.     

Virtual Teams: Guide to Successful Implementation

The successful initiation and execution of a virtual team is gaining increasing attention in the design and construction community. From opportunities to integrate international and multidisciplinary teams to the opportunity to leverage the best resources in an organization on a given project, virtual teams can transform the concept of project planning and execution. However, potential barriers exist in several areas to the successful implementation of virtual teams. The needs of increased management emphasis, social and cultural understanding, and emphasis on common goals are only a few of the nontechnical factors that can turn successful virtual teaming into virtual frustration. When combined with traditional technical challenges including compatibility of systems, security, and the selection of appropriate technologies, the line between leveraging virtual technologies for enhanced solutions and introducing additional complications into the project process is one that can be easily crossed. This paper presents the findings of research that addresses the opportunities and potential barriers to successful virtual teams in the engineering, procurement, and construction industry. Combining results from current research, industry practices, and early results from nonconstruction industries, the research findings provide an initial path to successful virtual team implementation.     

Smart dispatching and optimal elevator group control through real-time occupancy-aware deep learning of usage patterns

Passengers spend much time on elevator journeys in high-rise buildings every day, in which unnecessary stops caused by lack of cab capacity take up a certain proportion of the journey time. This study proposes real-time occupancy-aware smart dispatching to avoid pick-up failure by introducing the occupancy information that reflects elevator capacity into the optimization model, thus improving dispatching performance. Occupancy awareness is firstly implemented with deep learning-based object detection to provide estimated capacity. Traffic pattern recognition is implemented with time series analysis and fuzzy logic. Case-based reasoning is applied to recognize the current usage pattern and to deploy specific dispatching strategies. A prioritized A* search model is built to solve dispatching optimization with occupancy information. Discrete event simulation is conducted with Simio and MATLAB to validate the proposed dispatching model.     

Pyrolysis and co-pyrolysis of lignite and plastic

The study firstly discusses the pyrolysis characteristics and kinetics by thermogravimetric analysis (TGA), and then investigates the pyrolysis of lignite and co-pyrolysis with plastic (polyethylene or polypropylene) in tube furnace. Meanwhile, the research focuses on the co-pyrolysis products under different mixing ratios as well as pyrolysis products at different testing temperatures and heating rates. The results show that higher final testing temperature and lower heating rate contribute to bond fission in lignite pyrolysis, resulting in less char product. In co-pyrolysis, lignite acts as hydrogen donor, and the yields of char and water rise with increasing amount of plastic in the mixture, while the yields of gas and tar decrease; and a little admixture of plastic will promote the production of gas and tar. Kinetic studies indicate that in temperature range of 530–600 °C, activation energies of lignite are higher than those of lignite/plastic blends, and as plastic mass ratio increases from 0% to 10%, samples need less energy to be decomposed during co-pyrolysis.