37 research outputs found

    Multi‑physics bi‑directional evolutionary topology optimization on GPU‑architecture

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    Topology optimization has proven to be viable for use in the preliminary phases of real world design problems. Ultimately, the restricting factor is the computational expense since a multitude of designs need to be considered. This is especially imperative in such fields as aerospace, automotive and biomedical, where the problems involve multiple physical models, typically fluids and structures, requiring excessive computational calculations. One possible solution to this is to implement codes on massively parallel computer architectures, such as graphics processing units (GPUs). The present work investigates the feasibility of a GPU-implemented lattice Boltzmann method for multi-physics topology optimization for the first time. Noticeable differences between the GPU implementation and a central processing unit (CPU) version of the code are observed and the challenges associated with finding feasible solutions in a computational efficient manner are discussed and solved here, for the first time on a multi-physics topology optimization problem. The main goal of this paper is to speed up the topology optimization process for multi-physics problems without restricting the design domain, or sacrificing considerable performance in the objectives. Examples are compared with both standard CPU and various levels of numerical precision GPU codes to better illustrate the advantages and disadvantages of this implementation. A structural and fluid objective topology optimization problem is solved to vary the dependence of the algorithm on the GPU, extending on the previous literature that has only considered structural objectives of non-design dependent load problems. The results of this work indicate some discrepancies between GPU and CPU implementations that have not been seen before in the literature and are imperative to the speed-up of multi-physics topology optimization algorithms using GPUs

    Flow-Based Optimization of Products or Devices

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    Flow-based optimization of products and devices is an immature field compared to the corresponding topology optimization based on solid mechanics. However, it is an essential part of component development with both internal and/or external flow. The aim of this book is two-fold: (i) to provide state-of-the-art examples of flow-based optimization and (ii) to present a review of topology optimization for fluid-based problems

    From connected pathway flow to ganglion dynamics : understanding the effect of pore-scale properties on dynamic fluid connectivity and average flow functions

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    Since the turn of the industrial revolution in the early 1900s, the global economy has relied on fossil fuels for energy, transport, and other day to day industrial, commercial, and domestic activities. The combustion of fossil fuels (coal, petroleum (oil) and natural gas) is the primary cause of atmospheric carbon dioxide (CO2) emissions which result in climate change and global warming. Until we fully transition to cleaner alternative energy sources, the global economy will continue to rely on fossil fuels. The injection and storage of CO2 in subsurface geological formations such as saline aquifers and depleted oil and gas reservoirs, has been identified as a promising solution for mitigating climate change and global warming. Changes in reservoir rock and/or fluid properties at the pore-scale (scale of several microns) have been known to have an impact on flow and transport properties at the Darcy-scale (scale of several centimetres to metres). As such, successful implementation of CO2 storage technology at the large scale, relies heavily on our ability to understand and predict changes that occur in the subsurface at the pore scale and their subsequent effect on average flow functions. One of the major, unresolved challenges in upscaling multiphase flow from the pore scale to the Darcy scale lies in addressing the effects of connected and disconnected fluid fractions. Direct numerical simulations (DNS) were coupled with flow through experiments in miniature replicas of porous rocks fabricated on glass substrates (micromodels) to investigate the effects of pore-scale flow and transport properties on dynamic fluid connectivity and average flow functions such as displacement efficiency and the saturation function. Flow and transport properties investigated include surface roughness, wettability, as well as fluid velocity. Three pore-scale flow regimes were identified from the investigations conducted: two disconnected pore scale flow regimes namely, the ganglion dynamics (GD) regime and the droplet traffic flow (DTF) regime and a regime in which fluid displacement occurred by connected flow paths (the connected pathway flow (CPF) regime). It was established that there is a relationship between the dominant pore-scale mechanism and the kinetics of fluid displacement processes. Disconnected flow regimes were found to accelerate the fluid displacement process. The impact of disconnected and connected flow regimes was studied and it was determined that the GD regime can have a negative impact on the efficiency of subsurface fluid displacement processes and would adversely impact CO2 storage operations. In contrast, the DTF regime was found to enhance fluid displacement efficiency. Transitions between connected and disconnected flow regimes were also investigated and it was found that the shape of the saturation function is strongly influenced by transitions between pore-scale flow regimes. This work shows that the impact of pore-scale dynamic fluid connectivity on flow transport kinetics and the saturation function is highly significant and should not be ignored. Pore-scale property induced changes in the rate of change of saturation and the shape of the saturation function and could potentially have a knock-on effect on saturation dependent Darcy-scale functions such as relative permeability-saturation curves. Further work should be done to ascertain the relationship between dynamic fluid connectivity and relative permeability-saturation curves

    Numerical and experimental analysis on microbubble generation and multiphase mixing in novel microfluidic devices

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    In this study, a novel K-junction microfluidic junction and a conventional cross-junction were investigated numerically and experimentally for microbubble generation and multiple fluids mixing. In the K-junction, liquid solutions were injected into the junction via three liquid inlet channels, along with inert nitrogen gas supplied via the gas inlet channel, to periodically generate microbubbles in a controlled manner at the outlet channel. Numerical simulations based on Finite Volume method and Volume of Fluid (VOF) technique and experiments of both the K-junction and the cross-junction were conducted. The effect of parameters such as contact angle, surface tension, viscosity, gas pressure and gas-liquid flow ratios on the microbubble size distribution was investigated. The process of microbubble generation, obtained through high speed camera imaging and the numerical simulation, has shown good agreement in both junctions as well as the influence of viscosity and gas-liquid flow ratios for the K-junction and cross-junction. It was indicated that parameters like solution viscosities, gas-to-liquid flow ratios, gas inlet pressure, and their combination have a significant influence on the microbubble diameter, which was found to be in the range of 70-240 µm when using micro capillaries of 100 µm inner diameter. The multiple fluids mixing study was investigated by using two or three different polymer solutions for the cross-junction and the K-junction respectively in simulations and experiments. It can be seen that the mixing process obtained from simulations agrees well with experimental results and chaotic mixing was found in the mixing area of the K-junction, with higher mixing efficiency than the cross junction. Fluorescent images of microbubbles generated by using polymer solutions with dyes inside have shown the devices’ potential of encapsulating fluorescent dyes and polymers on the shell of bubbles and could be adopted as a method to encapsulate active pharmaceutical ingredients for potential applications in drug delivery

    Detection of Pathogens in Water Using Micro and Nano-Technology

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    Detection of Pathogens in Water Using Micro and Nano-Technology aims to promote the uptake of innovative micro and nano-technological approaches towards the development of an integrated, cost-effective nano-biological sensor useful for security and environmental assays.  The book describes the concerted efforts of a large European research project and the achievements of additional leading research groups. The reported knowledge and expertise should support in the innovation and integration of often separated unitary processes. Sampling, cell lysis and DNA/RNA extraction, DNA hybridisation detection micro- and nanosensors, microfluidics, together also with computational modelling and risk assessment can be integrated in the framework of the current and evolving European regulations and needs. The development and uptake of molecular methods is revolutionizing the field of waterborne pathogens detection, commonly performed with time-consuming cultural methods. The molecular detection methods are enabling the development of integrated instruments based on biosensor that will ultimately automate the full pathway of the microbiological analysis of water
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