Advances in Design and Optimization Using Immersed Boundary Methods

This thesis is concerned with topology optimization which provides engineers with a systematic approach to optimize the layout and geometry of a structure against various design criteria. Traditional topology optimization uses density-based methods to capture topological changes in geometry. Density-based methods describe a structural layout using artificial elemental densities. To obtain a good resolution of the geometry, fine meshes are required. This however leads to large computational costs in 3D. Using coarser but practical meshes results in blurred structural boundaries and unreliable prediction of physical response along those boundaries. Using immersed boundary methods instead, such as the extended finite element method (XFEM), alleviates these issues. The XFEM provides clear description of the geometry, and approximation of the physical response along boundaries has been shown to converge to the approximation using body-fitted meshes. This thesis focuses on the use of XFEM for topology optimization. Design geometry in this thesis is tracked precisely using the level set method (LSM).The LSM-XFEM approach is used to solve variety of multiphysics design and optimization problems. However, being a relatively new field of study the LSM-XFEM approach continues to pose many interesting challenges limiting its applicability to topology optimization. The goal of this thesis is to present advances made towards making LSM-XFEM more viable and reliable for design and optimization of multiphysics problems. Specifically, i) The numerical behavior of XFEM-based shape sensitivities has not yet been investigated. This thesis presents a first-of-its kind study on the numerical behavior of shape sensitivities using the XFEM. ii) The matter of overestimation of stresses using the XFEM, a longstanding issue with no concrete resolution available in the literature, is addressed for robust stress-based optimization. iii) LSM-based topology optimization is known to suffer from slow design evolution resulting from localized sensitivities. A recently proposed concept of geometric primitives as design variables alleviates this issue. Literature on this concept has been restricted to single material problems using linear elasticity. Using the XFEM, this thesis extends the concept of geometric primitives as design variables to multiphase multiphysics problems in 3D

Design of effective fins for fast PCM melting and solidification in shell-and-tube latent heat thermal energy storage through topology optimization

This paper presents a unique solution to the problem of heat transfer intensification in shell-and-tube latent heat thermal energy storage units by means of high conducting fins. We developed a design approach using topology optimization and multi-phase computational fluid dynamics. No assumption is made about the fins layout, which freely evolves along the optimization process resulting in more efficient non-trivial geometries. At each optimization iteration, the fluid-dynamic response in the phase change material is computed by solving the transient Navier-Stokes equations augmented with a phase-change porosity term. Coupling large design freedom to detailed physics modeling allowed studying the effect of convective transport on both design and performance of latent heat thermal storage units. Results indicate that accounting for fluid flow in design optimization studies is crucial for performance. It is shown that melting and solidification can be enhanced remarkably through natural convection by using well engineered fins with specific design features, that could hardly be revealed with alternative design routes. These features make designs optimized for melting fundamentally different from those optimized for solidification

Topology optimization for heat transfer enhancement in Latent Heat Thermal Energy Storage

Performance of a Latent Heat Thermal Energy Storage depends strongly on the spatial layout of high conductive material and phase change material. Previous design studies have explored a limited design space and have rarely taken advantage of any formal optimization approach. This paper presents a topology optimization framework of a Thermal Energy Storage system involving phase change. We solve the Stefan problem for solidification with a fixed grid finite element method based on the apparent heat capacity technique, while the topology optimization problem is formulated using a density-based method. This approach allows to identify design trends that have been rarely investigated in the past. Firstly, we explore the inherent trade-off between discharged energy and required time for complete discharge. We obtain very different designs and highly varying performances at selected Pareto points. Secondly, by comparing results obtained in two and three dimensions we observe that 3D designs allow superior performances by presenting features that are not apparent in 2D. Thirdly, we propose a formulation of the design problem that yields a nearly constant thermal power output during the entire discharge process. If the maximum discharge time is sufficiently large, the optimized design presents fins that are disconnected from the internal tube

Idiopathic retroperitoneal cyst in an adult male

Retroperitoneal cysts are not common. Primary retroperitoneal cysts are essentially benign in nature. Mostly, they are detected incidentally. At times, they may attain a huge size and may present with large abdominal lump. In our case, a 55-year-old man had a left-sided large idiopathic retroperitoneal cyst, for which complete curative excision was performed

Topology optimization for heat transfer enhancement in Latent Heat Thermal Energy Storage

Performance of a Latent Heat Thermal Energy Storage depends strongly on the spatial layout of high conductive material and phase change material. Previous design studies have explored a limited design space and have rarely taken advantage of any formal optimization approach. This paper presents a topology optimization framework of a Thermal Energy Storage system involving phase change. We solve the Stefan problem for solidification with a fixed grid finite element method based on the apparent heat capacity technique, while the topology optimization problem is formulated using a density-based method. This approach allows to identify design trends that have been rarely investigated in the past. Firstly, we explore the inherent trade-off between discharged energy and required time for complete discharge. We obtain very different designs and highly varying performances at selected Pareto points. Secondly, by comparing results obtained in two and three dimensions we observe that 3D designs allow superior performances by presenting features that are not apparent in 2D. Thirdly, we propose a formulation of the design problem that yields a nearly constant thermal power output during the entire discharge process. If the maximum discharge time is sufficiently large, the optimized design presents fins that are disconnected from the internal tube

Design of effective fins for fast PCM melting and solidification in shell-and-tube latent heat thermal energy storage through topology optimization

This paper presents a unique solution to the problem of heat transfer intensification in shell-and-tube latent heat thermal energy storage units by means of high conducting fins. We developed a design approach using topology optimization and multi-phase computational fluid dynamics. No assumption is made about the fins layout, which freely evolves along the optimization process resulting in more efficient non-trivial geometries. At each optimization iteration, the fluid-dynamic response in the phase change material is computed by solving the transient Navier-Stokes equations augmented with a phase-change porosity term. Coupling large design freedom to detailed physics modeling allowed studying the effect of convective transport on both design and performance of latent heat thermal storage units. Results indicate that accounting for fluid flow in design optimization studies is crucial for performance. It is shown that melting and solidification can be enhanced remarkably through natural convection by using well engineered fins with specific design features, that could hardly be revealed with alternative design routes. These features make designs optimized for melting fundamentally different from those optimized for solidification

Solvent-free production of nano-FeS anchored graphene from Ulva fasciata: a scalable synthesis of super-adsorbent for lead, chromium and dyes

Here we demonstrate, a simple and solvent-free synthetic route for the production of FeS/Fe(0) functionalized graphene nanocomposite (G-Fe) via a one-step pyrolysis of seaweed biomass (Ulva fasciata). It is proposed that the natural abundance of both inorganic and organic sulfur in the seaweed induces the reduction of exfoliated graphitic sheets at elevated temperatures. FeCl3 was employed both as the iron precursor as well as the templating agent. Iron doping played a dual-faceted role of exfoliating as well as activating agent, producing composite with high adsorption capacity for Pb2+ (645 ± 10 mg/g), CR (970 mg/g), CV(909 mg/g), MO (664 mg/g), MB (402 mg/g) dyes and good recyclability (8 cycles). Pb2+ adsorption was irreversible even at low pH values and the spent composite (G-Fe-Pb) was utilized for efficient Cr(IV) removal (̴100 mg/g). The adsorption data followed the pseudo second order kinetics while the equilibrium data fitted perfectly into the Langmuir adsorption equation. Further, a thin layer of composite was deposited on a filter paper by vacuum filtration which was tested under continuous filtration mode for RB5 dye removal. Preliminary results highlight the potential of this composite to be used in pretreatment steps in hybrid membrane processes for filtration of complex wastewater feeds.by Ashesh Mahto, Anshu Kumar, Jai Prakash Chaudhary,Madhuri Bhatt, Atul Kumar Sharma,Parimal Paul, Sanna Kotrappanavar Nataraj and Ramavatar Meen

ExaWind: Open‐source CFD for hybrid‐RANS/LES geometry‐resolved wind turbine simulations in atmospheric flows

Predictive high-fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch-control, stall/vortex-induced vibrations, and aftermarket add-ons. The biggest challenge with high-fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high-performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU-enabled open-source incompressible-flow hybrid-computational fluid dynamics framework, comprising the near-body unstructured grid solver Nalu-Wind, and the off-body block-structured-grid solver AMR-Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds-averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds-averaged Navier–Stokes is used for near-body flow and large eddy simulation is used for off-body flow. Being two-way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry-resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt-scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states

ExaWind: Open‐source CFD for hybrid‐RANS/LES geometry‐resolved wind turbine simulations in atmospheric flows

Abstract Predictive high‐fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch‐control, stall/vortex‐induced vibrations, and aftermarket add‐ons. The biggest challenge with high‐fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high‐performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU‐enabled open‐source incompressible‐flow hybrid‐computational fluid dynamics framework, comprising the near‐body unstructured grid solver Nalu‐Wind, and the off‐body block‐structured‐grid solver AMR‐Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds‐averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds‐averaged Navier–Stokes is used for near‐body flow and large eddy simulation is used for off‐body flow. Being two‐way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry‐resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt‐scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states