Umesh Gandhi

Design and fabrication of periodic lattice-based cellular structures

ABSTRACTA methodology, which consists of design, optimization and evaluation of periodic lattice-based cellular structures fabricated by additive manufacturing, is presented. A user-friendly design framework for lattice cellular structures is developed by using a size optimization algorithm. A 3D modeling process for the lattice-based cellular structures is introduced for non-linear finite element analysis and production. The approach is demonstrated on compression block with periodic lattice-based unit cells. First, based on loading condition, most appropriate lattice layout is selected. Then, for the selected lattice layout, the lattice components are modeled as simple beam and size of the beam cross sections is optimized using in-house optimization approach for both yield and local buckling criteria. The 3D model for the optimized lattice structure is built and non-linear finite element study is conducted to predict the performance. Physical parts are 3D printed and tested to compare with the simulatio...

Method to measure orientation of discontinuous fiber embedded in the polymer matrix from computerized tomography scan data

Usage of discontinuous glass fibers in injection- and compression-molded resin components is rapidly increasing to improve their mechanical properties. Since added fiber contributes to more strength along the fiber direction compared with transverse direction, the mechanical properties of such components strongly depend on the fiber orientation. Therefore, it is important to estimate the fiber orientation distribution in such materials. In this article, we are presenting a recently developed method to estimate fiber orientation using micro computerized tomography (CT) scan-generated three-dimensional (3-D) image of fibers. However, the large size of the CT scan-generated 3-D image often makes it difficult to separate each fiber and extract end point information. In this article, a novel method to address this challenge is presented. The micro-CT images were broken into finite volume, reducing data size, and then each fiber was reduced to its own centerline, using Mimics® Innovation Suite (Materialise NV), further reducing the data size. These 3-D centerlines were then used to quantify the second-order orientation tensor. The results from the proposed method are compared with the measurements using well-established industry standard approach called the method of ellipses for validation. The key challenges in estimating the fiber orientation are identified and future improvements are proposed.

An improved lattice structure design optimization framework considering additive manufacturing constraints

Purpose Methods to optimize lattice structure design, such as ground structure optimization, have been shown to be useful when generating efficient design concepts with complex truss-like cellular structures. Unfortunately, designs suggested by lattice structure optimization methods are often infeasible because the obtained cross-sectional parameter values cannot be fabricated by additive manufacturing (AM) processes, and it is often very difficult to transform a design proposal into one that can be additively designed. This paper aims to propose an improved, two-phase lattice structure optimization framework that considers manufacturing constraints for the AM process. Design/methodology/approach The proposed framework uses a conventional ground structure optimization method in the first phase. In the second phase, the results from the ground structure optimization are modified according to the pre-determined manufacturing constraints using a second optimization procedure. To decrease the computational cost of the optimization process, an efficient gradient-based optimization algorithm, namely, the method of feasible directions (MFDs), is integrated into this framework. The developed framework is applied to three different design examples. The efficacy of the framework is compared to that of existing lattice structure optimization methods. Findings The proposed optimization framework provided designs more efficiently and with better performance than the existing optimization methods. Practical implications The proposed framework can be used effectively for optimizing complex lattice-based structures. Originality/value An improved optimization framework that efficiently considers the AM constraints was reported for the design of lattice-based structures.

Optimal scheduling of parabolic heliostats aim targets in a mini-tower solar concentrator system

Solar tower with heliostat mirrors is an established technology for utility-scale solar energy harvesting. The setup has several advantages such as the capability to reach high temperature, modularity and ease of maintenance of the heliostats, containment of the high temperature zone, as well as overall low cost per harvested energy. Downscaling to medium and small scale applications is a desirable goal in order to attract more users of the technology. However, the downscaling often does not turn out economically feasible while using flat mirror heliostats, which are the norm in utility-scale systems. This is mainly due to the need to preserve the number (typically several hundred) of mirrors in order to maintain the solar concentration ratio. Use of parabolic mirrors instead can significantly reduce the required number of mirrors for smaller scale systems, but comes with new challenges. Unlike flat mirrors, the effective focal length of parabolic mirrors changes with the incidence angle causing undesirable variations in the concentration ratio and/or flux distribution at the receiver. To overcome this issue, we propose adjustment of the aim targets of the heliostat mirrors. Instead of aiming at the center of the receiver, aim targets are set as design variables and optimized to reduce undesirable peaks in the flux distribution. A special implementation of genetic algorithm is developed and applied to a case study of a nominal 10kW solar concentrator. Results of the study show significant improvement in flux distribution.Copyright

Effect of the initial fiber alignment on the mechanical properties for GMT composite materials

A glass-mat-reinforced thermoplastic (GMT) material is widely used in the automotive industry for components such as underbody shields, seat structures, front/rear bumper, and front-end modulus. Due to the higher residual length of the glass strands, GMT usually offers better mechanical properties than injection-molded fiber-reinforced thermoplastics. The GMT material is typically manufactured by compression molding (CM) of preimpregnated fibers–reinforced resin sheets called mat. Two types of mats, one with discontinuous random (RD) fibers and other with aligned continuous fibers, are considered in this study. A stack of such mats with different combinations is used to tailor the mechanical properties of the final part. During the CM, the fibers in the mat flow with the resin and change the alignment. In this study, we are presenting an approach to account for the initial condition, such as fiber length, orientation and concentration of the fibers in the mat, and process conditions used, to develop a material model for the finished part. First, a stack of mat with known fiber orientation, length, and concentration as initial conditions is simulated for CM to predict the fiber orientation in the finished part. Next, the material model for the finished parts is developed using a Mori–Tanaka homogenization approach. The fiber orientation in the finished part is mapped from the CM simulation. For the fiber concentration and fiber length distribution, we used an empirical approach. The cross section of the finished part is investigated under optical microscope, and the fiber length and concentration are estimated based on the microstructure and initial stacking of mats. The predicted fiber orientation tensor is verified with orientations measured using computerized tomography (CT) scan on actual parts. The material model is verified by comparing the predicted performance with the actual tensile and bending test results.

Semiempirical approach to predict shrinkage and warpage of fiber-reinforced polymers using measured material properties in finite element model:

The automotive industry has great interest in designing and producing lightweight high-performance components using fiber-reinforced polymers (FRPs), primarily due to their high specific strengths. Injection molding of FRP is one of the preferred processes to meet low-cost, high-volume objectives. It is imperative to account for shrinkage and warpage while designing the tools for injection molding. However, predicting shrinkage and warpage of injection-molded FRP parts remains a challenge. This is because both the structural and thermal properties depend on the condition of the fibers in the resin, that is, variation in the orientation, length, and concentration throughout the part. Additional challenges come from the fact that the material properties of polymers are a function of temperature, which varies as the parts cool. In this study, we are presenting a finite element-based semiempirical approach to address both these challenges and predict warpage due to cooling for a fiber-reinforced resin component in solid phase. The approach is demonstrated to predict warpage of an injection-molded flat plaque made of glass fiber-reinforced polypropylene, cooled from 160°C to room temperature of 23°C. First, the fiber orientation in the plaque is estimated. Next the material properties for the combined material, that is, glass and resin, are measured as a function of temperature. Then the combined material properties and calculated fiber orientations are used to estimate the ‘in-mold’ condition resin properties using reverse engineering. Finally, the warpage of the plaque is predicted using the estimated resin properties and fiber orientations. Warpage predictions using this method compare well with the measured experimental results. Our study demonstrates that valid predictions for shrinkage and warpage of injection-molded fiber-reinforced thermoplastic parts in solid phase can be made if accurate material properties are used.

Experimental Investigation of Drag Reduction on Automobiles With an Inflatable Boat-Tail

There is a growing demand for higher efficiency and more environmentally friendly vehicles, including better fuel economy, reduction in wind noise level, and greater vehicle performance and dynamic stability. These factors vary with aerodynamic performance. Overall, aerodynamic drag contributes to as much as 60% of a vehicles fuel consumption, motivating vehicle manufacturers to investigate new drag reduction applications. When streamlining a vehicle for aerodynamic performance, one method is by boattailing, or rear end tapering. This study includes an investigation of the overall potential of a lightweight yet rigid, inflatable drag reduction device, applied to a motor vehicle. Based on original concepts proposed by Toyota Research Institute North American (TRINA), combined with past research of inflatable technology, an inflatable drag reduction device is designed, manufactured, and tested. Peel strength of adhesive bonds testing provides detailed results of proper heat-sealable fabric utilization, and preferred materials are selected for inflatable models. Through multiple concept considerations and varying design stages ergonomic boattail designs evolve, as does construction, and manufacturing details are included. The inflatable boat-tail as a drag reduction device is examined through wind tunnel testing at Reynolds numbers O(10) by 2D wake survey and conservation of momentum theory, and multiple system designs are compared. Results show 10-80% decreased drag coefficients as a function of varying boat-tail construction compared to a baseline model. Wake survey is also performed at multiple heights along boat-tail sections, and 3D effects are investigated. Further investigations include wake survey velocity profiles as a function of angle of attack. Standard deviation and velocity fluctuations are compared for individual systems, and results are discussed.

A Design and Fabrication Framework for Periodic Lattice-Based Cellular Structures in Additive Manufacturing

A design framework that incorporates a size optimization algorithm is proposed for periodic lattice-based cellular structures fabricated by additive manufacturing. A 3D modeling process for the lattice-based cellular structures is integrated into the design framework for non-linear finite element analysis (FEA) and production. Material properties for the 3D printed parts are determined for the finite element study using reverse engineering of actual measured data. The lattice layout that will be used in the optimization is selected and the size of the cross sections is optimized using in-house optimization approach for both yield and local buckling criteria. The 3D model for the optimized lattice structure is built and non-linear finite element study is conducted to predict the performance. The approach is demonstrated on a compression block with periodic lattice-based unit cells. Physical parts are 3D printed and tested to compare with the simulations.Copyright

Optimization of Parabolic Heliostat Focal Lengths in a Mini-Tower Solar Concentrator System

Solar tower with heliostat mirrors is one of the established setups for utility-scale solar energy harvesting. Advantages of the setup include the capability to reach high temperature, modularity and ease of maintenance for the heliostats, containment of the high temperature zone atop the tower, as well as overall low cost per unit energy. However, downscaling to medium or small scale applications often does not turn out economically feasible with flat mirror heliostats that are the norm in utility-scale systems. This is mainly due to the need to preserve the solar concentration ratio, which in turn means the number of flat mirrors cannot be reduced. Use of parabolic mirrors instead can significantly reduce the required number of mirrors for smaller scale systems, but comes with new challenges. Unlike flat mirrors that have infinite effective focal length, the effective focal length of parabolic mirrors changes with the angle of incidence, which in turn, changes throughout the day and season. The design challenge tackled in this paper is that of optimal selection of the focal lengths of the heliostats in order to maximize the yearly harvested energy while maintaining the concentration ratio within desirable limits. A parameterized system model is developed and a genetic algorithm is implemented for the optimization task. The model is then applied to a demonstration case study of a 10 kW solar concentrator. Results of the study demonstrate the proposed design approach as well as show the promise for effective downscaling of tower and heliostat systems.Copyright