Design Optimization Stage Research Articles

Controlling local overheating in topology optimization for additive manufacturing

A novel constraint to prevent local overheating is presented for use in topology optimization (TO). The very basis for the constraint is the Additive Manufacturing (AM) process physics. AM enables fabrication of highly complex topologically optimized designs. However, local overheating is a major concern especially in metal AM processes leading to part failure, poor surface finish, lack of dimensional precision, and inferior mechanical properties. It should therefore be taken into account at the design optimization stage. However, including a detailed process simulation in the optimization would make the optimization intractable. Hence, a computationally inexpensive thermal process model, recently presented in the literature, is used to detect zones prone to local overheating in a given part geometry. The process model is integrated into density-based TO in combination with a robust formulation, and applied in various numerical test examples. It is found that existing AM-oriented TO methods which rely purely on overhang control do not ensure overheating avoidance. Instead, the proposed physics-based constraint is able to suppress geometric features causing local overheating and delivers optimized results in a computationally efficient manner.

In situ Thermoreflectance Characterization of Thermal Resistance in Multilayer Electronics Packaging.

High-performance, high-reliability microelectronic devices are essential for many applications. Thermal management is required to ensure that the temperature of semiconductor devices remains in a safe operating range. Advanced materials, such as silver-sintered die attach (the bond layer between the semiconductor die and the heat sink) and metal-diamond composite heat sinks, are being developed for this purpose. These are typically multilayered structures, with individual layer thicknesses ranging from tens of micrometers to millimeters. The effective thermal conductivity of individual layers likely differs from their bulk values due to interface effects and potential material imperfections. A method is needed to characterize the thermal resistance of these structures at the design optimization stage to understand what effect non-idealities may have on the final packaged device temperature. We have adapted the frequency-domain thermoreflectance technique to measure at low frequencies, from 10 Hz to 10 kHz, enabling multiple layers to be probed at depths from tens of micrometers to millimeters, which is tailored to assess novel device packaging and heat sinks. This is demonstrated by measuring the thermal resistance of a sintered silver die attach.

Weight optimization of metal T stiffened panel of a transport aircraft wing using CAE tools

Skin stiffened constructions are common in aircraft structural components that are subjected to compressive loads. The skin is so thin that it provides very little resistance to buckling against in-plane compressive loads. The objective of the design optimization is to obtain the minimum structural weight of the stiffened panel. The MSC/NASTRAN is used for design optimization. Von Misses failure criteria, Panel Buckling criteria (Metal) and Eigen value criteria are incorporated in an automatic way by exploiting the secondary response constraint feature of the design optimizer. The optimizer allows calculating the secondary response quantities at any stage of design optimization, using the primary response quantities like stress values and design variables values as input; and the secondary response constraint is used in defining the design constraints. Therefore, this study reveals that 125 mm stinger spacing is the optimum spacing and this configuration provides a reduction in weight by 22.14%

Weight optimization of a hat stiffened panel of a typical transport aircraft composite wing

This paper proposes a method of weight optimization of a composite hat stiffened panel of a transport aircraft wing meeting the strength and buckling design constraints for different stringer spacings. The final configuration of stiffened panel drives the optimum stringer spacing and the minimum weight. The YSFI criterion is used for strength whereas PBF criteria and the Eigen value approach is used for buckling. These criteria are incorporated in an automatic way by exploiting the secondary response constraint feature of design optimizer; which allows calculating the secondary response quantities at any stage of design optimization. The MSC/PATRAN and NASTRAN tools are used as pre processor and optimizer. Therefore, this study reveals that 150 mm stinger spacing is the optimum spacing, but for weight optimization, the 100 mm stringer spacing provides a reduction in weight by 31.18%.

Multilevel Robust Design Optimization of a Superconducting Magnetic Energy Storage Based on a Benchmark Study

Superconducting magnetic energy storage (SMES) systems with different superconducting materials are attracting great attentions and funding from the governments around the world because they are promising large-scale energy storage devices for future smart grid. Due to the high cost of SMES, its manufacturing quality and operation reliability have to be investigated in the design optimization stage. This paper presents a robust design optimization method to solve this issue based on a benchmark problem, TEAM problem 22. The proposed method is based on a technique called design for Six Sigma. Meanwhile, a three-level optimization framework is employed to reduce the computation cost of a finite-element analysis due to high-dimensional design space and Monte-Carlo analysis. As shown, the manufacturing reliability and quality of the investigated SMES after robust optimization have been increased greatly.

Design optimization of an ironless inductive position sensor for the LHC collimators

The Ironless Inductive Position Sensor (I2PS) is an air-cored displacement sensor which has been conceived to be totally immune to external DC/slowly-varying magnetic fields. It can thus be used as a valid alternative to Linear Variable Differential Transformers (LVDTs), which can show a position error in magnetic environments. In addition, since it retains the excellent properties of LVDTs, the I2PS can be used in harsh environments, such as nuclear plants, plasma control and particle accelerators. This paper focuses on the design optimization of the sensor, considering the CERN LHC Collimators as application. In particular, the optimization comes after a complete review of the electromagnetic and thermal modeling of the sensor, as well as the proper choice of the reading technique. The design optimization stage is firmly based on these preliminary steps. Therefore, the paper summarises the sensor's complete development, from its modeling to its actual implementation. A set of experimental measurements demonstrates the sensor's performances to be those expected in the design phase.

Bottom Shape Optimization of Two-piece Aluminum Beverage Bottle by Multilevel Optimization Method

The design variable progressive optimization method, a kind of multilevel optimization based on RSA, was applied to optimize the shape of two-piece resealable aluminum beverage bottle bottoms. On the basis of sensitivity analyses, the most effective dimensions are selected as design variables in the first stage of design optimization, while the dimensions with relatively small influences are optimized in the secondary stage. In the design optimization of the bottom, the column strengh was maximized, the bulge strength was restricted to fall into a range, and the maximum bottom growth and the axial displacement of sidewall were constrained.

AN INTEGRATED METHOD OF PARAMETER DESIGN AND TOLERANCE DESIGN

Taguchi proposed a two-stage approach to quality improvement: parameter design followed by tolerance design. A novel approach is proposed for integrating parameter design and tolerance design into a single stage of design optimization. It enjoys a de..

DESIGN OPTIMIZATION FOR ROBUSTNESS USING PERFORMANCE SIMULATION PROGRAMS

Abstract This paper presents a methodology to incorporate manufacturing and operational variances in the design optimization stage to achieve robust and optimal performance. The procedure uses Taguchi's orthogonal arrays to approximate the expected value of performance during optimization. This approach reduces the number of function evaluations in problems that use computationally expensive performance simulation programs. The method allows incorporation of variances on many variables simultaneously. This paper uses two illustrative examples: (1) Design of helical gears that have minimum transmission error and at the same time are less sensitive to manufacturing errors, (2) Design of beverage cans where we minimize the effects of errors in tooling on can weight and structural requirements. The optimal robust design shows a considerable decrease in sensitivity to manufacluring and operational variances and, at the same time, has good performance.