Multidisciplinary Design Optimization (MDO) is a method that has shown many promising results in the development of complex engineered products. To this date, research on MDO has been extensive, but at the same time, very few publications have addressed the aspect of how it can be taught to students and young professionals. In this light, this paper aims to present the experiences of the authors in respect to the development and management of an MDO course at Linköping University. First, this work will describe the authors' teaching approaches, and in particular, it will present the various educational activities that have been considered over the years as well as the lessons learnt. Secondly, this work will attempt to investigate how students perceive a set of common MDO concepts, and more specifically, it will present an analysis based on the results of two surveys that took place in 2016 and 2020, respectively. Given the above foundation, this paper will try to establish guidelines regarding the activities which are suitable for teaching each concept, while finally, it will also touch upon the challenges as well as the solutions for adjusting an MDO course to a distance learning mode.

In order to efficiently design and deliver customized products, it is crucial that the process of translating customer needs to engineering characteristics and into unique products is smooth and without any misinterpretations. The paper proposes a method that combines design optimization with value-driven design to support and automate configuration of customized products. The proposed framework is applied to a case example with spiral staircases, a product that is uniquely configured for each customer from a set of both standard and customized components; a process that is complex, iterative and error-prone. In the case example, the optimization and value-driven design models are used to automate and speed-up the process of delivering quotations and design proposals that could be judged based on both engineering characteristics as well as their added value, thereby increasing the knowledge at the sales stage. Finally, a multi-objective optimization algorithm is employed to generate a set of Pareto-optimal solutions that contain four clusters of solutions that dominate the baseline design. Hence the decision-maker is given a set of optimal solutions to choose from when balancing different economical and technical characteristics.

This paper proposes an optimization framework based on the OpenMDAO software library intended for engineer-to-order products and applies it to the conceptual design of a Mobile Miner. A Mobile Miner is a complex machine and a flexible alternative to Tunnel Boring Machines for small-scale tunneling and mining applications. The proposed framework is intended for use in early design and quotation stages with the objective to get fast estimates of important product characteristics, such as excavation rate and cutter lifetime. The ability to respond fast to customer requests is vital when offering customized products for specific applications and thereby to stay competitive on the global market. This is true for most engineer-to-order products and especially for mining equipment where each construction project is unique with different tunnel geometries and rock properties. The presented framework is applied to a specific use-case where the design of the miner's cutter wheel is in focus and a set of Pareto optimal designs are obtained. Furthermore, the framework extends the capabilities of OpenMDAO by including support for mixed-variable formulations and it supports an exploratory approach to design optimization.

This paper proposes a method to compare the performances of different methods for robust design optimization of computationally demanding models. Its intended usage is to help the engineer to choose the optimization approach when faced with a robust optimization problem. This paper demonstrates the usage of the method to find the most appropriate robust design optimization method to solve an engineering problem. Five robust design optimization methods, including a novel method, are compared in the demonstration of the comparison method. Four of the five compared methods involve surrogate models to reduce the computational cost of performing robust design optimization. The five methods are used to optimize several mathematical functions that should be similar to the engineering problem. The methods are then used to optimize the engineering problem to confirm that the most suitable optimization method was identified. The performance metrics used are the mean value and standard deviation of the robust optimum as well as an index that combines the required number of simulations of the original model with the accuracy of the obtained solution. These measures represent the accuracy, robustness, and efficiency of the compared methods. The results of the comparison show that sequential robust optimization is the method with the best balance between accuracy and number of function evaluations. This is confirmed by the optimizations of the engineering problem. The comparison also shows that the novel method is better than its predecessor is.

Recent research on economic voting has moved beyond the traditional reward–punishment hypothesis, according to which the economy is merely considered a valence issue. Instead, patrimonial economic voting research looks at voters as property owners within the economic system. These studies have relied on survey items that measure whether individuals own different kinds of property to test the patrimonial dimension. This study emphasizes the importance of a surprisingly neglected aspect: the value of assets. It uses official register data files from the Swedish Tax Agency on the value of individuals’ assets merged with survey data from the 2006 Swedish National Election Study. The study finds that the relationship between patrimony and voting behavior in Sweden is similar to that found in other countries, but only when it is tested in a similar way as in these studies – that is, only when it is coded as whether voters own different assets. This study brings three important contributions to the debate. First, it offers a new empirically based categorization of the dimensionality of asset ownership and shows that the previous distinction between low- and high-risk assets is insufficient. Secondly, it shows that merely having assets or not, which is what previous studies have measured, is not what primarily matters; the relevant factor is the value of the assets. And thirdly, it demonstrates that only the value of some kinds of assets matters (especially stocks and real estate properties), while other assets (savings in bonds and funds) do not affect voting behavior or political opinions.

We report on a preferred phase shift ΔΦ0 between a spin torque oscillator (STO) and an ac current (Iac) injected at the intrinsic frequency (fSTO) of the STO. In the in-plane precession mode (IP) the STO adjusts to a state where its resistance (or voltage) lags Iac about a quarter of a wave length (ΔΦ0 = 87°−94°). In the IP mode ΔΦ0 increases somewhat with the dc current. As the precession changes into the Out-Of-Plane (OOP) mode, ΔΦ0 jumps by about 180°, i.e. the STO resistance now precedes Iac by about a quarter of a wave length (|ΔΦ0| = 86°). At the IP/OOP boundary, the ac current mixes the two oscillation modes and both periodic and chaotic oscillations are observed. As a consequence of mixing, subharmonic terms appear in the STO signal. ΔΦ0 can furthermore be tuned by changing one or more of the anisotropy field, the demagnetizing field or the applied field. At the IP/OOP boundary, Iac mixes the two oscillation modes. The intrinsic ΔΦ0 will impact any circuit design based on STO technology and will e.g. have direct consequences for phase locking in networks of serially connected STOs.

Current-induced magnetization dynamics in a system composed of two electrically coupled spin torque oscillators (STOs) is examined. The dynamics of the STOs is modeled by the Landau–Lifshitz–Gilbert equations modified with a Slonczewski spin-transfer torque term. To study the impact of realistic process variations on STO synchronization we let the two STOs have different in-plane anisotropy fields (Hk). The simulation also provides for a time delay τ. We construct a phase diagram of the STO synchronization as a function of Hk and direct current (Idc) at different τ. The phase diagram turns out to be quite rich with different types of synchronized precession modes. While the synchronized state is originally very sensitive to STO process variations and can only sustain up to 4% Hk variation, the addition of a small time delay dramatically improves its robustness and allows as much as 145% Hk variation in the entire out-of-plane precession regime. It is also shown that the two STOs can not only be locked in frequency, but also in phase at a given τ and the phase difference between the two STOs can be tuned by varying the dc current.

A novel superfamily designated MAPEG (Membrane Associated Proteins in Eicosanoid and Glutathione metabolism), including members of widespread origin with diversified biological functions is defined according to enzymatic activities, sequence motifs, and structural properties. Two of the members are crucial for leukotriene biosynthesis, and three are cytoprotective exhibiting glutathione S-transferase and peroxidase activities. Expression of the most recently recognized member is strongly induced by p53, and may therefore play a role in apoptosis or cancer development. In spite of the different biological functions, all six proteins demonstrate common structural characteristics typical of membrane proteins. In addition, homologues are identified in plants, fungi, and bacteria, demonstrating this superfamily to be generally occurring.