A new class of electronic materials derived predominantly from natural foods and foodstuffs, with minimal levels of inorganic materials, is developed and studied to build edible electronic components and devices compatible with the gastrointestinal (GI) tract. A “toolkit” of food‐based electronic materials, fabrication schemes, basic device components, and functional devices with integrated sensing and wireless signal transmission is reported. These new materials establish the possibility to extend GI electronic devices beyond the ingested nondegradable systems to edible and nutritive systems, in which the described materials may be ingested and assimilated as metabolized nutrients. This study represents a new era of edible electronics with the potential to revolutionize modern biomedical technologies and devices.

A systematic and rational approach is presented for the consideration of uncertainty in rotordynamics systems, i.e., in rotor mass and gyroscopic matrices, stiffness matrix, and bearing coefficients. The approach is based on the nonparametric stochastic modeling technique, which permits the consideration of both data and modeling uncertainty. The former is induced by a lack of exact knowledge of properties such as density, Young’s modulus, etc. The latter occurs in the generation of the computational model from the physical structure as some of its features are invariably ignored, e.g., small anisotropies, or approximately represented, e.g., detailed meshing of gears. The nonparametric stochastic modeling approach, which is briefly reviewed first, introduces uncertainty in reduced order models through the randomization of their system matrices (e.g., stiffness, mass, and damping matrices of nonrotating structural dynamic systems). Here, this methodology is extended to permit the consideration of uncertainty in symmetric and asymmetric rotor dynamic systems. More specifically, uncertainties on the rotor stiffness (stiffness matrix) and/or mass properties (mass and gyroscopic matrices) are first introduced that maintain the symmetry of the rotor. The generalization of these concepts to uncertainty in the bearing coefficients is achieved next. Finally, the consideration of uncertainty in asymmetric rotors is described in detail.

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In the first part of this series, a comprehensive methodology was proposed for the consideration of uncertainty in rotordynamic systems. This second part focuses on the application of this approach to a simple, yet representative, symmetric rotor supported by two journal bearings exhibiting linear, asymmetric properties. The effects of uncertainty in rotor properties (i.e., mass, gyroscopic, and stiffness matrices) that maintain the symmetry of the rotor are first considered. The parameter λ that specifies the level of uncertainty in the simulation of stiffness and mass uncertain properties (the latter with algorithm I) is obtained by imposing a standard deviation of the first nonzero natural frequency of the free nonrotating rotor. Then, the effects of these uncertainties on the Campbell diagram, eigenvalues and eigenvectors of the rotating rotor on its bearings, forced unbalance response, and oil whip instability threshold are predicted and discussed. A similar effort is also carried out for uncertainties in the bearing stiffness and damping matrices. Next, uncertainties that violate the asymmetry of the present rotor are considered to exemplify the simulation of uncertain asymmetric rotors. A comparison of the effects of symmetric and asymmetric uncertainties on the eigenvalues and eigenvectors of the rotating rotor on symmetric bearings is finally performed to provide a first perspective on the importance of uncertainty-born asymmetry in the response of rotordynamic systems.

This paper focuses on the optimization of intentional mistuning patterns for the reduction of the sensitivity of the forced response ofbladed disks to random mistuning. Intentional mistuning is achieved here by using two different blade types (denoted as A and B) around the disk. It is thus desired to find the arrangement of these A and B blades (AIB pattern) that leads to the smallest 99th percentile of the amplitude of blade response in the presence of random mistuning. It is first demonstrated that there usually is a large number of local minima and further that the cost of a function evaluation is high. Accordingly, two novel, dedicated optimization algorithms are formulated and validated to address this specific problem. Both algorithms proceed in a two-step fashion. The first step, which consists of an optimization in a reduced space, leads to a series of good initial guesses. A local search from these initial guesses forms the second step of the methods. A detailed validation effort of this new procedure was next achieved on a single-degree-of-freedomper-blade model, a reduced order model of a blisk, and that of an impeller considered in an earlier study. In all validation cases, the two novel algorithms were found to converge to the global optimum or vei-y close to it at a small computational cost. Finally, the results of these optimization efforts further demonstrate the value of intentional mistuning to increase the robustness of bladed disks to random mistuning.