Free-form optimization of nanophotonic devices: from classical methods to deep learning

Nanophotonic devices have enabled microscopic control of light with an unprecedented spatial resolution by employing subwavelength optical elements that can strongly interact with incident waves. However, to date, most nanophotonic devices have been designed based on fixed-shape optical elements, and a large portion of their design potential has remained unexplored. It is only recently that free-form design schemes have been spotlighted in nanophotonics, offering routes to make a break from conventional design constraints and utilize the full design potential. In this review, we systematically overview the nascent yet rapidly growing field of free-form nanophotonic device design. We attempt to define the term “free-form” in the context of photonic device design, and survey different strategies for free-form optimization of nanophotonic devices spanning from classical methods, adjoint-based methods, to contemporary machine-learning-based approaches.

MODELING AND ANALYSIS OF PARAMETRIC OPTIMIZATION OF THE MASS OF A CLOSED PLANETARY MECHANISM FORMED BY TWO SIMPLE PLANETARY MECHANISMS OF JAMES

The mathematical model of estimation of a design mass of the closed planetary mechanism formed from two simple planetary mechanisms of James (mechanism of type ), taking into account their structural diagrams and design constraints, determined by the conditions of contact and bending strengths of external gearing of sun gears and satellites, is offered. A model is a dimensionless function (analogue of mass) of two variables – transmission relations of simple planetary mechanisms, and set of numerical parameters. As parameters of analogue of mass coefficients are chosen, characterizing the models of mass of gear wheels and carriers, structural and strength limitations of the external gearing of simple planetary mechanisms of the type , and also structure of these mechanisms. In the program Mathcad differential properties of the offered model and influence on position of minimum of analogue of mass are investigational depending on the numerical values of his parameters. Documents of the Mathcad program are presented that implement computer modeling of algorithms for parametric optimization of mass closed planetary mechanism, where the function of the analogue of the mass of the given mechanism is used as the objective function. A comparative analysis of minimizing the design mass of two kinematic schemes of planetary mechanisms is considered – closed planetary mechanism and in-line planetary of the type . Keywords: simple planetary mechanism of James, simple planetary mechanism type ; closed planetary mechanism; in-line planetary mechanism; mass of closed planetary mechanism; contact strength of gearing; bending strength of gearing; parametric optimization; parametric optimization of mass of planetary mechanism

Feasibility-Based Design Model For Road Vertical Alignment

Road vertical alignment design is a multi-objective design problem that needs to consider multiple constraints. Intelligent design based on optimization algorithms cannot wholly solve problems, such as multi-objective, uncertainty, and constraint dynamics. The article proposes a model of dynamically transforming design constraints into feasible regions as the design develops, to provide decision information before design actions rather than performing constraint evaluation after the design that reduces the empirical estimation. The design actions are divided into new design actions and modifying design actions, and corresponding feasible regions derived from constraints of design specifications and control elevations are established, respectively. Geometrical equations and program algorithms of feasible regions are described in the graphic environment, which is applied to the vertical alignment design to improve the design efficiency and decision-making level.

Polynomial fault detection filter design under adaptive event-triggered scheme via line-integral Lyapunov functions

This paper investigates the problem of polynomial fault detection filter design under an adaptive event-triggered scheme for continuous-time networked polynomial fuzzy model–based (PFMB) systems considering network transmission delays. The proposed adaptive polynomial event-triggered scheme is checked only at the sampling instant to eliminate the Zeno behavior as well as save the network bandwidth. With the consideration of the mismatched membership functions (MFs), the asynchronous problem between the physical plant and the polynomial fault detection filter (PFDF) is examined. A Lyapunov–Krasovskii (L-K) function is introduced to deal with the time delays caused by the network transmission and the zero-order holder (ZOH), and a proper line-integral Lyapunov function is also introduced to reduce the conservation of the design constraints, whose analytical procedure is rule-dependent. The design constraints are given in the form of sum of squares (SOS) to keep the PFMB fault detection system asymptotically stable with [Formula: see text] performance [Formula: see text]. Finally, an inverted pendulum example together with a numerical example is given to verify the effectiveness and superiority of the proposed scheme in terms of transfer rate and conservatism.

Effectiveness of different requirements checklists for novice designers

Working under constrained conditions can boost or kill creativity, depending on the nature of the constraints (organizational, personal or task-related). However, a design process without clearly identified constraints, which set the project objectives, could lead to inefficiencies and unfruitful iterations. Some of the most acknowledged procedures to support requirement definition are focused on the use of specific checklists. However, notwithstanding the importance of the task, little attention was dedicated to the verification of the effectiveness of these tools. In such a context, the paper presents an investigation aimed at assessing the performance of three checklists that exploit different strategies to elicit requirements. To that purpose, a sample of fifty engineering students was asked to use the checklists to define the requirements for a specific design case. The outcomes of the experiment were assessed according to well-acknowledged effectiveness metrics, i.e. quantity, operationality, validity, non-redundancy, and completeness. The result of the assessment highlights that checklists based on more general questions or abstract stimuli can better support novice designers in making explicit internally felt design constraints that can potentially lead to more innovative design.

Optimal Design of SRM for EV Application

Electric vehicles (EVs) need a wide speed and torque range for their reliable operation and working. Switched reluctance motors (SRMs) offer several advantages like high life cycle, meager cost, simple construction, robustness, good speed characteristics, and fault-tolerance, making it a suitable motor drive for EV application. The selection of independent variables like dimensions, winding turns, make materials, the number of slots, and the shape of rotor and stator teeth is a cumbersome task as SRM performance is mainly dependent on these parameters. This paper describes the methodology for selecting these independent variables by evaluating the SRM performance for different shapes of rotor and stator teeth, with the different stator and rotor materials, by taking all the design constraints like winding resistance, turns, and the number of slots. The EV drive performance is evaluated for the chosen independent variables and analyzed using JMAG software for determining the efficiency, Torque, and speed responses for comparison and analysis to get the optimal design constraints of the independent variables of SRM.

Genetic Algorithm-Driven Surface-Enhanced Raman Spectroscopy Substrate Optimization

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive and molecule-specific detection technique that uses surface plasmon resonances to enhance Raman scattering from analytes. In SERS system design, the substrates must have minimal or no background at the incident laser wavelength and large Raman signal enhancement via plasmonic confinement and grating modes over large areas (i.e., squared millimeters). These requirements impose many competing design constraints that make exhaustive parametric computational optimization of SERS substrates prohibitively time consuming. Here, we demonstrate a genetic-algorithm (GA)-based optimization method for SERS substrates to achieve strong electric field localization over wide areas for reconfigurable and programmable photonic SERS sensors. We analyzed the GA parameters and tuned them for SERS substrate optimization in detail. We experimentally validated the model results by fabricating the predicted nanostructures using electron beam lithography. The experimental Raman spectrum signal enhancements of the optimized SERS substrates validated the model predictions and enabled the generation of a detailed Raman profile of methylene blue fluorescence dye. The GA and its optimization shown here could pave the way for photonic chips and components with arbitrary design constraints, wavelength bands, and performance targets.