Multiple Design Constraints Research Articles

Automatic Selection of Structure Parameters of Silicon on Insulator Lateral Power Device Using Bayesian Optimization

The selection of design structure parameters is a critical step for meeting the performance requirement for silicon on insulator (SOI) lateral power devices, especially when multiple design constraints are presented. In this letter, we propose a fully-automated structural design method for SOI lateral power device based on a Bayesian optimization (BO) framework. Given the design target characterized by breakdown voltage (BV) and on-resistance (Ron) specifications, the proposed approach searches for the optimal structure that can satisfy the constraints. The experimental results demonstrate that designs obtained from our optimization framework fall within 5% range from the desired specifications when evaluated using technology computer-aided design (TCAD) simulation, which proves the efficiency of the proposed approach. Besides, the efficiency of our proposed approach is reflected by its runtime which does not exceed 10 minutes for more than 70% of the cases. We believe that this modeling method can greatly accelerate the design exploration process of power devices for designers.

A new water wave optimization algorithm for satellite stability

Scientific and efficient design is the foundation requirement for stable operation of satellites. While a satellite is composed of a number of subsystems with independent functions. These subsystems interact with each other and related design variables are also coupled with each other. Thus, the overall design process needs to comprehensively weigh the relationship among multiple design objectives and design constraints of different subsystems, in order to obtain the optimal balance of the overall framework. Here we propose a novel Powell-Water Wave Optimization (POWWO) algorithm and apply it to the overall optimization design of earth observation satellites. Compared with previous works, this algorithm shows more excellent optimization properties, via combining the global and local search ability. Its effectiveness can also be supported by the well-known benchmarks and satellite optimization design experiments.

Enhancing Optimization Skills in Embedded Stream: Integrated Learning

Abstract Embedded system is one of the major focus areas in Electronics and Communication Engineering supported by relevant courses and projects at multiple levels. Students are well exposed in the embedded system verticals with industry supported labs, courses as well as industry guided projects for designing real time embedded systems. As embedded systems became bigger, intelligent and complex, millions of lines of code are to be optimized to meet system deadlines, fit into the available memory, and meet power requirements to achieve the desired functionality. Developing such embedded system, to meet multiple design constraints is a considerable challenge. In order to meet this challenge code optimization techniques at multiple levels are introduced in curriculum focusing on machine dependent and independent optimizations. Architecture specific machine dependent optimization techniques are addressed at basic courses like 8051 Microcontrollers and ARM processors, while machine dependent and independent optimization techniques are addressed at advanced courses like Real Time Embedded System and Course Projects which provides integrated experience. The courses are co-designed and delivered by both industry experts and in-house faculty. This exposure enables our students to be prepared for industry requirements and challenges, and has resulted in increased placements in embedded industries.

Design structure matrix‐based modularization approach for complex systems with multiple design constraints

AbstractDesigning a complex system generally requires its decomposition into smaller modular constituents for the ease of design, integration, operation, and future upgrades. Typically, system decomposition analysis is conducted using an abstract system model during the initial system design stage. The design structure matrix (DSM) has been a popular tool for abstract system modeling. In the DSM, systems are modeled and decomposed into modular configurations using published clustering algorithms. In this paper, we present a novel approach for system architecture decomposition and modularization based on the DSM, which can incorporate multiple design constraints into clustering algorithms. Two clustering algorithms are modified to accommodate the system design constraints. The modified algorithms are used to decompose a static inverter (SIV) of an electrical train into modular configurations that include various design constraints. Finally, the results and analysis of the SIV modularization using new modified clustering algorithms are presented.

Transformable Electronics Implantation in ROM for Anti-Reverse Engineering

The protection of intellectual property (IP) is increasingly critical for IP vendors in the semiconductor industry. Read Only Memories (ROMs) serve as important non-volatile memory in various hardware systems to store predefined data and programs, which is critical to IP protection. Its pre-determined layout pattern makes unauthorized data extraction through chip-level reverse engineering easy to carry out. Advanced reverse engineering techniques can physically disassemble the chip and derive the IPs precisely at a much lower cost than the value of IP design that chips carry. This invasive hardware attack obtaining information from IC chips always violates the IP rights of vendors. This paper proposes a new security mechanism implanted ROM design to address the vulnerability to reverse energy attacks. Irreversible via in ROM layout transform triggered by reverse engineering completely changes the electrical properties and the physical structure of ROMs that determine the stored data. Newly-created patten will significantly increase the difficulty of reverse engineering, even lead the attackers to another working function mode. Furthermore, to improve the effectiveness of the proposed technique, a systematic design method is developed targeting integrated circuits with multiple design constraints. Two widely used ROM scheme cases have been studied to test the design method and its effectiveness. Simulations have been conducted to demonstrate the capability of the proposed technique, which generates extremely large complexity for reverse engineering with manageable overhead. CCS Concepts: Security and privacy → Hardware reverse engineering; Hardware → Hard and soft IP

Deterministic Constrained Synthesis Technique for Conformal Aperiodic Linear Antenna Arrays—Part II: Applications

The aim of this paper is to illustrate the application of the antenna placement methodology introduced in Part I for the deterministic synthesis of general conformal aperiodic arrays subject to multiple concurrent design constraints on the relevant layout and excitation tapering, as it is typically the case in satellite communications and radar applications. Antenna mutual coupling is not considered in the developed methodology; hence, to assess the sensitivity of the design procedure to such nonideality, a dedicated investigation has been conducted using rigorous full-wave electromagnetic modeling and experimental measurements collected on physical prototypes. The obtained results demonstrate the effectiveness and versatility of the proposed array synthesis approach, even in operative scenarios in which a significant deviation from the desired antenna operation is observed.

A new multiscale topology optimization method for multiphase composite structures of frequency response with level sets

This paper proposes a new multiscale topology optimization method for the concurrent design of multiphase composite structures under a certain range of excitation frequencies. Distinguished from the existed studies, a general concurrent design formulation for the dynamic composite structures with more than two material phases is developed. The macrostructureand its microstructures with multiple material phases are optimized simultaneously. The integral of the dynamic compliances over an interval of frequencies is formulated as the optimization objective, so as to minimize the frequency response within the concerned excitation range. The effective properties of the multiphase microstructures are evaluated by using the numerical homogenization method, which actually serves as a link to bridge the macro and micro finite element analyses. Furthermore, to describe the boundaries of multiple material phases for the microstructure, a parametric color level set method (PCLSM) is developed by using an efficient interpolation scheme. In this way, L level set functions can represent at most 2L material phases without any overlaps. Moreover, these “color” level sets are updated by directly using the well-established gradient-based algorithm, which can greatly facilitate the proposed method to solve the multi-material optimizations with multiple design constraints. Several 2D and 3D numerical examples are used to demonstrate the effectiveness of the proposed method in the concurrent design of the dynamic composite structures under the excitation frequency ranges.

Optimization of Sparse Concentric Ring Arrays for Low Sidelobe

To lower the peak sidelobe level (PSLL) of sparse concentric ring arrays, a method with multiple design constraints that embed a function model into modified real genetic algorithm (MGA) and select the grid ring radii as optimization individual to synthesize sparse concentric ring arrays is proposed. The multiple constraints include the array aperture, the minimum element spacing, and the number of elements. The proposed method dynamically calculates the ratio of element on each ring, and it has a faster convergence rate than other algorithms. The MGA uses real number to code the optimization variable, and it reduces the complexity of coding and improves the search efficiency. Finally, the results demonstrate the accuracy and effectiveness of the algorithm.

Flexible Architectures for Cryptographic Algorithms — A Systematic Literature Review

Symmetric and asymmetric cryptographic algorithms are used for a secure transmission of data over an unsecured public channel. In order to use these algorithms in real-time applications, many flexible hardware architectures have been proposed and implemented with multiple design constraints. Therefore, a systematic study is required to analyze various implementation approaches. This paper has focused on the identification and classification of recent research practices pertaining to the flexible hardware implementation of cryptographic algorithms. We have used Systematic Literature Review (SLR) process to identify 51 research articles, published during 2008–2017. The identified researches have been classified according to three design approaches: (1) crypto processor, (2) crypto coprocessor and (3) multicore crypto processor. Consequently, a comparative analysis of various cryptographic algorithms in terms of flexibility, throughput, area, power and implementation technology has been presented. A comprehensive investigation of flexible architectures for implementing cryptographic algorithms facilitates researchers and designers of the domain to select an appropriate design approach for a particular algorithm and/or application according to their needs.

Ergonomics in Alternative Vehicle Design: Educating Students on the Practical Application of Anthropometric Data

An instructor taught students to use industry-standard anthropometric data sets by applying them to a long-term, alternative vehicle design project within industrial design courses. Students learned how to verify existing anthropometric data through physical testing using three-dimensional mock-ups to produce a robust, anthropometrically appropriate model that balances multiple design constraints. As a practical exercise, students examined aesthetics and control interface of the vehicle interior focusing on human interaction, optimum comfort, and control within the confined constraints of the aerodynamically optimized vehicle packaging. Ultimately, students gained insights into how to apply ergonomics to new, varied design challenges through these educational tasks.

A Chip-Level Anti-Reverse Engineering Technique

Protection of intellectual property (IP) is increasingly critical for IP vendors in the semiconductor industry. However, advanced reverse engineering techniques can physically disassemble the chip and derive the IPs at a much lower cost than the value of IP design that chips carry. This invasive hardware attack—obtaining information from IC chips—always violates the IP rights of vendors. The intent of this article is to present a chip-level reverse engineering resilient design technique. In the proposed technique, transformable interconnects enable an IC chip to maintain functioning in normal use and to transform its physical structure into another pattern when exposed to invasive attacks. The newly created pattern will significantly increase the difficulty of reverse engineering. Furthermore, to improve the effectiveness of the proposed technique, a systematic design method is developed targeting integrated circuits with multiple design constraints. Simulations have been conducted to demonstrate the capability of the proposed technique, which generates extremely large complexity for reverse engineering with manageable overhead.

Re-Thinking Design Methodology for Castings: 3D Sand-Printing and Topology Optimization

Additive manufacturing of sand molds and cores for metal castings, often called 3D sand-printing (3DSP), is an efficient “freeform” fabrication process that enables rapid production of sand metal castings. The ability to create highly complex molds and cores for advanced metal casting geometries via 3DSP provides unparalleled design freedom, particularly for low-volume production. However, there is a need to thoroughly understand the opportunities and restrictions of 3DSP in a systematic approach similar to well-established design guidelines for traditional sand casting. This study presents a knowledge-based design framework for 3DSP with the goal of developing new part design guidelines under such 3DSP framework. In particular, constrained topology optimization approach for the part redesign is developed for 3DSP. The presented design framework is compared with traditional sand-casting rules and validated through a case study on an existing metal component. Advantages of the developed 3DSP design framework are illustrated and validated through a case study where a 30% improvement in factor of safety and a 50% reduction in weight of a mechanical part is achieved. Other advantages, such as reduced lead time and production cost, are also observed. This research provides the first known investigation into systematic implementation of simultaneous constraints of 3DSP sand-casting rules mechanical strength through the integration of topology optimization and novel design rules to castings via 3D-printed molds. 3DSP also eliminates multiple design constraints in conventional mold-making and core-box fabrication. Findings from this study can be applied for a wide range of alloy systems, part geometries and loading conditions for sand castings in industrial applications.

A Systematic Optimization Design Method for Complex Mechatronic Products Design and Development

Designing a complex mechatronic product involves multiple design variables, objectives, constraints, and evaluation criteria as well as their nonlinearly coupled relationships. The design space can be very big consisting of many functional design parameters, structural design parameters, and behavioral design (or running performances) parameters. Given a big design space and inexplicit relations among them, how to design a product optimally in an optimization design process is a challenging research problem. In this paper, we propose a systematic optimization design method based on design space reduction and surrogate modelling techniques. This method firstly identifies key design parameters from a very big design space to reduce the design space, secondly uses the identified key design parameters to establish a system surrogate model based on data-driven modelling principles for optimization design, and thirdly utilizes the multiobjective optimization techniques to achieve an optimal design of a product in the reduced design space. This method has been tested with a high-speed train design. With comparison to others, the research results show that this method is practical and useful for optimally designing complex mechatronic products.

A multi-objective evolutionary artificial bee colony algorithm for optimizing network topology design

Abstract The topological design of a computer communication network is a well-known NP-hard problem. The problem complexity is further magnified by the presence of multiple design objectives and numerous design constraints. This paper presents a goal programming-based multi-objective artificial bee colony optimization (MOABC) algorithm to solve the problem of topological design of distributed local area networks (DLANs). Five design objectives are considered herein, namely, network reliability, network availability, average link utilization, monetary cost, and network delay. Goal programming (GP) is incorporated to aggregate the multiple design objectives into a single objective function. A modified version of MOABC, named as evolutionary multi-objective ABC (EMOABC) is also proposed which incorporates the characteristics of simulated evolution (SE) algorithm for improved local search. The effect of control parameters of MOABC is investigated. Comparison of EMOABC with MOABC and the standard ABC (SABC) shows better performance of EMOABC. Furthermore, a comparative analysis is also done with non-dominated sorting genetic algorithm II (NSGA-II), Pareto-dominance particle swarm optimization (PDPSO) algorithm and two recent variants of decomposition based multi-objective evolutionary algorithms, namely, MOEA/D-1 and MOEA/D-2. Results indicate that EMOABC demonstrated superior performance than all the other algorithms.

Comparative analysis on flexibility requirements of typical Cryogenic Transfer lines

The cryogenic systems and their applications; primarily in large Fusion devices, utilize multiple cryogen transfer lines of various sizes and complexities to transfer cryogenic fluids from plant to the various user/ applications. These transfer lines are composed of various critical sections i.e. tee section, elbows, flexible components etc. The mechanical sustainability (under failure circumstances) of these transfer lines are primary requirement for safe operation of the system and applications. The transfer lines need to be designed for multiple design constraints conditions like line layout, support locations and space restrictions. The transfer lines are subjected to single load and multiple load combinations, such as operational loads, seismic loads, leak in insulation vacuum loads etc. [1]. The analytical calculations and flexibility analysis using professional software are performed for the typical transfer lines without any flexible component, the results were analysed for functional and mechanical load conditions. The failure modes were identified along the critical sections. The same transfer line was then refurbished with the flexible components and analysed for failure modes. The flexible components provide additional flexibility to the transfer line system and make it safe. The results obtained from the analytical calculations were compared with those obtained from the flexibility analysis software calculations. The optimization of the flexible component’s size and selection was performed and components were selected to meet the design requirements as per code.

An Ontological Approach to Constraint-Based Design Case Adaptation

Designing tasks in case-based reasoning requires for the use of case adaptation due to its novelty characteristic. In this paper, constraint satisfaction is used to generate potential solutions for design case adaptation. An ontological approach is proposed to perform the inference process to satisfy the multiple design constraints. Domain application is the dietary menu planning for diabetics. Results show that the dietary menu planning designed by the proposed approach is better than the conventional approach. Both the physical and aesthetic constraints were satisfied by the proposed approach.

Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

PrimerDesign-M: a multiple-alignment based multiple-primer design tool for walking across variable genomes.

Analyses of entire viral genomes or mtDNA requires comprehensive design of many primers across their genomes. Furthermore, simultaneous optimization of several DNA primer design criteria may improve overall experimental efficiency and downstream bioinformatic processing. To achieve these goals, we developed PrimerDesign-M. It includes several options for multiple-primer design, allowing researchers to efficiently design walking primers that cover long DNA targets, such as entire HIV-1 genomes, and that optimizes primers simultaneously informed by genetic diversity in multiple alignments and experimental design constraints given by the user. PrimerDesign-M can also design primers that include DNA barcodes and minimize primer dimerization. PrimerDesign-M finds optimal primers for highly variable DNA targets and facilitates design flexibility by suggesting alternative designs to adapt to experimental conditions. PrimerDesign-M is available as a webtool at http://www.hiv.lanl.gov/content/sequence/PRIMER_DESIGN/primer_design.html tkl@lanl.gov or seq-info@lanl.gov.

Time-domain dynamic drift optimisation of tall buildings subject to stochastic wind excitation

Wind-resistant design of tall buildings has been traditionally treated using the equivalent static load approach. In order to account for the uncertainties in random wind excitation, it is necessary to develop a comprehensive and reliable dynamic optimisation technique in the time domain. The optimal lateral stiffness design problem of wind-excited tall buildings consists of (1) identifying the critical dynamic drift response in the time domain and (2) searching for the optimal distribution of element stiffness of the building subject to multiple drift design constraints. The critical time-history drift constraints of a wind-excited building are first treated by the worst-case formulation and then explicitly expressed in terms of element sizing variables using the principle of virtual work. The extreme value distribution and the Gaussian assumption are employed to formulate and simplify the probabilistic drift constraints, which are explicitly considered in the dynamic optimisation problem. The system reliability associated with the interstory drift is estimated approximately by the bound approach to ensure that the most cost-efficient solution also attains an acceptable reliability level. A full-scale 45-story building example under wind tunnel derived time history wind loading is presented to illustrate the effectiveness and practicality of the reliability-based dynamic optimisation technique.

Frequency response design of uncertain systems using performance indices and meta-models

Abstract Systems that are operated near their resonance frequencies experience vibrations that can lead to impaired performance, overstressing, fatigue fracture and adverse human reactions. Frequency response (FR) analysis can be invoked to mitigate the effects. When components of a system are described by random variables, modal frequencies and modal shapes, or, amplitudes and phases, are also random variables and the frequency response (FR) design of the system becomes more complex since it requires the solution of a frequency-variant probability problem. This paper presents a methodology to provide the frequency response design of uncertain systems using a transfer function approach. The methodology is found to be robust, expandable and flexible and can be applied to multi-disciplinary systems with n-dof and multiple design constraints. The novelty of the approach is the creation of a frequency-invariant probability problem through: (a) the discretization of the frequency band of interest into multiple contiguous point frequencies, (b) the introduction of new performance indices that measure the probability of success over the entire frequency band, and (c) the introduction of explicit meta-models to provide sufficiently fast probability evaluations through Monte Carlo simulation. The key to the performance indices are limit-state functions formed at all discrete, contiguous, frequencies. Each limit-state function establishes a conformance region in terms of the random design variables. The probabilities of the conformance regions are correctly combined to provide a single series-system index to be maximized by adjusting distribution parameters. The simple explicit meta-model is based on Kriging and performance measures at arbitrary design sets are efficiently calculated. Error analysis suggests ways to predict and control the errors with regards to meta-model fitting and probability calculations and so the method appears sufficiently accurate for engineering applications. The proposed methodology has applications in numerous areas such as electrical filters and structural mechanics – all with n-dof and multiple responses. The Performance indices can be evaluated at any frequency over any number of frequency ranges. A case study of a vibration absorber mechanism shows how the new methodology provides an improved and timely design with controllable accuracy when compared with previous proposals that employed modal frequencies.