Systematic Design Methodology Research Articles

Design Optimization of a Mooring System for an Offshore Aquaculture Platform

In the present paper, the mooring system of an offshore aquaculture platform is designed and optimized, applying a shallow water mooring system design methodology which combines the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and the cable–platform coupled model. One mooring design is first given using the proposed methodology. Two reference mooring systems are modified based on an NSGA-II design, and AIP criteria and expertise. The hydrodynamic performance of the offshore aquaculture platform with these three mooring systems is compared via use of a potential flow time–domain numerical simulation. A physical model-scale experiment is carried out to validate the numerical coupled model. Both numerical and experimental results confirm the effectiveness of present model. The comparative analysis shows that the mooring system designed using NSGA-II can provide a relative radical solution compared to the other two mooring designs when considering a limited budget.

Inductance Interpolation-Based Fast Design and Optimization Methodology for Wireless Power Transfer Systems

Inductance Interpolation-Based Fast Design and Optimization Methodology for Wireless Power Transfer Systems

Social system design methodology for transitioning to a new social structure - a holistic urban living lab approach to the well-being city.

In recent years, along with the rise of new technologies such as AI, IoT, and Bigdata, there has been much discussion replacing entire cities with smart cities. These discussions have given rise to questions about what kind of society should be realized, and keywords such as well-being and sustainability are attracting attention. In this context, how concretely can we transform our current cities into new social structures? Social system design methodology is, in this paper, intend to achieve a comprehensive transition to a new social system, rather than overcoming individual social problems. In Japan, approaches to transforming society, such as elections and social activism, are not fully functional. Transitioning to a new social structure requires critiques from inside together with the presentation of concrete activities. We propose a systematized social system design methodology that aims at a principled transition; it is based on analyses of a series of practices developed in Omuta City, Fukuoka Prefecture in Japan. The methodology proposes a new way of perceiving social systems, practitioner attitude, and a practical design process. It also suggests that existing social system concepts create fundamental problems that lead to discomfort for practitioners, that clarifying existing concepts through policy background analysis can lead to a new view of social system concepts, and that bottom-up practices that realize these new concepts can begin to transform social systems. In order to confirm the versatility of this methodology, two case studies involving care prevention and the work of persons with disabilities are analyzed.

Particle Swarm Optimization Method for Stand-Alone Photovoltaic System Reliability and Cost Evaluation Based on Monte Carlo Simulation

In rural regions with limited access to the power grid, self-reliance for electricity generation is paramount. This study focuses on enhancing the design of stand-alone photovoltaic installations (SAPV) to replace conventional fuel generators thanks to the decreasing costs of PV modules and batteries. This study presents a particle swarm optimization (PSO) method for the reliable and cost-effective sizing of SAPV systems. The proposed method considers the variability of PV generation and domestic demand and optimizes the system design to minimize the total cost of ownership while ensuring a high level of reliability. The results show that for the PSO method with 500 iterations, the error is around 2%, and the simulation time is approximately 2.25 s. Moreover, the PSO method allows a much lower number of iterations to be used in the Monte Carlo simulation, with a total of 100 iterations used to obtain the averaged results. The optimization results, encompassing installed power, battery capacity, reliability, and annual costs, reveal the effectiveness of our approach. Notably, our discretized PSO algorithm converges, yielding specific parameters like 9900 W of installed power and a battery configuration of five 3550 Wh units for the case study under consideration. In summary, our work presents an efficient SAPV system design methodology supported by concrete numerical outcomes, considering supply reliability and installation and operational costs.

From Biomimicking to Bioinspired Design of Electrocatalysts for CO2 Reduction to C1 Products.

The electrochemical reduction of CO2 (CO2 RR) is a promising approach to maintain a carbon cycle balance and produce value-added chemicals. However, CO2 RR technology is far from mature, since the conventional CO2 RR electrocatalysts suffer from low activity (leading to currents <10 mA cm-2 in an H-cell), stability (<120 h), and selectivity. Hence, they cannot meet the requirements for commercial applications (>200 mA cm-2 , >8000 h, >90 % selectivity). Significant improvements are possible by taking inspiration from nature, considering biological organisms that efficiently catalyze the CO2 to various products. In this minireview, we present recent examples of enzyme-inspired and enzyme-mimicking CO2 RR electrocatalysts enabling the production of C1 products with high faradaic efficiency (FE). At present, these designs do not typically follow a methodical approach, but rather focus on isolated features of biological systems. To achieve disruptive change, we advocate a systematic design methodology that leverages fundamental mechanisms associated with desired properties in nature and adapts them to the context of engineering applications.

From Biomimicking to Bioinspired Design of Electrocatalysts for CO2 Reduction to C1 Products

AbstractThe electrochemical reduction of CO2 (CO2RR) is a promising approach to maintain a carbon cycle balance and produce value‐added chemicals. However, CO2RR technology is far from mature, since the conventional CO2RR electrocatalysts suffer from low activity (leading to currents &lt;10 mA cm−2 in an H‐cell), stability (&lt;120 h), and selectivity. Hence, they cannot meet the requirements for commercial applications (&gt;200 mA cm−2, &gt;8000 h, &gt;90 % selectivity). Significant improvements are possible by taking inspiration from nature, considering biological organisms that efficiently catalyze the CO2 to various products. In this minireview, we present recent examples of enzyme‐inspired and enzyme‐mimicking CO2RR electrocatalysts enabling the production of C1 products with high faradaic efficiency (FE). At present, these designs do not typically follow a methodical approach, but rather focus on isolated features of biological systems. To achieve disruptive change, we advocate a systematic design methodology that leverages fundamental mechanisms associated with desired properties in nature and adapts them to the context of engineering applications.

Backstepping speed controller design for a multi-phase permanent magnet synchronous motor drive

This paper deals with the synthesis of a speed control strategy for a six-phase permanent magnet synchronous motor (PMSM) drive based on backstepping controller (BC). The Backstepping control is a systematic and recursive design methodology for nonlinear feedback control. The results demonstrate that backstepping controller has the advantage of rapid response, no overshoot and stability compared with PI controller.

A hybrid approach to system verification in early design for complex mechatronic systems based on formal functional semantics

Model-based systems engineering (MBSE) has been adopted as a mainstream design methodology for complex mechatronic systems. According to this paradigm, structured models, typically represented in SysML are used to describe the system of interest from various aspects. Among these models, the system behavior model is fundamental for the subsequent design and hence should be verified against system functions in the early design stage. However, due to the lack of formal semantics of the involved SysML models and software-physical hybrid characteristics of the mechatronic systems, it is not a trivial task to apply existing formal verification methods to solve this problem. In this study, a novel approach relying on hybrid functional semantics is proposed. First, this verification problem is formally defined based on an in-depth analysis of the architectures and traceability between the involved SysML models. Then, a graphical modeling language to represent the hybrid functional semantics in SysML is defined so that the function and behavior models can be enhanced and explicitly correlated by the formal semantics. Finally, based on the semantically enhanced models, the model verification problem is formally re-defined as a semantics verification problem and further divided into two sub-problems, i.e., continuous and discrete semantics verification problems, which are automatically solved by leveraging existing verification techniques including functional-effect compatibility check and symbolic model checking. A mobile robot is illustrated to show the effectiveness of the proposed approach.

High-Efficiency Circularly Polarized Phased Array Based on 5 μm-Thick Nematic Liquid Crystals: Design, Over-The-Air Calibration, and Experimental Validation

This paper presents a systematic investigation and demonstration of a K-band circularly polarized liquid-crystal-based phased array (LCPA), including the design, over-the-air (OTA) in-array calibration, and experimental validation. The LCPA contains 16 phase-shifting radiating channels, each consisting of a circularly polarized stacked patch antenna and a liquid-crystal-based phase shifter (LCPS) based on a loaded differential line structure. Thanks to its slow-wave properties, the LCPS exhibits a maximum phase-shifting range of more than 360° with a figure of merit of 78.3(° )·dB−1 based on a liquid crystal layer with a thickness of only 5 μm. Furthermore, an automatic OTA calibration based on a state ergodic method is proposed, which enables the extraction of the phase–voltage curve of every individual LCPA channel. The proposed LCPA is manufactured and characterized with a total profile of only 1.76 mm, experimentally demonstrating a scanned circularly polarized beam from −40° to +40° with a measured peak gain of 12.5 dBic and a scanning loss of less than 2.5 dB. The bandwidth of the LCPA, which satisfies the requirements of port reflection (|S11|) < −15 dB, an axial ratio (AR) < 3 dB, beam squinting < 3°, and a gain variation < 2.2 dB, spans from 25.5 to 26.0 GHz. The total efficiency is about 34%, which represents a new state of the art. The use of the demonstrated low-profile LCPA to support circularly polarized scanning beams, along with the systematic design and calibration methodology, holds potential promise for a variety of millimeter-wave applications.

Optical Design of an LCoS-Based 1 × 10 WSS with High Coupling Efficiency and Compact Light Paths

In the field of communication, the utilization of Liquid Crystal On Silicon (LCoS) in Wavelength Selective Switch (WSS) systems holds great promise. However, the lack of research on the optical path design of LCoS-based WSS makes it challenging to realize high-port-count and perfect performance with a compact structure. In this paper, the conceptual optical path design method of a compact LCoS-based 1 × 10 WSS system working in C-band (1529 nm–1568 nm) is proposed, where there exists 1 input port and 10 output ports in the same array. The optical powers in both the wavelength and deflection directions have been meticulously considered separately, while the polarization-independent structure has been designed novelty, which boost system compactness and lowers manufacturing costs. Finally, a high fiber-to-fiber coupling efficiency of an idealized system ranging from 95.07 to 99.18% with only five components is achieved. Furthermore, a brief tolerance analysis to demonstrate the instrumentation feasibility is also conducted and the additional losses that will be introduced by real experiments are discussed. Our work is pioneering in providing a more straightforward methodology and conceptual model for WSS system design and offering reference significant for high-port-count systems.

From theory to practice: Evaluating the thermodynamic design landscape of compressed air energy storage systems

Compressed air energy storage (CAES) systems offer significant potential as large-scale physical energy storage technologies. Given the increasing global emphasis on carbon reduction strategies and the rapid growth of renewable energy sources, CAES has garnered considerable attention. However, the optimal design of CAES systems presents challenges due to the intricate coupling of multiple parameters, complex physical processes, and highly variable operating conditions. This paper comprehensively reviews three key aspects related to CAES optimal design. Firstly, it examines system analysis and optimization methodologies. Secondly, it investigates the off-design characteristics of CAES systems. Lastly, it explores system design methodologies specifically addressing off-design operations. Notably, the corresponding-point methodology (CPM) is proposed as a means to provide clearer guidance for system improvements. Future research should aim to combine CPM with traditional methods to establish more efficient and intuitive system optimization approaches. Furthermore, the exploration of active off-design regulation strategies, including the integration of various adjustment methods and multistage combined regulation for CAES systems experiencing wide load fluctuations, requires further investigation. Novel CAES configurations that enable efficient off-design conditions should also be explored, despite the inherent complexities associated with regulation and control. Finally, a coupled design methodology based on off-design operation data and probabilistic-load factor analysis is presented. This paper provides valuable insights and guidance for the optimal design and study of CAES systems.

A methodology for subsea system design considering integrated production/injection modeling

A methodology for subsea system design considering integrated production/injection modeling

Methodology for energy management strategies design based on predictive control techniques for smart grids

This article focuses on the development of a general energy management system (EMS) design methodology using on model-based predictive control (MPC) for the control and management of microgrids. Different MPC-based EMS for microgrids have been defined in the literature; however, there is a lack of generality in the proposed that would facilitate adapting to new architectures, energy storage system technology, nature of the bus, application, or purpose. To fill this gap, a novel general formulation that is parameterizable, simple, easily interpretable, and reproducible in different microgrid architectures is presented. This is the result of the development of a novel methodology, which is also presented. It considers the state space formulation of the controller from the initial modelling phase, from the dynamics of the energy storage systems represented by their models to the subsequent definition of the optimisation problem. This is developed through the design of the general cost function and the formulation of constrains, by means of general guidelines and reference values. To evaluate the performance of the developed methodology, simulation tests were carried out for four different microgrid architectures, with different applications and objectives, also considering different generation conditions, demand profiles, and initial conditions. The results showed that, with some simple guidelines and regardless of the case study, the developed MPC controller design methodology can address the technical-economic optimisation problem associated with energy management in microgrids in an easy and intuitive way.

Purchasing, Sales and Inventory Information System Design at UD. Monza Collection

The information system is also one of the most important parts for companies in increasing productivity, both in obtaining information, processing, and using the information, especially for the benefit of the company. UD. Monza Collection is a form of business that is engaged in distributors for women's clothing such as shorts, leggings, tank tops, and others and then sells them wholesale. The problem with the store is that the store often has difficulty in knowing the amount of raw materials by the distribution staff quickly and the calculation of the number of finished goods by the warehouse staff who are very prone to errors, this will result in delays in distribution and sales activities. The system design methodology used is the System Development Life Cycle (SDLC) methodology. The design of the input system using Microsoft Visual Studio 2015, The design of the system output using Crystal Report and data storage using Microsoft SQL Server 2014. The result of this writing is a desktop design that makes it easy to find out the available stock and makes it easy to make the required reports quickly. So that the results of this information system design can help the store in managing information and computerized business processes.

Specifying task allocation in automotive wire harness assembly stations for Human-Robot Collaboration

Wire harness assembly is normally a manual assembly process that poses ergonomic challenges. As a consequence of the rapidly expanding electrification of vehicles and transportation systems, the demand for wire harnesses can be expected to grow radically, further increasing assembly operator challenges. Thus, automating this assembly process is highly prioritised by production engineers. The rapid development of industrial robot technology has enabled more human-robot collaboration possibilities, simplifying the automation of wire harness process tasks. However, successful automation applications involving humans require efficient and safe allocation of tasks between humans and technology. Unfortunately, present assembly system design methods may be obsolete and insufficient in light of the capabilities of emerging automation technologies such as collaborative robots. This paper presents a design and specification methodology for human-centred manufacturing systems and focuses on collaborative assembly operations in complex production systems. A case study on human-robot collaboration provides an application example from a wire-harness collaborative assembly process. The proposed design methodology combines hierarchical task analysis with assessments of cognitive and physical Levels of Automation (LoAc and LoAp). The assessments are then followed by evaluations of the Levels of human-robot Collaboration (LoC) and the Levels of operator Skill requirements (LoSr) respectively. A task allocation matrix supports the identification of possible combinations of automation and collaboration solutions for a human-centred and collaborative wire harness assembly process. System designers and integrators may utilise the design and specification methodology to identify the potential and extent of human-robot collaboration in collaborative manufacturing assembly operations.

Learning flat optics for extended depth of field microscopy imaging

Abstract Conventional microscopy systems have limited depth of field, which often necessitates depth scanning techniques hindered by light scattering. Various techniques have been developed to address this challenge, but they have limited extended depth of field (EDOF) capabilities. To overcome this challenge, this study proposes an end-to-end optimization framework for building a computational EDOF microscope that combines a 4f microscopy optical setup incorporating learned optics at the Fourier plane and a post-processing deblurring neural network. Utilizing the end-to-end differentiable model, we present a systematic design methodology for computational EDOF microscopy based on the specific visualization requirements of the sample under examination. In particular, we demonstrate that the metasurface optics provides key advantages for extreme EDOF imaging conditions, where the extended DOF range is well beyond what is demonstrated in state of the art, achieving superior EDOF performance.

Comparison and extension of advanced frequency domain non-active power decompositions

This research paper introduces new prospects in the field of power quality and energy transmission efficiency analysis and system design methodology through advanced frequency-domain power definitions. This proposal presents an improved extension of the power theory Currents’ Physical Components (CPC) by L.S. Czarnecki and compares its improvements with the CPC and an extension of the CPC by H. Lev-Ari. This proposal increases the resolution of physical phenomena reducing the power quality and hence contributes to its analysis and improvement. For this purpose, four additional non-active power components compared to the CPC are introduced. In contrast to the extension by H. Lev-Ari, these additional components are obtained from different definitions. In particular, the decomposition of the unbalance component into a spectral uniform and a spectral non-uniform component is novel to frequency-domain power definitions. As the CPC and its extension through H. Lev-Ari already decompose the collinear and shift components into spectral uniform and non-uniform components, the proposal for the unbalance components finally completes this structure. This yields a consistent and intuitive designation of physical phenomena related to spectral non-uniformity constituting as a concretization to the well-known distortion non-active power. Conclusive examples illustrate this improvement using the appertaining non-active power components.

A Design of Fuzzy Rule-Based Models With Data Privacy

One of the currently visible requirement of data analysis is to cope with data privacy requirements. The quest for privacy triggers design challenges in the construction of Machine Learning models. In this study, we propose a novel and systematic design methodology of fuzzy rule-based models completed in the following privacy-driven environment. Multidimensional data are available for model design in two different formats: those attributes that are privacy sensitive are provided at the higher non-numeric level of abstraction represented in the form of information granules while the remaining ones are available directly. It is shown that the granular manifestation of data becomes beneficial in the formation of the conditions of the rules whereas numeric attributes are available for the construction of the conclusions of the rules. The generic development scheme is discussed. Some generalization is introduced to cope with a number of data islands associated with corresponding data owners. It is shown that a formation of the data structure calls for a mechanism of collaborative clustering. A way of handling information granules at different levels of information granularity is discussed. Some illustrative examples are presented.

Design Methodology of Off-Grid PV Solar Powered Systems for Rural Areas in Ecuador

Renewable technologies are a modern, clean form of energy with a very low environmental impact. They can become a viable option for energy generation, especially in rural areas of Ecuador, where the scarce access to electricity service limits the development possibilities of these areas. Solar energy is the resource used by off grid photovoltaic generation systems, which are used exclusively in rural areas because the installation of the electrical grid is costly or technically complex. In the Matlab/Simulink environment, off grid photovoltaic systems have been designed, which are composed of an array of photovoltaic modules, charge controllers, storage systems and single-phase inverters that together will allow knowing the behavior of electric power generation through solar photovoltaic energy. In addition, a maximum power point tracking (MPPT) algorithm was developed to obtain the peak power of the photovoltaic array and a discrete integral proportional control was incorporated for the charging and discharging of the batteries. Finally, a sizing tool was designed and developed through Excel Macros and Visual Basic, which facilitated the input of the different parameters and the obtaining of the results for the implementation of the photovoltaic systems.

Topology Optimization Design of Resonant Structures Based on Antiresonance Eigenfrequency Matching Informed by Harmonic Analysis

Abstract In this article, we present a design methodology for resonant structures exhibiting particular dynamic responses by combining an eigenfrequency matching approach and a harmonic analysis-informed eigenmode identification strategy. This systematic design methodology, based on topology optimization, introduces a novel computationally efficient approach for 3D dynamic problems requiring antiresonances at specific target frequencies subject to specific harmonic loads. The optimization’s objective function minimizes the error between target antiresonance frequencies and the actual structure’s antiresonance eigenfrequencies, while the harmonic analysis-informed identification strategy compares harmonic displacement responses against eigenvectors using a modal assurance criterion, therefore ensuring an accurate recognition and selection of appropriate antiresonance eigenmodes used during the optimization process. At the same time, this method effectively prevents well-known problems in topology optimization of eigenfrequencies such as localized eigenmodes in low-density regions, eigenmodes switching order, and repeated eigenfrequencies. Additionally, our proposed localized eigenmode identification approach completely removes the spurious eigenmodes from the optimization problem by analyzing the eigenvectors’ response in low-density regions compared to high-density regions. The topology optimization problem is formulated with a density-based parametrization and solved with a gradient-based sequential linear programming method, including material interpolation models and topological filters. Two case studies demonstrate that the proposed design methodology successfully generates antiresonances at the desired target frequency subject to different harmonic loads, design domain dimensions, mesh discretization, or material properties.