Final Design Solution Research Articles

Research on Bionic Design of Packaging Forms for Snacks in Fishing Villages

This article aims to explore the bionic design of the packaging form of snacks in fishing village. Taking Quanzhou xunpu village as an example, through the in-depth understanding of the culture and natural environment of the fishing village, as well as the application of the principle of bionics, a snack package with bionic morphology is designed in line with the local characteristics of XunPu Village and the marine culture. The research combines the analysis of the morphological characteristics of marine organisms such as oysters, shells and fishes, and combines these characteristics with the traditional cultural background of the characteristic snacks of the fishing village to design a new type of packaging scheme that meets the requirements of aesthetics, functionality and sustainability. Through fieldwork research and internet data collection, and research and analysis were carried out. The final design solution is not only artistic and culturally expressive, but also considers the impact of packaging on the environment and enhances the market competitiveness of the product and consumer experience. Future research can further explore the application of bionic design in packaging and its potential in promoting sustainable development and cultural heritage.

Early Marine Systems' Design – Cracking the wicked problem - The case of a novel biomass harvesting vessel

Several IMDC contributions have argued for a better approach to capture stakeholders' expectations in vessel newbuilding projects' execution. The appropriate processes of requirements elucidation are, however, often forgotten or insufficiently handled in traditional ship design and customer-designer settings. Such situations most often reveal a situation in which both "tamed" and "wicked" problems are addressed and must be dealt with properly and effectively at the earliest stage of the process. This paper shows how such problems can be addressed by using the existing multidisciplinary methodology. A practical approach consisting of a set of methods, tools, and work processes integrated into the Accelerated Business Development (ABD) approach is applied to a specific use case, a next-generation factory stern trawler development. A detailed step-by-step story of the early vessel design process – requirements elucidation in parallel with concept design solution development – is outlined following a narrative approach. The process being described covers how necessary support information, stakeholders' expectations identification, business[1]related analyses, specific design layout, onboard comfort, and fish process handling and storage are dealt with effectively and efficiently. This case study exemplifies specific solutions to better handle particularly wicked problem situations, but also tamed problems are addressed systemically. The paper concludes by showing how a final ship design solution can look like and consequently be prepared for and to be built. The handover process and documentation from requirements capture and concept design solution development to further basic design activities are highlighted. The case vessel at hand won the prestigious “ship-of-the-year” award in Norway in 2023. The paper critically discusses what are likely to be the most important factors leading to this outcome.

A near-optimum multi-objective optimization approach for structural design

Multi-objective design optimization problems offer a set of solution alternatives within a Pareto-front. In structural design, the design variables are typically the section properties. The outcomes of these design variables are usually used in selecting standard sections. However, the properties of the selected standard sections normally have different values from the determined design variables. Accordingly, the values of the objective functions for these solutions will change after selecting standard sections. This change may be different among these solutions. Thus far, only Pareto-optimal solutions have been standardized in the literature. The effects of the inclusion of non-Pareto solutions in the standardization process have never been examined. In this paper, the differences between including the near-optimal solutions and not including them in the final structural design optimization set are explored. The paper investigates the impact of selecting standard sections on both Pareto-front solutions and near-optimal solutions, and it studies the importance of keeping track of the near-optimal solutions. A modified version of a multiple-objective particle swarm optimization method, enhanced with a proposed computationally efficient section standardization algorithm, is used to solve multi-objective system-reliability design optimization problems. The concepts of the paper are applied to examples of bridge structures. The results demonstrate the efficiency of the proposed technique in capturing final design solutions that would have been otherwise missed due to standardization.

Robust optimization design method for structural reliability based on active-learning MPA-BP neural network

PurposeMechanical products usually require deterministic finite element analysis in the design phase to determine whether their structures meet the requirements. However, deterministic design ignores the influence of uncertainties in the design and manufacturing process of mechanical products, leading to the problem of a lack of design safety or excessive redundancy in the design. In order to improve the accuracy and rationality of the design results, a robust design method for structural reliability based on an active-learning marine predator algorithm (MPA)–backpropagation (BP) neural network is proposed.Design/methodology/approachThe MPA was used to obtain the optimal weights and thresholds of a BP neural network, and an active-learning function applicable to neural networks was proposed to efficiently improve the prediction performance of the BP neural network. On this basis, a robust optimization design method for mechanical product reliability based on the active-learning MPA-BP model was proposed. Random moving quadrilateral sampling was used to obtain the sample points required for training and testing of the neural network, and the reliability sensitivity corresponding to each sample point was calculated by subset simulated significant sampling (SSIS). The total mass of the mechanical product and the structural reliability sensitivity of the trained active-learning MPA-BP model output were taken as the optimization objectives, and a multi-objective reliability-robust optimization design model was constructed, which was solved by the second-generation non-dominated ranking genetic algorithm (NSGA-II). Then, the dominance function was used in the obtained Pareto solution set to make a dominance-seeking decision to obtain the final reliability-robust optimization design solution. The feasibility of the proposed method was verified by a reliability-robust optimization design example of the bogie frame.FindingsThe prediction error of the active-learning MPA-BP neural network was smaller than those of the particle swarm optimization (PSO)-BP, marine predator algorithm (MPA)-BP and genetic algorithm (GA)-BP neural networks under the same basic parameter settings of the algorithm, which indicated that the improvement strategy proposed in this paper improved the prediction accuracy of the BP neural network. To ensure the reliability of the bogie frame, the reliability sensitivity and total mass of the bogie frame were reduced, which not only realized the lightweight design of the bogie frame, but also improved the reliability and robustness of the bogie.Originality/valueThe MPA algorithm with a higher optimization efficiency was introduced to find the weights and thresholds of the BP neural network. A new active-learning function was proposed to improve the prediction accuracy of the MPA-BP neural network.

Multi-criteria decision making for adaptive façade optimal design in varied climates: Energy, daylight, occupants’ comfort, and outdoor view analysis

Adaptive façades can enhance interior environmental quality and reduce building energy expenditure. To this end, counterbalancing numerous objectives must be considered during the early stage. However, there remain challenges in this high-performance access, leading to difficulties in obtaining the final design solution. Therefore, this study aims to establish a robust design decision-making process for adaptive façade systems in actual commercial building scales. Firstly, the parametric simulation was implemented in varied climates, simultaneously integrating daylight, energy, and occupants' view analysis. Five comprehensive objectives of maximising daylighting and view quality whilst minimising energy use, thermal discomfort, and visual discomfort were assessed, in which the most challenging criterion, outdoor view, was built precisely upon three all-inclusive facets: view context, view access, and view clarity. Then, the robust multi-criteria decision-making framework was applied to determine the unique optimal design for each selected region with preferences sensitivity analysis. Simulation results revealed that climatic conditions, materials, and configurations significantly impact adaptive façade performance. Meanwhile, optimal design results showed that building energy can save as much as 17% compared to the average design values. Although daylighting and outdoor view criteria meet current building standards, it suggested proper architectural layouts to accomplish the most occupants’ comfort. • The parametric simulation was integrated for adaptive façades in varied climates. • Maximising daylight and view whilst minimising energy use and occupants' discomfort. • The proposed outdoor view factor comprised view context, access, and clarity. • Multi-criteria decision making was investigated by preferences sensitivity analysis. • The optimal designs found complied with current building performance standards.

Ideal Flow Design of Plane-Strain Bending Driven by Springback

The present paper is concerned with the design of the plane-strain bending of wide sheets driven by the sheet’s geometric shape after unloading. The solution is based on the ideal flow theory. It determines the loading path (the dependence between the dimensionless bending moment and the dimensionless tensile force) that produces the desirable shape. The ideal flow theory is valid for the rigid perfectly plastic material model. A method proposed in the literature combines a rigid plastic solution at loading and an elastic solution for springback. The final design solution is practically analytical. A numerical method is only necessary to solve a system of transcendental equations. An illustrative example is provided. This example shows that, in some cases, it is sufficient to use the solution at loading to determine an accurate loading path that produces the desirable sheet’s shape after springback.

Energy performance-oriented design candidate selection approach for additive manufacturing using toolpath length comparison method

To ensure environmental benefits of additive manufacturing (AM), the energy performance should be optimized in the product design for AM (DfAM). We are proposing a new approach to select the design candidate (DC) for AM with the highest energy performance. In the first stage, multiple DCs are generated using topology optimization. In the second stage, the energy performance of each DC is evaluated based on the Toolpath-Length-Comparison (ToPaLC) method, in which the toolpath lengths of all DCs are calculated and compared. The candidate with the minimum path length is selected as the final design solution with the highest energy performance.

Digital optimization of car’s hinged components

The purpose of this work is to reduce the weight of the car’s hinged structures (front and rear doors, tailgate and lock reinforcements) by using various types of optimization which involve removing material, changing thicknesses, and topography from parts (topology, topography, parameter and multivariate) as well as the interpretation of optimization results for specific types of production while maintaining the rigidity and strength characteristics. This technique is necessary to reduce the time for product development and reduce the cost of manufacturing parts. This study addressed the issue of the maximum possible weight reduction while meeting all the requirements (strength calculations, stiffness calculations, modal analysis, analysis of resistance to external loads, local rigidity of the door attachment points - strength loadcases, stiffness loadcases, modal, denting, IPI) and technological limitations (Envelope requirements, casting technology). The final design solution was required to contain visible changes from the original structure, meet performance requirements, and obtain a feasibility study from the production department.

A method of shaping an energy-efficient building envelope based on natural patterns in order to achieve save of energy

This article aims to present an innovative way of designing objects called A method of shaping an energy-efficient building envelope based on natural patterns. The method uses currently available technologies in an unusual way. Digital photogrammetry data are inserted into a process of designing envelope structure of future objects. In the process of construction, this method counts on the use of all the advantages of 3D printing technology. This combination of the use of relatively innovative technologies in the process of design and construction of buildings opens up new possibilities for the design of the building envelope. Consequently, new building envelope shaping options create space for more efficient use of the energy savings associated with the building envelope shape as a building shape factor. The final design solution of the proposed building takes inspiration directly from the environment in which it is to be situated. Final design takes inspiration of its shape from the environment in which it will be built as a future object. As a result, the building works harmoniously and in accordance with the environment in which it was designed. This creates a pleasant ecological environment for its inhabitants and the surrounding area.

Efficient Surrogate Modeling and Design Optimization of Compact Integrated On-Chip Inductors Based on Multi-Fidelity EM Simulation Models

High-performance and small-size on-chip inductors play a critical role in contemporary radio-frequency integrated circuits. This work presents a reliable surrogate modeling technique combining low-fidelity EM simulation models, response surface approximations based on kriging interpolation, and space mapping technology. The reported method is useful for the development of broadband and highly accurate data-driven models of integrated inductors within a practical timeframe, especially in terms of the computational expense of training data acquisition. Application of the constructed surrogate model for rapid design optimization of a compact on-chip inductor is demonstrated. The optimized EM-validated design solution can be reached at a low computational cost, which is a considerable improvement over existing approaches. In addition, this work provides a description and illustrates the usefulness of a multi-fidelity design optimization method incorporating EM computational models of graduated complexity and local polynomial approximations managed by an output space mapping optimization framework. As shown by the application example, the final design solution is obtained at the cost of a few high-fidelity EM simulations of a small-size integrated coil. A supplementary description of variable-fidelity EM computational models and a trade-off between model accuracy and its processing time complements the work.

Multi-level performance-based design optimisation of steel frames with nonlinear viscous dampers

This paper presents a practical multi-level performance-based optimisation method of nonlinear viscous dampers (NVDs) for seismic retrofit of existing substandard steel frames. A Maxwell model is adopted to simulate the behaviour of the combined damper-supporting brace system, with a fractional power-law force–velocity relationship for the NVDs, while a distributed-plasticity fibre-based section approach is used to model the beam-column members thus incorporating the nonlinearity of the parent steel frame in the design process. The optimum height-wise distribution of the damping coefficients of NVDs satisfying given performance requirements is identified via a uniform damage distribution (UDD) design philosophy. The efficiency of the proposed multi-level performance-based design optimisation is illustrated through nonlinear time-history analysis of 3-, 7- and 12-storey steel frames under both artificial and natural spectrum-compatible earthquakes. Sensitivity analysis is performed to investigate the effects of initial height-wise damping distribution, convergence factor and uncertainty in design ground-motion prediction on the optimisation strategy. The efficiency of the final optimum design solution is also investigated by using drift-based, velocity-based, and energy-based UDD approaches to identify the most efficient performance index parameter for optimisation purposes. It is found that regardless of the selected performance parameter, the optimum damping distribution identified by the proposed methodology leads to frames exhibiting lower maximum inter-storey drift, local damage (maximum plastic rotation) and global damage index compared to an equal-cost uniform damping distribution. However, using drift-based UDD approach generally results in a better seismic performance. It is shown that the proposed UDD optimisation method can be efficiently used to satisfy multiple performance objectives at different intensity levels of the earthquake excitation, in line with performance-based design recommendations of current seismic codes. The proposed method is easy to implement for practical design purposes and represents a simple yet efficient tool for optimum seismic retrofit of steel frames with NVDs.

Fatigue Behavior of Metallic Components Obtained by Topology Optimization for Additive Manufacturing

The main goal of the present research is to propose an integrated methodology to address the fatigue performance of topology optimized components, produced by additive manufacturing. The main steps of the component design will be presented, specially the methods and parameters applied to the topology optimization and the post-smoothing process. The SIMP method was applied in order to obtain a lighter component and a suitable stiffness for the desired application. In addition, since residual stresses are intrinsic to every metallic additive manufacturing process, the influence of those stresses will be also analyzed. The Laser Powder Bed Fusion was numerically simulated aiming at evaluating the residual stresses the workpiece during the manufacturing process and to investigate how they could influence the fatigue behavior of the optimized component. The effect of the built orientation of the workpiece on the residual stresses at some selected potential critical points are evaluated. The final design solution presented a stiffness/volume ratio nearly 6 times higher when compared to the initial geometry. By choosing the built orientation, it is possible impact favorably in the fatigue life of the component.

Tower structure optimization through finite element analyses

In this study the objective is to obtain an optimal configuration for an antenna lattice tower which has an imposed height of 30 m. For this purpose, a variable geometric model which considers specific working parameters is created, and a 3D finite element (FE) model is generated by using beam and shell elements for an optimization study. The 3D FE analysis is updated automatically for each variant of the geometric model. The response surface methodology (RSM) is used together with the central composite design (CCD) approach as to optimize the response of the lattice tower. The model of the tower is subject to static and dynamic loadings, including earthquake analysis. A response spectrum analysis based on Rosenblueth's Double Sum Combination (ROSE) is performed because the natural frequencies resulting from the modal analysis have close values. The optimization solution algorithm used for the tower optimization is the nonlinear programming by quadratic Lagrangean (NLPQL), which is based on the gradient algorithm for models with only one objective function and several optimization restrictions. Out of three final candidate design solutions the one which gives the minimum mass is proposed.

Projecting learner engagement in remote contexts using empathic design.

This paper is in response to the manuscript entitled “Empathic design: Imagining the cognitive and emotional learner experience” (Tracey and Hutchinson in Educ Technol Res Dev 67(5):1259–1272, 2019) from a research perspective. The original manuscript provides a theoretical and empirical foundation of an instructional design approach—empathic design—where designers, during the design process, predict how learners would feel while engaging in the final design solution. Empathic design has significant implications in the “shift to digital” during the pandemic. That is, when designing the remote learning experience, instructional designers need to project into the remote contexts and predict learners’ engagement experiences in these contexts. To address the “shift to digital” remote learning, empathic design needs to be extended with two important considerations, including learners’ engagement and the context in which engagement occurs. This paper discusses how empathic design can be applied to consider four types of engagement (i.e., behavioral, cognitive, affective, and social engagement) and three contextual features (e.g., physical environment, technological, and social features) in order to best support learner experiences in the “shift to digital” remote learning during the pandemic.

Development of Decision-Making Tool and Pareto Set Analysis for Bi-Objective Optimization of an ORC Power Plant

Power plants based on organic Rankine cycle (ORC) are known for their capacity in converting low and medium-temperature energy sources to electricity. To find the optimal operating conditions, a designer must evaluate the ORC from different perspectives including thermodynamic performance, technological limits, economic viability, and environmental impact. A popular approach to include different criteria simultaneously is to formulate a bi-objective optimization problem. This type of multi-objective optimization (MOO) allows for finding a set of optimal design points by defining two different objectives. Once the optimization is completed, the decision-making analysis shall be carried out to identify the final design solution. This study aims to develop a decision-making tool for facilitating the choice of the optimal design point. The proposed procedure is coded in MATLAB based on the commonly used Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By providing the capability to graphically identify the decisions taken, the tool developed in the study is called Tracking and Recognizing Alternative Design Solutions (TRADeS). Analysis of our data shows that certain regions of Pareto set points should be excluded from the design space. It was noted that in these regions a high rate at which one of the objectives moves away from its ideal value coincides with a low rate at which the second criterion approaches its ideal solution. Hence, it was recommended that the criteria weights corresponding to excluded regions of the Pareto set should be discarded when selecting the final design point. By comparing the results obtained using the proposed model to those of existing decision-making techniques, it was concluded that while the known approaches are appropriate for an easy and fast selection of the final design point, the presented procedure allows for a more comprehensive and well-rounded design. It was shown that our design tool can be successfully applied in the decision-making analysis for problems that aim at optimizing the ORC using two design criteria. Finally, the proposed software benefits from a generic structure and is easy to implement which will facilitate its use in other industrial applications.

Topology Optimization for FDM Parts Considering the Hybrid Deposition Path Pattern.

Based on a solid orthotropic material with penalization (SOMP) and a double smoothing and projection (DSP) approach, this work proposes a methodology to find an optimal structure design which takes the hybrid deposition path (HDP) pattern and the anisotropic material properties into consideration. The optimized structure consists of a boundary layer and a substrate. The substrate domain is assumed to be filled with unidirectional zig-zag deposition paths and customized infill patterns, while the boundary is made by the contour offset deposition paths. This HDP is the most commonly employed path pattern for the fused deposition modeling (FDM) process. A critical derivative of the sensitivity analysis is presented in this paper, which ensures the optimality of the final design solutions. The effectiveness of the proposed method is validated through several 2D numerical examples.

Alternatives to Improve Operational Traffic in Roundabouts Using Microsimulation

Roundabout in urban arterials are likely to block roads or generate long queues of vehicles due to the constant changes on urban dynamics near to the interception. Several alternatives to modify the flow pattern or geometry and infrastructure need to be study previously to propose a final design solution of roundabout with traffic issues. In this study, a review of three alternatives to improve the operational traffic are discussed; signalized intersection, turbo-roundabouts and overpass/underpass. In addition, the application of these alternatives is evaluated in a “classic” roundabout located at Tunja city that has a maximum of 3691 Veh/h counted and it is operated in saturated condition. Microsimulation is used from a calibrated model with volume counted, vehicle composition and speeds in the VISSIM software. Results show that signalize the roundabout does not improve the operational traffic (with a reduction on 38% of approach speed) and, the turbo-roundabouts are a mid-term solution that meet the traffic demand on 15 years with a progressively loss of service (with a mean approach speed of 6.4 Km/h at 15 years). The constructions of underpass and overpass show to be the only solution that increase four times the travel speed throw the roundabout and keep acceptable speed at the end of cyclic live of intersection (18.7 Km/h at 20 years).

Adaptive Inspirational Design Stimuli: Using Design Output to Computationally Search for Stimuli That Impact Concept Generation

Abstract Design activity can be supported using inspirational stimuli (e.g., analogies, patents) by helping designers overcome impasses or in generating solutions with more positive characteristics during ideation. Design researchers typically generate inspirational stimuli a priori in order to investigate their impact. However, for a chosen stimulus to possess maximal utility, it should automatically reflect the current and ongoing progress of the designer. In this work, designers receive computationally selected inspirational stimuli midway through an ideation session in response to the contents of their current solution. Sourced from a broad database of related example solutions, the semantic similarity between the content of the current design and concepts within the database determines which potential stimulus is received. Designers receive a particular stimulus based on three experimental conditions: a semantically near stimulus, a semantically far stimulus, or no stimulus (control). Results indicate that adaptive inspirational stimuli can be determined using latent semantic analysis (LSA) and that semantic similarity measures are a promising approach for real-time monitoring of the design process. The ability to achieve differentiable near versus far stimuli was validated using both semantic cosine similarity values and participant self-response ratings. As a further contribution, this work also explores the impact of different types of adaptive inspirational stimuli on design outcomes using a newly introduced “design innovation” measure. The design innovation measure mathematically captures the overall goodness of a design concept by uniquely combining expert ratings across easier to evaluate subdimensions of feasibility, usefulness, and novelty. While results demonstrate that near inspirational stimuli increase the feasibility of design solutions, they also show the significant impact of the overall inspirational stimulus innovativeness on final design outcomes. In fact, participants are more likely to generate innovative final design solutions when given innovative inspirational stimuli, regardless of their experimental condition.

Mechanistic-empirical design of fibre reinforced concrete (FRC) pavements using inelastic analysis

Use of fibre reinforced concrete (FRC) for pavements is advocated since the higher crack resistance could lead to lower slab thickness and higher joint spacing. The post-cracking capacity of FRC allows pavements to be designed and analysed considering the response beyond the elastic regime. The current paper presents possible failure patterns in FRC pavement slabs, which are governed by the slab dimensions, loading type and boundary conditions, and the appropriateness of inelastic design methodologies for these failure patterns. Subsequently, a mechanistic-empirical design methodology developed for FRC pavements, based on yield line analysis incorporating fatigue in the moment calculation, is discussed. The proposed design methodology gives specific checks for the different failure patterns and the consequent design strategy to be adopted. The method incorporates material parameters, such as the first crack and post crack flexural strengths, and fatigue correction factors for the evaluation of the moment carrying capacity. Cumulative fatigue damage analysis is also done as a serviceability check. The final design solution satisfies both the inelastic moment capacity requirement and fatigue life required without excessive damage accumulation.

Quantifying seismic risk in structures via simplified demand–intensity models

Performance-based earthquake engineering (PBEE) has traditionally implied the verification of limit states at different earthquake intensities, where recent developments advocate a more risk-consistent approach. This has been primarily investigated for assessing existing structures and typically involves extensive analyses using detailed numerical models and ground motions. For new design, structures must be sized and detailed before more advanced numerical verifications are performed and the final design solution is established. In assessment, simplified procedures have been developed to incorporate further aspects of PBEE and typically comprise extensions to traditional structural analysis methods. Displacement-based assessment is one such method and while it has been extended for PBEE in the past, its use in a risk-oriented context still requires some validation. This article presents such a study, where recent developments in simplified analysis to estimate the exceedance rates of both storey drift and floor acceleration in reinforced concrete frames are described. This gives a method that is simple in its application, since it doesn’t require extensive and detailed numerical modelling or analysis, but also sufficiently accurate in its quantification of performance. While not intended as a substitute to extensive verification analysis, such a method for quantifying structural demand exceedance rates can be used to check results and provide better understanding to risk analysts. The work described herein can also be used in simplified verification analysis of new designs, whereby trial solutions may be verified in a relatively easy manner before more extensive verifications are carried out via non-linear dynamic analysis. It represents a further extension to existing simplified methods that strive toward more advanced performance quantification in line with the needs and goals of PBEE.