Initial Design Space Research Articles

Homogenization Model for Multistable Honeycomb Metastructures with Beam-like Behavior

Reduced order models facilitate initial design space investigations and enable assessing the benefits of compliant structures utilized for shape adaptability. This work presents a simple model to determine the flexural rigidity of a beam-like, multistable metastructure used as a spar in a hybrid spanwise morphing wing. The model considers the more complex metabeam as a homogeneous beam described by Euler-Bernoulli beam theory with an equivalent flexural rigidity. The analytical model's validity is established by comparing the obtained static and dynamic responses to finite element simulations. A closed-form expression of the flexural rigidity is then given, drawing from the multistable honeycomb's material properties and the metabeam’s geometry. The model's limitations are addressed by examining several specific cases of the metabeam’s morphed configurations and a more complex metabeam structure.

3G-optimization of multi-cell crash box cross-section of autobody based on crashworthiness

The cross-section, thickness, and material of the autobody structure determine the crashworthiness and lightweight level. Different from the variables in traditional autobody design that are considered separately, the basic theory of 3G-optimization is to simultaneously consider geometric shape (Geometry), the thickness of structure (Gauge), and material grade (Grade) in structural optimization design, which is conducive to maximizing the lightweight potential of the structure. This paper presents a cross-section optimization method for multi-cell thin-walled structures based on 3G-optimization, which is used in the structural design of crash box. Based on full width frontal collision condition, the cross-section shape, thickness, and material variables of the multi-cell crash box are optimized simultaneously. Multiple sets of optimization schemes show obvious weight reduction effect while ensuring safety. Besides, the sub-system decoupling method and hybrid cellular automaton (HCA) method are applied to 3G-optimization process, which is beneficial to improve the calculation efficiency and provide a theoretical basis for the definition of the initial design space for 3G-optimization.

Load frequency fractional‐order controller design for shipboard microgrids using direct search alghorithm

Load frequency control (LFC) is one of the controversial topics in power systems, especially in shipboard microgrids (SMG). In such applications, renewable energies such as wind, solar, or wave energies provide the power supply. However, changes in the weather conditions or loads can disrupt the frequency. To have a constant frequency in the presence of such turbulence in SMG, a fractional-order dynamic output feedback controller (FDOFC) is proposed. As a result, the closed-loop system is extended to a non-identical fractional-order system in the state space model. First, the non-identical fractional-order system is transformed into an identical one using the least common multiple techniques to determine control parameters. Subsequently, using a direct search algorithm, a considered initial design space is divided into smaller totally stable (TS) sub-spaces. Then, among all TS controller parameters, the H ∞ $H_{\infty }$ controller is designed to reduce the effects of disturbances. The study is carried out on a practical SMG system to show the practicality of the proposed FDOFC. Finally, to evaluate the proposed method's efficiency, the SMG results are compared with the results obtained with μ synthesis, H ∞ $H_{\infty }$ , Bilinear Matrix Inequality (BMI)-based, and fuzzy fractional optimization methods. Compared to the state-of-the-art approaches, more promising results are obtained for H ∞ $H_{\infty }$ -norm of the closed-loop system about ten times smaller, that is, | | Δ f | | ∞ = 0.00026 $||\Delta f||_\infty = 0.00026$ which is such a negligible norm that concludes perfect disturbance rejection. Moreover, in more scenarios, the robustness of the designed framework is evaluated under parameter variations and time delays in communication. The results show that the maximum frequency deviation is 2.5 × 10 − 3 $2.5 \times 10^{-3}$ , which is very small. Therefore, the controller also works impressively under deviations of SMG system parameters, and communication time delays.

Robust observer design for LPV systems using Kronecker sum and direct searching

This paper addresses a robust Luenberger observer for an uncertain linear parameter varying (LPV) system based on the concepts of direct searching, Kronecker sum, and small gain theorem. An algorithm is proposed to investigate the situation of the different parts of the initial observer design space, in terms of suitability for being selected as the observer gain or needing elimination due to being an undesirable part. To find the undesirable parts of the design space, the singularity of the Kronecker sum matrix of the estimation error is checked by employing the small gain theorem concept. By excluding undesired parts from the entire design space and checking the remaining parts’ feasibility, a suitable solution can be found, appropriately. The performance of the proposed observer design method is illustrated by using numerical examples and an electric ground vehicle (EGV) system for the estimation of the vehicle sideslip angle and the yaw rate. The results prove the appropriateness of the designed observer using the proposed approach.

Influence of Systematic Hull Shape Variations on Ship Stability Performances in Waves

Abstract The sensitivity of ship stability performance in waves to geometric variation has been investigated by means of a simulation-based design framework. The study was devoted to assess the influence of hull geometry variations on some stability failure modes, namely, parametric roll (PR) and pure loss of stability (PLS). The application has been developed by using a representative model of a postpanamax container vessel. PR and PLS phenomena have been investigated by the application of second-generation intact stability criteria (SGISc). The initial multidimensional design space has been filled by 500 design configurations identified by means of a design of experiments approach. A method developed in-house, combining the subdivision surface and free-form deformation approaches, has been used to create the whole set of design alternatives. The generated design configurations have been assessed analyzing the results derived from application of the first- and the second-level SGIS vulnerability criteria for both the selected stability failure modes. To strengthen the correlation behaviors, the design space has then been further explored by using 10k design configurations exploiting the capabilities of a surrogate model–based approximation, relying on a Gaussian process formulation. The study has been focused on the correlations among the variables and the response functions, i.e., the outcomes of the SGIS vulnerability criteria. The significance, in terms of effects, of each geometry shape variable has been investigated. Results have been discussed in the light of the SGISc structure, to provide further insight into this innovative safety framework for a modern approach to intact stability. Introduction In the last 10 years, the development of the so-called second-generation intact stability criteria (SGISc) has been one of the most engaging topics addressed by the Sub-Committee on Safety Design and Construction (SDC) of the International Maritime Organization (IMO).

An Iterative Approach towards Single stage Axial Fan Design using Off Design Prediction

A single-stage axial fan having a pressure ratio of 1.01 is designed in the current study. The design pressure ratio is chosen based on the power available from the existing motor (2.2 kW). The design space for the axial flow fan was generated by varying specific flow and geometrical parameters in suitable steps, using a program written in MATLAB. The varied flow parameters are mass flow rate, inlet Mach number, inlet flow angle, and rotor speed. The geometrical parameters that were varied are hub to tip ratio, aspect ratio, and blade solidity. Using these as the input variables and applying free vortex theory for 3-dimensional blade design, the aerodynamic design of the axial flow fan was carried out. Performance parameters like flow coefficient, stage loading coefficient, degree of reaction, diffusion factor, De Haller’s number, and blade angles were calculated at the blade’s hub, mean, and tip. Total design space of 92160 data points was obtained from the combination of input parameters. Several constraints were applied to optimise the design space based on the available power from the existing motor and in-house manufacturing limitations. The initial design space was reduced to 82 data points using these constraints. To further reduce the number of points in the design space, off-design performance was evaluated for each of these data points. Following this, one design point was selected based on the optimum performance range in off-design operation, while considering manufacturing limitations. Using Mellor charts, a suitable blade profile was chosen based on the inlet and exit blade angles. NACA 65-410 airfoil was selected with a stagger of 55 degrees and an incidence of 6 degrees for optimum performance.

Developing data-driven surrogate models for holistic performance-based assessment of mid-rise RC frame buildings at early design

This paper presents a framework to develop generalizable surrogate models to predict seismic vulnerability and environmental impacts of a class of buildings at a particular location. To this end, surrogate models are trained on a performance inventory, here simulation-based seismic and environmental assessments of 720 mid-rise concrete office buildings of variable topology in Charleston, South Carolina. Five surrogate models of multiple regression, random forest, extreme gradient boosting, support vector machine and k-nearest neighbors were trained in a machine-learning pipeline including hyperparameter tuning and cross-validation. Variance-based sensitivity and accumulated local effect analysis were performed on the most accurate model to identify the most influential parameters and interpret the trained surrogate model. Support vector machines achieved the highest accuracy for total annual loss with an average 10-fold adjusted R2 of 0.96, whereas simpler linear regression was adequate to estimate the initial and seismic-induced embodied carbon emission. Floor area, building height, lateral-resisting frame weight, and average beam section sizes were found to be the most influential features. As these features may be approximated by an experienced structural engineer the results indicate that, with suitable performance inventories available, it should be possible to employ surrogate models in early design to narrow the initial design space to highly resilient and sustainable configurations.

A Breakdown of System of Systems Needs Using Architecture Frameworks, Ontologies and Description Logic Reasoning

Aerospace systems are connected with the operational environment and other systems in general. The focus in aerospace product development is consequently shifting from a singular system perspective to a System-of-Systems (SoS) perspective. This increasing complexity gives rise to new levels of uncertainty that must be understood and managed to produce aerospace solutions for an ever-changing future. This paper presents an approach to using architecture frameworks, and ontologies with description logic reasoning capabilities, to break down SoS needs into required capabilities and functions. The intention of this approach is to provide a consistent way of obtaining the functions to be realized in order to meet the overarching capabilities and needs of an SoS. The breakdown with an architecture framework results in an initial design space representation of functions to be performed. The captured knowledge is then represented in an ontology with description logic reasoning capabilities, which provides a more flexible way to expand and process the initial design space representation obtained from the architecture framework. The proposed approach is ultimately tested in a search and rescue case study, partly based on the operations of the Swedish Maritime Administration. The results show that it is possible to break down SoS needs in a consistent way and that ontology with description logic reasoning can be used to process the captured knowledge to both expand and reduce an available design space representation.

Optimized One-Click Development for Topology-Optimized Structures

Topology optimization is a powerful digital engineering tool for the development of lightweight products. Nevertheless, the transition of obtained design proposals into manufacturable parts is still a challenging task. In this article, the development of a freeware framework is shown, which uses a hybrid topology optimization algorithm for stiffness and strength combined with manufacturing constraints based on finite spheres and a two-step smoothing algorithm to design manufacturable prototypes with “one click”. The presented workflow is shown in detail on a rocker, which is “one-click”-optimized and manufactured. These parts were experimentally tested using a universal testing machine. The objective of this article was to investigate the performance of “one-click”-optimized parts in comparison with manually redesigned optimized parts and the initial design space. The test results show that the design proposals created while applying the finite-spheres and two-step smoothing are equal to the manual redesigned parts based on the optimization results, proposing that the “one-click”-development can be used for the fast and direct development and fabrication of prototypes.

Aero-structural Design of Composite Wings for Airborne Wind Energy Applications

In this work we explore the initial design space for composite kites, focusing on the configuration of the bridle line system and its effect on the aeroelastic behaviour of the wing. The computational model utilises a 2D cross sectional model in conjunction with a 1D beam model (2+1D structural model) that captures the complex composite coupling effects exhibited by slender, multi-layered composite structures, while still being computationally efficient for the use at the initial iterative design stage. This structural model is coupled with a non-linear vortex lattice method (VLM) to determine the aerodynamic loading on the wing. In conjunction with the aerodynamic model, a bridle model is utilised to determine the force transfer path between the wing and the bridles connected with the tethers leading to the ground station. The structural model is coupled to the aerodynamic and bridle models in order to obtain the equilibrium aero-structural-bridle state of the kite. This computational model is utilised to perform a design space exploration to assess the effects of varied load introduction to the structure and resulting effects on the kite.

Numerical evaluation of topologically optimized ribs for mechanical components

Topology optimization method helps to minimize the mass or volume of the mechanical elements. In the present work, a methodology is proposed to use the topology optimization method for development of ribs like structure that add strength in the two-dimensional mechanical components. Ribs improve the stiffness significantly for the mechanical or structural components. However, the mass and the volume are also increased by adding ribs. Here a methodology is proposed to optimize the shape and size of ribs with their connections to the main component, which minimizes the overall mass. For illustration, a 2D rotary link of predefined shape and dimension are chosen, on which the ribs are added. The region of ribs is defined by initial design space of specific area such as rectangular, trapezoidal and elliptical. The density-based modified solid isotropic material with penalization approach (SIMP) is used for modeling material properties in continuous setting through interpolation and solved by optimality criteria algorithm. Minimization of compliance is chosen as the objective function, with volume fraction as a constraint ranging from 0.7 to 0.1. A MATLAB code is developed based on boundary conditions to obtain topologies at different geometrical shapes for different volume fraction. A comparison of the different shaped material domain is performed based on maximum deflection and Von-Mises stress values. The rectangular domain is found to be the best for minimum compliance and deflection, however, the trapezoidal domain is found to be the best for minimum stress levels.

A novel global optimization algorithm and data-mining methods for turbomachinery design

A new multi-objective, multi-disciplinary global optimization strategy is proposed to address the high-dimensional, computationally expensive black box problem (HEB) in turbomachinery design. The strategy consists of an adaptive sampling hybrid optimization algorithm (ASHOA), two data-mining techniques, a 3D blade parameterization method, and the aerodynamic/mechanical codes. Firstly, the ASHOA is established by integrating a novel adaptive sampling Kriging metamodel and a new hybrid optimization method. Secondly, two data-mining methods (analysis of variance (ANOVA) and self-organizing map (SOM)) are applied to set the initial design space and optimization objectives of the transonic centrifugal compressor. A refined design space and objective parameters of the optimization problem are eventually obtained. Finally, the optimization process of a transonic centrifugal compressor is carried out based on the refined design space and objectives using ASHOA. The results show that the search efficiency of the optimization strategy is 2–10 times higher when compared to other excellent optimization algorithms. For the optimized compressor, both isentropic efficiency and total pressure ratio at design condition are improved by 1.61% and 4.13%, respectively, and the maximum stress decreases by 9.68%.

Architectural Optimization Framework for Earth-Observing Heterogeneous Constellations: Marine Weather Forecast Case

Earth observation satellite programs are currently facing, for some applications, the need to deliver hourly revisit times, subkilometric spatial resolutions, and near-real-time data access times. These stringent requirements, combined with the consolidation of small-satellite platforms and novel distributed architecture approaches, are stressing the need to study the design of new, heterogeneous, and heavily networked satellite systems that can potentially replace or complement traditional space assets. In this context, this paper presents partial results from ONION, a research project devoted to studying distributed satellite systems and their architecting characteristics. A design-oriented framework that allows selecting optimal architectures for the given user needs is presented in this paper. The framework has been used in the study of a strategic use-case and its results are hereby presented. From an initial design space of 5586 potential architectures, the framework has been able to preselect 28 candidate designs by an exhaustive analysis of their performance and by quantifying their quality attributes. This very exploration of architectures and the characteristics of the solution space are presented in this paper along with the selected solution and the results of a detailed performance analysis.

Optimizing Weight of Housing Elements of Two-stage Reducer by Using the Topology Management Optimization Capabilities Integrated in SOLIDWORKS: A Case Study

This paper presents the results of a conducted topology management optimization study based on the finite element analysis on a two-stage spur gear reducer housing body and cover using the SOLIDWORKS Simulation module. The main goal of the study is to optimize the overall weight of the reducer by thinning specific areas of the casted gearbox housing elements according to the calculated minimal strain energy. The topology optimization algorithm that is used in current research gives an optimal structural shape of the housing elements of the reducer with the largest stiffness, considering the given amount of mass that will be removed from the initial design space. The complete sequence of steps for conducting the topology management optimization study is shown, taking into account the constraints arising from the construction features and the method of manufacturing the housing elements of the gear reducer. Conclusions on the use of the topology optimization results are given and potential directions for further development of the approach are also identified.

Rapid Design of Deployable Antennas for CubeSats: A tool to help designers compare and select antenna topologies

A novel methodology for the rapid preliminary design of deployable antennas for CubeSats is proposed in this article. It uses a graphical representation of antenna performance, consisting of a set of plots of different performance metrics against antenna geometry parameters. Coupled electromagnetic and structural design problems are addressed easily, enabling the rapid and direct comparison of different antenna concepts. This approach is demonstrated for a case study at ultrahigh frequency (UHF), comparing the performance of a dipole, a helix, a conical horn, and a conical log spiral (CLS), all based on dual-matrix composite deployable structures. The initial design space of antenna geometries is reduced by two orders of magnitude to a set of constraintsatisfying designs. A graphical user interface implementing the approach is presented, and the accuracy of the method is briefly addressed.

Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates

In the paper, computationally efficient constrained multi-objective design optimization of transonic airfoil profiles is considered. Our methodology focuses on fixed-lift design aimed at finding the best possible trade-offs between the two objectives: minimization of the drag coefficient and maximization of the pitching moment. The algorithm presented here exploits the surrogate-based optimization principle, variable-fidelity computational fluid dynamics (CFD) models, as well as auxiliary data-driven surrogates (here, using Kriging). In order to permit computationally feasible construction of the Kriging models, initial design space reduction is also utilized. The design process has three major stages: (i) identification of the extreme points of the Pareto front through single-objective optimization (one objective at a time), (ii) construction of the Kriging model and initial Pareto front generation using multi-objective evolutionary algorithm (MOEA), and (iii) Pareto front refinement using response correction techniques and local response surface approximation (RSA) models. For the sake of computational efficiency, stages (i) and (ii) are realized at the level of coarse-discretization CFD model. The RSA models are also utilized to predict the angle of attack necessary to achieve the target lift coefficient, which considerably reduces the CFD simulation effort involved in the design process. Two design case studies are considered involving B-spline-parameterized airfoil shapes with 8 and 12 design variables. The 10-element Pareto front representations are obtained at the cost corresponding to just over two hundred of high-fidelity CFD model evaluations. This cost is not only considerably lower (up to two orders of magnitude) than the cost of direct high-fidelity model optimization using metaheuristics but, more importantly, renders multi-objective optimization of aerodynamic components computationally tractable even at the level of accurate CFD models.

Rational development of two flowthrough purification strategies for adenovirus type 5 and retro virus-like particles

We report on the rational design and implementation of flowthrough (FT) platforms for purification of virus vectors (VVs) and virus-like particles (VLPs), combining anion-exchange polyallylamine membranes (Sartobind STIC) and core–shell octylamine resins (CaptoCore 700). In one configuration, the VV bulk is concentrated and conditioned with appropriate buffer in a ultra/diafiltration (UF/DF) unit prior to injection into the STIC chromatography membrane. The FT pool and an intermediate cut of the elution pool of the STIC membrane are admixed and directed to a second UF/DF. Finally, the retentate is injected into a CC700 packed bed adsorber where the purified VVs are collected in the FT pool, whereas the residual amount of DNA and host cell protein (HCP) are discarded in the eluate. The experimental recovery achieved with this downstream processing (DSP) platform is close to 100%, the DNA clearance is roughly a 4-log reduction, and the HCP level is reduced by 5 logs. The platform developed for VLP purification is simpler than the previous one, as the STIC membrane adsorber and CC700 bed are connected in series with no UF/DF unit in between. Experimentally, the FT scheme for VLP purification gave a recovery yield of 45% in the chromatography train; the experimental log reduction of DNA and HCP were 2.0 and 3.5, respectively. These results are in line with other purification strategies in the specific field of enveloped VLPs. Both DSP platforms were successfully developed from an initial design space of the binding of the major contaminant (DNA) to the two ligands, determined by surface plasmon resonance, which was subsequently scaled up and confirmed experimentally.

Comparison of Information Passing Strategies in System-Level Modeling

Research on complex system optimization has focused on areas including algorithms, coordination strategies, and communication tools. This paper considers optimization from the perspective of information coordination during the solution process. This work aims to determine the potential impact of factors including the role of a system facilitator in managing system-level tradeoffs, the influence of an ideal information scenario, the choice of system variables, and the amount and form of passed information. The goal is not to develop the “best” communication structure or optimization algorithm, but to understand the significance of these factors. A traditional multidisciplinary design optimization coordination framework, a game theoretic approach, and a modified game theory approach are used to mimic design team behaviors. Results suggest these factors can influence the coordination process outcomes: The choice of system variable plays a significant role in the optimality of the final design; perfect information does not necessarily reduce the number of iterations or improve optimality; a system facilitator aids in making better design tradeoffs, though it is possible to achieve optimality without one; and the stability of the design cycle depends on the amount of passed information. This suggests a design team should carefully analyze the initial design space to determine an appropriate design formulation before applying optimization.

Investigating the release of a hydrophobic peptide from matrices of biodegradable polymers: An integrated method approach

The objectives of this work were: (1) to select suitable compositions of tyrosine-derived polycarbonates for controlled delivery of voclosporin, a potent drug candidate to treat ocular diseases, (2) to establish a structure–function relationship between key molecular characteristics of biodegradable polymer matrices and drug release kinetics, and (3) to identify factors contributing in the rate of drug release. For the first time, the experimental study of polymeric drug release was accompanied by a hierarchical sequence of three computational methods. First, suitable polymer compositions used in subsequent neural network modeling were determined by means of response surface methodology (RSM). Second, accurate artificial neural network (ANN) models were built to predict drug release profiles for fifteen polymers located outside the initial design space. Finally, thermodynamic properties and hydrogen-bonding patterns of model drug–polymer complexes were studied using molecular dynamics (MD) technique to elucidate a role of specific interactions in drug release mechanism. This research presents further development of methodological approaches to meet challenges in the design of polymeric drug delivery systems.

Robust Design in Occupant Safety Simulation

Explicit FE-simulation has become a standard design tool in passive safety development as it can help to reduce the number of vehicle prototype tests, especially in the early project stages. Due to fewer hardware tests available as sources of validation, the expectations towards predictability of dummy injury occurrence have strongly increased. To produce robust results, virtual passive safety analysis has to take real uncertainties of test condition and their probabilistic effects upon the system's response into account. FINDINGS by simulation therefore should not be regarded anymore as single point statements in a pure deterministic approach. They rather need to be extended into statements upon grades of correlation between individual system parameters taking into account their stochastic nature. This paper illustrates a process for complete robustness analysis in occupant safety simulation. It introduces techniques to document statistical confidence intervals of the correlations determined, and uses statistical bootstrapping in populations where only a limited number of samplings can be generated. Finally, by regression analysis within the reduced relevant physical parameter space, a risk assessment upon a potential failure within the specific test requirements is carried out. Identification of initial design space parameters requires experience and proper preparation when one is conducting statistical analysis on occupant safety. This work explains relevant design space parameters for a typical full vehicle test and classifies them in proper ways since obtaining their sampling often requires additional pre-simulation efforts. In this context a number of in-house tools are highlighted here that helps the designer in obtaining work intensive design parameters such as the distribution of dummy, seat & belt positions. The entire robustness design process uses automated work flows and tools to visualize the statistical data observed since the simulation model complexity and its computational costs are extremely high. Finally, the gained correlations are discussed, interpreted and explained in terms of real life phenomenon that can be observed in testing. Language: en