scholarly journals Optimal design of sandwich floor panels made of high-strength composite materials considering stiffness constraints

2021 ◽  
Vol 20 (2) ◽  
pp. 45-52
Author(s):  
V. A. Komarov ◽  
S. A. Pavlova
Keyword(s):  
Design Space ◽  
Constraint Equation ◽  
High Strength ◽  
Geometrical Parameters ◽  
Additional Mass ◽  
Sandwich Construction ◽  
Design Variables ◽  
Floor Panel ◽  
Honeycomb Filler ◽  
Strength And Stiffness

The article considers the challenge of designing sandwich floor panels made of high-strength composites considering stiffness constraints. A dimensionless criterion is proposed for assessing the stiffness of floor panels. A new constraint equation determines an interrelation between geometrical parameters of composite constructions and a given criterion. A demo example and the results of designing a typical floor panel using a high-strength composite material are presented. The mass of a square meter of the structure is considered as an objective function, and the thickness of the skin and the height of the honeycomb core of a sandwich construction are considered as design variables. In order to find the optimal ratio of design variables, a graphical interpretation of the design problem is used considering strength and stiffness constraints in the design space. It is noted that the presence of restrictions on a given value of the permissible relative deflection leads to an increase in the required height of the honeycomb filler with an insignificant consumption of additional mass of the sandwich construction.

scholarly journals Optimization of honeycomb sandwich floor panels made of polymer-matrix low-combustible composite materials based on high-strength carbon and glass fibers and adhesive binder

2020 ◽  
Vol 19 (3) ◽  
pp. 51-72
Author(s):  
V. A. Komarov ◽  
K. E. Kutsevich ◽  
S. A. Pavlova ◽  
T. Yu. Tyumeneva
Keyword(s):  
Experimental Data ◽  
Composite Materials ◽  
Glass Fibers ◽  
Design Procedure ◽  
High Strength ◽  
Visual Interpretation ◽  
Design Task ◽  
Design Variables ◽  
Honeycomb Sandwich ◽  
Floor Panel

The article deals with the task of designing aircraft honeycomb sandwich floor panels considering experimental data on the mechanical properties of new high-strength low-combustible composite materials. The developed experimental and analytical design procedure and optimization algorithm are described. The design task is formulated in terms of nonlinear mathematical programming in which the mass per square meter of the construction is the objective function. The thickness of the base layers, the height of honeycomb core and some other parameters are considered as the design variables. The proposed visual interpretation of the optimal design task allows reducing possible design solutions based on the experimental data to an enumeration of a limited number of design alternates. The article presents a demo task and the results of designing floor panes for an advanced passenger aircraft in the aisle area using a new low-combustible composite material. The floor panel is regarded as a continuous multiply supported plate loaded with distributed load. The proposed grapho-analytical method makes it possible to form the area of rational designs that differ from the optimal one in terms of mass by a specified allowable value. The performed computational and experimental analysis shows that with the use of the new material, a floor panel can be designed with base layers made of carbon or fiberglass and lightweight honeycomb filler with the mass of a square meter from 2,9 to 3,4 kg, which is the state-of-the-art.

scholarly journals Materials for Automotive Lightweighting

2019 ◽  
Vol 49 (1) ◽  
pp. 327-359 ◽  
Author(s):  
Alan Taub ◽  
Emmanuel De Moor ◽  
Alan Luo ◽  
David K. Matlock ◽  
John G. Speer ◽  
...  
Keyword(s):  
Galvanic Corrosion ◽  
Low Carbon Steel ◽  
High Strength Steels ◽  
High Strength ◽  
Low Carbon ◽  
New Materials ◽  
Specific Strength ◽  
Advanced High Strength Steels ◽  
Strength And Stiffness ◽  
The Cost

Reducing the weight of automobiles is a major contributor to increased fuel economy. The baseline materials for vehicle construction, low-carbon steel and cast iron, are being replaced by materials with higher specific strength and stiffness: advanced high-strength steels, aluminum, magnesium, and polymer composites. The key challenge is to reduce the cost of manufacturing structures with these new materials. Maximizing the weight reduction requires optimized designs utilizing multimaterials in various forms. This use of mixed materials presents additional challenges in joining and preventing galvanic corrosion.

Multi-Objective Optimization of an Autonomous Underwater Vehicle

2009 ◽  
Vol 43 (2) ◽  
pp. 48-60 ◽  
Author(s):  
M. Martz ◽  
W. L. Neu
Keyword(s):  
Design Space ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Design Problems ◽  
Single Measure ◽  
Design Variables ◽  
Complex Design ◽  
Final Design ◽  
Undersea Vehicle ◽  
Hierarchy Process

AbstractThe design of complex systems involves a number of choices, the implications of which are interrelated. If these choices are made sequentially, each choice may limit the options available in subsequent choices. Early choices may unknowingly limit the effectiveness of a final design in this way. Only a formal process that considers all possible choices (and combinations of choices) can insure that the best option has been selected. Complex design problems may easily present a number of choices to evaluate that is prohibitive. Modern optimization algorithms attempt to navigate a multidimensional design space in search of an optimal combination of design variables. A design optimization process for an autonomous underwater vehicle is developed using a multiple objective genetic optimization algorithm that searches the design space, evaluating designs based on three measures of performance: cost, effectiveness, and risk. A synthesis model evaluates the characteristics of a design having any chosen combination of design variable values. The effectiveness determined by the synthesis model is based on nine attributes identified in the U.S. Navy’s Unmanned Undersea Vehicle Master Plan and four performance-based attributes calculated by the synthesis model. The analytical hierarchy process is used to synthesize these attributes into a single measure of effectiveness. The genetic algorithm generates a set of Pareto optimal, feasible designs from which a decision maker(s) can choose designs for further analysis.

Aerodynamic Efficiency Optimization of the 1st Stage of Transonic High Pressure Turbine through Lean and Sweep Angles

2019 ◽  
Vol 36 (3) ◽  
pp. 245-256
Author(s):  
Yoonki Kim ◽  
Sanga Lee ◽  
Kwanjung Yee ◽  
Young-Seok Kang
Keyword(s):  
High Pressure ◽  
Surrogate Model ◽  
Design Space ◽  
Latin Hypercube Sampling ◽  
Expected Improvement ◽  
Total Efficiency ◽  
High Pressure Turbine ◽  
Sweep Angle ◽  
Design Variables ◽  
Optimal Latin Hypercube Sampling

Abstract The purpose of this study is to optimize the 1st stage of the transonic high pressure turbine (HPT) for enhancement of aerodynamic performance. Isentropic total-to-total efficiency is designated as the objective function. Since the isentropic efficiency can be improved through modifying the geometry of vane and rotor blade, lean angle and sweep angle are chosen as design variables, which can effectively alter the blade geometry. The sensitivities of each design variable are investigated by applying lean and sweep angles to the base nozzle and rotor, respectively. The design space is also determined based on the results of the parametric study. For the design of experiment (DoE), Optimal Latin Hypercube sampling is adopted, so that 25 evenly distributed samples are selected on the design space. Sequentially, based on the values from the CFD calculation, Kriging surrogate model is constructed and refined using Expected Improvement (EI). With the converged surrogate model, optimum solution is sought by using the Genetic Algorithm. As a result, the efficiency of optimum turbine 1st stage is increased by 1.07 % point compared to that of the base turbine 1st stage. Also, the blade loading, pressure distribution, static entropy, shock structure, and secondary flow are thoroughly discussed.

Optimization of a vacuum cleaner fan suction and shaft power using Kriging surrogate model and MIGA

2021 ◽  
pp. 095765092110496
Author(s):  
Soheil Almasi ◽  
Mohammad Mahdi Ghorani ◽  
Mohammad Hadi Sotoude Haghighi ◽  
Seyed Mohammad Mirghavami ◽  
Alireza Riasi
Keyword(s):  
Optimization Design ◽  
Optimization Technique ◽  
Internal Flow ◽  
Latin Hypercube Sampling ◽  
Sample Space ◽  
Geometrical Parameters ◽  
Vacuum Cleaner ◽  
Time Saving ◽  
Design Variables ◽  
Shaft Power

Optimization of vacuum cleaner fan components is a low-cost and time-saving solution to satisfy the increasing requirement for compact energy-efficient cleaners. In this study, surrogate-based optimization technique is used and for the first time it is focused on maximization of Airwatt parameter, which describes the fan suction power, as an objective function (Case II). Besides, the shaft power is minimized (Case I) as another optimization target in order to reduce the power consumption of the vacuum cleaner. 11 geometrical variables of 3 fan components including impeller, diffuser and return channel are selected as the optimization design variables. 80 training points are distributed in the sample space using Advanced Latin Hypercube Sampling (ALHS) technique and the outputs of sample points are calculated by means of CFD simulations. Kriging and RSA surrogate models have been fitted to the outputs of the sample space. Through coupling of constructed Kriging models and Multi-Island Genetic Algorithm (MIGA), the optimal design for each of the optimization cases is presented and evaluated using numerical simulations. A 20.22% reduction in shaft power in Case I and an improvement of 27.73% in Airwatt in Case II have been achieved as the overall results of this study. Despite achieving goals in both optimization cases, a slight decrease in Airwatt in Case I (−6.20%) and a slight increase in shaft power in Case II (+4.82%) are observed relative to primary fan. Furthermore, the Analysis of Variance (ANOVA) determines the importance level of design variables and their 2-way interactions on the objective functions. It was concluded that geometrical parameters related to all of the fan components must be considered simultaneously to conduct a comprehensive optimization. The reasons of enhancement in optimal cases compared with the reference design have been further investigated by analysis of the fan internal flow field. Post-processing of the CFD results demonstrates that the applied geometrical modifications cause a more uniform flow through the flow passages of the optimal fan components.

Beyond the Known: Detecting Novel Feasible Domains Over an Unbounded Design Space

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Wei Chen ◽  
Mark Fuge
Keyword(s):  
Real World ◽  
Adaptive Sampling ◽  
Design Space ◽  
Fundamental Problem ◽  
Domain Boundary ◽  
Sampling Technique ◽  
Standard Test ◽  
Worst Case ◽  
Trade Offs ◽  
Design Variables

To solve a design problem, sometimes it is necessary to identify the feasible design space. For design spaces with implicit constraints, sampling methods are usually used. These methods typically bound the design space; that is, limit the range of design variables. But bounds that are too small will fail to cover all possible designs, while bounds that are too large will waste sampling budget. This paper tries to solve the problem of efficiently discovering (possibly disconnected) feasible domains in an unbounded design space. We propose a data-driven adaptive sampling technique—ε-margin sampling, which learns the domain boundary of feasible designs and also expands our knowledge on the design space as available budget increases. This technique is data-efficient, in that it makes principled probabilistic trade-offs between refining existing domain boundaries versus expanding the design space. We demonstrate that this method can better identify feasible domains on standard test functions compared to both random and active sampling (via uncertainty sampling). However, a fundamental problem when applying adaptive sampling to real world designs is that designs often have high dimensionality and thus require (in the worst case) exponentially more samples per dimension. We show how coupling design manifolds with ε-margin sampling allows us to actively expand high-dimensional design spaces without incurring this exponential penalty. We demonstrate this on real-world examples of glassware and bottle design, where our method discovers designs that have different appearance and functionality from its initial design set.

Computer-aided design of a dielectric insert supporting uniformity of fast microwave heating

2018 ◽  
Vol 37 (6) ◽  
pp. 1958-1968 ◽  
Author(s):  
Ethan M. Moon ◽  
Vadim V. Yakovlev
Keyword(s):  
Microwave Heating ◽  
Complex Permittivity ◽  
Computer Aided Design ◽  
Heating Time ◽  
Geometrical Parameters ◽  
Heating Rates ◽  
Content Type ◽  
Design Variables ◽  
Processed Material ◽  
Aided Design

PurposeThis paper aims to introduce and illustrate a computational technique capable of determining the geometry and complex permittivity of a supplementary dielectric insert making distributions of microwave-induced dissipated power within the processed material as uniform as possible.Design/methodology/approachThe proposed technique is based on a 3D electromagnetic model of the cavity containing both the processed material and the insert. Optimization problem is formulated for design variables (geometrical and material parameters of the insert) identified from computational tests and an objective function (the relative standard deviation [RSD]) introduced as a metric of the field uniformity. Numerical inversion is performed with the method of sequential quadratic programming.FindingsFunctionality of the procedure is illustrated by synthesis of a dielectric insert in an applicator for microwave fixation. Optimization is completed for four design variables (two geometrical parameters, dielectric constant and the loss factor of the insert) with 1,000 points in the database. The best three optimal solutions provide RSD approximately 20 per cent, whereas for the patterns corresponding to all 1,000 non-optimized (randomly chosen) sets of design variables this metric is in the interval from 27 to 136 per cent with the average of 78 per cent.Research limitations/implicationsAs microwave thermal processing is intrinsically inhomogeneous and the heating time is not a part of the underlying model, the procedure is able to lead only to a certain degree of closeness to uniformity and is intended for applications with high heating rates. The initial phase of computational identification of design variables and their bounds is therefore very important and may pre-condition the “quality” of the optimal solution. The technique may work more efficiently in combination with advanced optimization techniques dealing with “smart” (rather than random) generation of the data; for the use with more general microwave heating processes characterized by lower heating rates, the technique has to use the metric of non-uniformity involving temperature and heating time.Practical implicationsWhile the procedure can be used for computer-aided design (CAD) of microwave applicators, a related practical limitation may emerge from the fact that the material with particular complex permittivity (determined in the course of optimization) may not exist. In such cases, the procedure can be rerun for the constant values of material parameters of the available medium mostly close to the optimal ones to tune geometrical parameters of the insert. Special manufacturing techniques capable of producing a material with required complex permittivity also may be a practical option here.Originality/valueNon-uniformity of microwave heating remains a key challenge in the design of many practical applicators. This paper suggests a concept of a practical CAD and outlines corresponding computational procedure that could be used for designing a range of applied systems with high heating rates.

scholarly journals Biomimetic Composites with Enhanced Toughening Using Silk Inspired Triblock Proteins and Aligned Nanocellulose Reinforcements

2019 ◽  
Author(s):  
Pezhman Mohammadi ◽  
A. Sesilja Aranko ◽  
Christopher P. Landowski ◽  
Olli Ikkala ◽  
Kristaps Jaudzems ◽  
...  
Keyword(s):  
Spider Silk ◽  
Cellulose Nanofibrils ◽  
High Strength ◽  
Beta Sheets ◽  
Conformational Switching ◽  
Multiple Length Scales ◽  
The Matrix ◽  
Strength And Stiffness ◽  
Flow Alignment

Silk and cellulose are biopolymers that show a high potential as future sustainable materials.They also have complementary properties, suitable for combination in composite materials where cellulose would form the reinforcing component and silk the tough matrix. Therein, a major challenge concerns balancing structure and properties in the assembly process. We used recombinant proteins with triblock architecture combining structurally modified spider silk with terminal cellulose affinity modules. Flow-alignment of cellulose nanofibrils and triblock protein allowed a continuous fiber production.The protein assembly involved phase separation into concentrated coacervates, with subsequent conformational switching from disordered structures to beta sheets. This gave the matrix a tough adhesiveness, forming a new composite material with high strength and stiffness combined with increased toughness. We show that versatile design possibilities in protein engineering enable new fully biological materials, and emphasize the key role of controlled assembly at multiple length scales for realization.<br>

scholarly journals A Multi-Fidelity Model for Simulations and Sensitivity Analysis of Piezoelectric Inkjet Printheads

Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1038
Author(s):  
Vinh-Tan Nguyen ◽  
Jason Yu Chuan Leong ◽  
Satoshi Watanabe ◽  
Toshimitsu Morooka ◽  
Takayuki Shimizu
Keyword(s):  
Sensitivity Analysis ◽  
Three Dimensional ◽  
Element Model ◽  
Geometrical Parameters ◽  
Generation Process ◽  
Mechanical Coupling ◽  
Design Variables ◽  
Computational Structural Mechanics ◽  
Lumped Element Model ◽  
Inkjet Printhead

The ink drop generation process in piezoelectric droplet-on-demand devices is a complex multiphysics process. A fully resolved simulation of such a system involves a coupled fluid–structure interaction approach employing both computational fluid dynamics (CFD) and computational structural mechanics (CSM) models; thus, it is computationally expensive for engineering design and analysis. In this work, a simplified lumped element model (LEM) is proposed for the simulation of piezoelectric inkjet printheads using the analogy of equivalent electrical circuits. The model’s parameters are computed from three-dimensional fluid and structural simulations, taking into account the detailed geometrical features of the inkjet printhead. Inherently, this multifidelity LEM approach is much faster in simulations of the whole inkjet printhead, while it ably captures fundamental electro-mechanical coupling effects. The approach is validated with experimental data for an existing commercial inkjet printhead with good agreement in droplet speed prediction and frequency responses. The sensitivity analysis of droplet generation conducted for the variation of ink channel geometrical parameters shows the importance of different design variables on the performance of inkjet printheads. It further illustrates the effectiveness of the proposed approach in practical engineering usage.

scholarly journals Optimization of Geometrical Parameters of Hollow-core Slabs by Formwork-free Shaping for Construction in Seismic Areas

2020 ◽  
Vol 8 (6) ◽  
pp. 4973-4977
Keyword(s):  
Cross Section ◽  
High Strength ◽  
Geometrical Parameters ◽  
Hollow Core ◽  
Constructive Solution ◽  
Industrial Buildings ◽  
Operational Load ◽  
Wide Range ◽  
Hollow Core Slab ◽  
The Cross

The building norms and standards of Uzbekistan on the reinforced concrete structures do not regulate the design of hollow-core slabs of formwork-free shaping, reinforced with prestressed wire reinforcement. The manufacturing technology of such slabs allows creating a wide range of products that increase the possibility of their use in various structural systems in residential, civil and industrial buildings, but in non-seismic areas only. The aim of this work is to develop a constructive solution for the cross section of a prestressed hollow-core floor slab of bench formwork-free shaping, reinforced with high-strength wire reinforcement, in order to create a wide range of products intended for construction in seismic areas. To achieve the goal, the problem of determining the optimal combination of height and configuration parameters of the cross section of such a slab is solved, meeting the normalized operational requirements and limitations of earthquake-resistant building standards. The main variable parameters are the height and the void degree of the section, characterized by the size and shape of voids. In calculating the cross-section of a hollow-core slab when substantiating the theoretical basis for the calculation, the cross section is reduced to the equivalent I-section. As a result of research, a constructive solution was developed for the slab cross section of the maximum parameter values (the span, operational load) set by the customer. The parameters of the slab cross-section are: the height 190 mm, the hollowness 38%, the height of the upper thickened flange (compared with the height of the lower flange) of the given section is 0.27h, the height of the lower flange is 0.17h, the reduced (total) thickness of all ribs “b” is 0.32 of the width of the upper flange. The voids in the section along the height of the slab are arranged asymmetrically. A patent for a utility model has been received for the proposed constructive solution of the slab cross section.

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