A Framework for the Design and Optimization of Self-Folding Structures

2017 ◽  
Author(s):  
Landen Bowen ◽  
Mary Frecker ◽  
Timothy W. Simpson ◽  
Rebecca Strzelec
Keyword(s):  
Active Material ◽  
Optimization Methods ◽  
Design And Optimization ◽  
Simulation And Optimization ◽  
Optimization Framework ◽  
Simulation Based ◽  
Trade Space Exploration ◽  
Specific Implementation ◽  
Passive Materials ◽  
Novel Design

Due to the multidisciplinary nature and complexity of self folding structures, it can be difficult to know where to start when designing for a new application. Decisions about the active and passive materials to be used and the functionality of the design are very interrelated and can create problems if not considered holistically. There is a need to formalize the steps necessary to move from an origami-inspired shape to a full self-folding concept. In this paper, an optimization framework is proposed to help designers create self-folding, origami-inspired structures that can accommodate any type of active material. The optimization framework formalizes the design steps needed to move from a target shape/application to a self-folding design. The method is simulation-based, allowing a self-folding design candidate to be identified quickly prior to costly trial-and-error physical prototyping. A general version of the framework is presented that can accommodate a variety of simulation and optimization methods, after which a specific implementation of the framework utilizing a dynamic model and trade space exploration tools is discussed and then used to design a multi-field self-folding carton. By using the framework, a novel design was identified that both significantly decreased the folding error as well as the amount of active material used when compared to designs that would typically be attempted in a trial-by-error design approach. The demonstrated self-folding design optimization framework has the potential to streamline the design of self-folding structures, resulting in better designs with less time, effort, and cost.

Reflections on the Opportunities of Multicriteria Optimization within Simulation Studies

2014 ◽  
Vol 693 ◽  
pp. 159-164
Author(s):  
Vladimír Jerz
Keyword(s):  
Theoretical Model ◽  
Optimal Design ◽  
Process Control ◽  
Simulation Model ◽  
Multicriteria Optimization ◽  
Optimization Methods ◽  
Simulation Studies ◽  
Simulation And Optimization ◽  
Logistics Systems ◽  
Simulation Based

This article discusses the possibilities of linking simulation and optimization methods, processes and tools to solve complex tasks of optimal design and process control in production and logistics systems. A theoretical model of simulation-based optimization is formulated. Its use in resolving practical problems as well as methods for the integration of algorithms for multi-criteria optimization into the simulation model are outlined.

Numerical multidisciplinary optimization of aircraft with flight dynamic stability constraints

2020 ◽  
pp. 095441002092665
Author(s):  
Jacek Mieloszyk
Keyword(s):  
Dynamic Stability ◽  
Optimization Methods ◽  
Multidisciplinary Optimization ◽  
Preliminary Design ◽  
Flight Performance ◽  
Design And Optimization ◽  
Optimization Framework ◽  
Aircraft Flight ◽  
Vertical Takeoff And Landing ◽  
Vertical Takeoff

Classical approach to conceptual and preliminary design in aerospace sciences reaches limits. To go further and achieve better, competitive results’ use of optimization methods becomes mandatory. The trend is clearly visible in professional software for simulations equipped with optimization tools, which was not standard just decade ago. Many examples of multidisciplinary optimization were shown, especially with coupled aerodynamics and structure analyses, but only few of them consider dynamic stability effects in the conceptual and preliminary design. The article shows successful example of multidisciplinary design and optimization of Vertical Takeoff and Landing aircraft, which includes coupling of aerodynamics, mass analyses and innovative approach of constraints from flight dynamic stability. Presented optimization framework revealed potential for more efficient conceptual and preliminary design with the result of known dynamic stability characteristics of the aircraft. Obtaining the dynamic stability characteristics is not common on the early stages of the design yet crucial for the aircraft flight performance.

scholarly journals A Comprehensive Study on the Optimal Design of Magnetorheological Dampers for Improved Damping Capacity and Dynamical Adjustability

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 64
Author(s):  
Liankang Wei ◽  
Hongzhan Lv ◽  
Kehang Yang ◽  
Weiguang Ma ◽  
Junzheng Wang ◽  
...  
Keyword(s):  
Optimal Design ◽  
Optimization Methods ◽  
Design Stage ◽  
Damping Capacity ◽  
Damping Force ◽  
Simulation And Optimization ◽  
Damping Characteristics ◽  
Hysteretic Characteristics ◽  
Gap Width ◽  
Comprehensive Study

Purpose: We aim to provide a systematic methodology for the optimal design of MRD for improved damping capacity and dynamical adjustability in performing its damping function. Methods: A modified Bingham model is employed to model and simulate the MRD considering the MR fluid’s compressibility. The parameters that describe the structure of MRD and the property of the fluid are systematically examined for their contributions to the damping capacity and dynamically adjustability. A response surface method is employed to optimize the damping force and dynamically adjustable coefficient for a more practical setting related to the parameters. Results: The simulation system effectively shows the hysteretic characteristics of MRDs and shows our common sense understanding that the damping gap width and yoke diameter have significant effects on the damping characteristics of MRD. By taking a typical MRD device setup, optimal design shows an increase of the damping force by 33% and an increase of the dynamically adjustable coefficient by 17%. It is also shown that the methodology is applicable to other types of MDR devices. Conclusion: The compressibility of MR fluid is one of the main reasons for the hysteretic characteristics of MRD. The proposed simulation and optimization methods can effectively improve the MRD’s damping performance in the design stage.

scholarly journals Combined simulation and optimization framework for irrigation scheduling in agriculture fields

2021 ◽  
Author(s):  
Mireia Fontanet ◽  
Daniel Fernàndez-Garcia ◽  
Gema Rodrigo ◽  
Francesc Ferrer ◽  
Josep Maria Villar
Keyword(s):  
Crop Yields ◽  
Root Zone ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Traditional Methods ◽  
Simulation And Optimization ◽  
Optimization Framework ◽  
Net Margin ◽  
Combined Simulation

AbstractIn the context of growing evidence of climate change and the fact that agriculture uses about 70% of all the water available for irrigation in semi-arid areas, there is an increasing probability of water scarcity scenarios. Water irrigation optimization is, therefore, one of the main goals of researchers and stakeholders involved in irrigated agriculture. Irrigation scheduling is often conducted based on simple water requirement calculations without accounting for the strong link between water movement in the root zone, soil–water–crop productivity and irrigation expenses. In this work, we present a combined simulation and optimization framework aimed at estimating irrigation parameters that maximize the crop net margin. The simulation component couples the movement of water in a variably saturated porous media driven by irrigation with crop water uptake and crop yields. The optimization component assures maximum gain with minimum cost of crop production during a growing season. An application of the method demonstrates that an optimal solution exists and substantially differs from traditional methods. In contrast to traditional methods, results show that the optimal irrigation scheduling solution prevents water logging and provides a more constant value of water content during the entire growing season within the root zone. As a result, in this case, the crop net margin cost exhibits a substantial increase with respect to the traditional method. The optimal irrigation scheduling solution is also shown to strongly depend on the particular soil hydraulic properties of the given field site.

An improved lattice structure design optimization framework considering additive manufacturing constraints

2017 ◽  
Vol 23 (2) ◽  
pp. 305-319 ◽  
Author(s):  
Recep M. Gorguluarslan ◽  
Umesh N. Gandhi ◽  
Yuyang Song ◽  
Seung-Kyum Choi
Keyword(s):  
Additive Manufacturing ◽  
Lattice Structure ◽  
Structure Optimization ◽  
Optimization Methods ◽  
Structure Design ◽  
Second Phase ◽  
Manufacturing Constraints ◽  
Ground Structure ◽  
Content Type ◽  
Optimization Framework

Purpose Methods to optimize lattice structure design, such as ground structure optimization, have been shown to be useful when generating efficient design concepts with complex truss-like cellular structures. Unfortunately, designs suggested by lattice structure optimization methods are often infeasible because the obtained cross-sectional parameter values cannot be fabricated by additive manufacturing (AM) processes, and it is often very difficult to transform a design proposal into one that can be additively designed. This paper aims to propose an improved, two-phase lattice structure optimization framework that considers manufacturing constraints for the AM process. Design/methodology/approach The proposed framework uses a conventional ground structure optimization method in the first phase. In the second phase, the results from the ground structure optimization are modified according to the pre-determined manufacturing constraints using a second optimization procedure. To decrease the computational cost of the optimization process, an efficient gradient-based optimization algorithm, namely, the method of feasible directions (MFDs), is integrated into this framework. The developed framework is applied to three different design examples. The efficacy of the framework is compared to that of existing lattice structure optimization methods. Findings The proposed optimization framework provided designs more efficiently and with better performance than the existing optimization methods. Practical implications The proposed framework can be used effectively for optimizing complex lattice-based structures. Originality/value An improved optimization framework that efficiently considers the AM constraints was reported for the design of lattice-based structures.

Simulation und Optimierung kombiniert/A simulation-based framework for operational optimization of industrial energy systems

2020 ◽  
Vol 110 (01-02) ◽  
pp. 12-17
Author(s):  
Niklas Panten ◽  
Heiko Ranzau ◽  
Thomas Kohne ◽  
Daniel Moog ◽  
Eberhard Abele ◽  
...  
Keyword(s):  
Synthetic Data ◽  
Cost Savings ◽  
Energy Systems ◽  
Decisive Role ◽  
Optimization Methods ◽  
Energy System ◽  
Significant Cost ◽  
Operational Optimization ◽  
Simulation Based ◽  
Industrial Energy

Die optimierte Betriebsweise von industriellen Energiesystemen ist eine Schlüsseltechnologie, um signifikante Kosteneinsparpotenziale durch Steigerung der Energieeffizienz und -flexibilität zu heben. Weil dabei eine Vielzahl dynamischer und stochastischer Einflüsse berücksichtigt werden müssen, spielt die Simulation des Energiesystems eine entscheidende Rolle. Zur Evaluierung unterschiedlicher Betriebsoptimierungsverfahren wird ein simulationsgestütztes Framework vorgestellt, welches bei KI (Künstliche Intelligenz)-Algorithmen unter anderem für das Anlernen mit synthetischen Daten verwendet werden kann.   The optimized operation of industrial energy systems is a key technology to unlock significant cost savings by increasing energy efficiency and flexibility. Since a variety of dynamic and stochastic influences must be considered, the simulation of the energy system plays a decisive role. A simulation-based framework is presented for evaluating various operational optimization methods, which can also be used for learning based on synthetic data with AI (artificial intelligence) algorithms.

Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering

2011 ◽  
Vol 1 (1) ◽  
pp. 57-79 ◽  
Author(s):  
A. Andrade-Campos
Keyword(s):  
Inverse Problems ◽  
Shape Optimization ◽  
Parameter Identification ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimum Shape ◽  
Optimization Framework ◽  
Search Optimization ◽  
Initial Geometry

The use of optimization methods in engineering is increasing. Process and product optimization, inverse problems, shape optimization, and topology optimization are frequent problems both in industry and science communities. In this paper, an optimization framework for engineering inverse problems such as the parameter identification and the shape optimization problems is presented. It inherits the large experience gain in such problems by the SiDoLo code and adds the latest developments in direct search optimization algorithms. User subroutines in Sdl allow the program to be customized for particular applications. Several applications in parameter identification and shape optimization topics using Sdl Lab are presented. The use of commercial and non-commercial (in-house) Finite Element Method codes to evaluate the objective function can be achieved using the interfaces pre-developed in Sdl Lab. The shape optimization problem of the determination of the initial geometry of a blank on a deep drawing square cup problem is analysed and discussed. The main goal of this problem is to determine the optimum shape of the initial blank in order to save latter trimming operations and costs.

Simulation-based optimization methods applied in hospital emergency departments: A systematic review

SIMULATION ◽  
2020 ◽  
Vol 96 (10) ◽  
pp. 791-806
Author(s):  
Milad Yousefi ◽  
Moslem Yousefi ◽  
Flavio S Fogliatto
Keyword(s):  
Emergency Departments ◽  
High Performance ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Hospital Emergency ◽  
Future Studies ◽  
Simulation Based ◽  
Performance Optimizations ◽  
Simulation Based Optimization ◽  
Hospital Emergency Departments

Since high performance is essential to the functioning of emergency departments (EDs), they must constantly pursue sensible and empirically testable improvements. In light of recent advances in computer science, an increasing number of simulation-based approaches for studying and implementing ED performance optimizations have become available in the literature. This paper aims to offer a survey of these works, presenting progress made on the topic while indicating possible pitfalls and difficulties in EDs. With that in mind, this review considers research studies reporting simulation-based optimization experiments published between 2007 and 2019, covering 38 studies. This paper provides bibliographic background on issues covered, generates statistics on methods and tools applied, and indicates major trends in the field of simulation-based optimization. This review contributes to the state of the art on ED modeling by offering an updated picture of the present state of the field, as well as promising research gaps. In general, this review argues that future studies should focus on increasing the efficiency of multi-objective optimization problems by decreasing their cost in time and labor.

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