Design Optimization Environment Research Articles

Power Transformer Characterization and Design Optimization Environment

Power Transformers are essential part of all AC Power Grids. This work proposes a characterization and design optimization environment for Power Transformers to increase efficiency while decreasing core volume. It utilizes a Finite-Element State-Space models in conjunction with Artificial Neural Networks and Particle Swarm Optimization. A case study of a 42 MVA, 118/13.8kV distribution power transformer was conducted, and transformer performance characteristics were compared to test data for verification. Next, the optimization environment was used to decrease the transformer volume and improve its efficiency. In addition, the Taguchi orthogonal arrays method was used to reduce computational costs.

Dynamic Wireless Power Transfer Characterization Environment

Dynamic Wireless Power Transfer is one of the emerging technologies for electric vehicle charging applications. This paper presents an electromagnetic Finite Element-State Space based characterization environment to predict the performance characteristics of DWPT systems. This environment is applied to characterize several configurations of a prototype DWPT system utilizing multi-ground transmitter coils and a vehicle receiver coil. The proposed environment would be useful as a characterization tool in a design process and could be used as a system identifier in a design optimization environment for this class of devices.

Development of an Open-Source Autonomous Computational Fluid Dynamics Meta-Modeling Environment for Small-Scale Combustor Optimization

Abstract This work presents an open-source autonomous computational fluid dynamics (CFD) metamodeling environment (OpenACME) for small-scale combustor design optimization in a deterministic and continuous design space. OpenACME couples several object-oriented programing open-source codes for conjugate-heat transfer, steady-state, multiphase incompressible Reynolds averaged Navier-Stokes CFD-assisted engineering design metamodeling. There are fifteen design variables. Nonparametric rank regression (NPRR), global sensitivity analyses (GSA), and single-objective (SOO) optimization strategies are evaluated. The Euclidean distance (single-objective criterion) between a design point and the utopic point is based on the multi-objective criteria: combustion efficiency (η) maximization and pattern factor (PF), critical liner area factor (Acritical ), and total pressure loss (TPL) minimization. The SOO approach conducts Latin hypercube sampling (LHS) for reacting flow CFD for subsequent local constraint optimization by linear interpolation. The local optimization successfully improves the initial design condition. The SOO approach is useful for guiding the design and development of future gas turbine combustors. NPRR and GSA indicate that there are no leading-order design variables controlling η, pattern factor (PF), Acritical , and TPL. Therefore, interactions between design variables control these output metrics because the output design space is inherently nonsmooth and nonlinear. In summary, OpenACME is developed and demonstrated to be a viable tool for combustor design metamodeling and optimization studies.

Electromagnetic–AI-Based Design Optimization of SynRM Drives

Characterization modules in electric machines and drives design optimization environments typically involve the use of electromagnetic finite element-state space models that require large number of iterations and computational time. It is shown in this work that the utilization of a Taguchi orthogonal arrays method in conjunction with a particle swarm optimization (PSO), search algorithm in a design optimization case study of a synchronous reluctance motor (SynRM) drive, resulted in about 80% reduction of computational time.

Automated and interactive evaluation of welding producibility in an multidisciplinary design optimization environment for aircraft components

The automation capabilities and virtual tools within engineering disciplines, such as structural mechanics and aerodynamics, enable efficient Multidisciplinary Design Optimization (MDO) approaches to evaluate and optimize the performance of a large number of design variants during early design stages of aircraft components. However, for components that are designed to be welded, in which multiple functional requirements are satisfied by one single welded structure, the automation and simulation capabilities to evaluate welding-producibility and predict welding quality (geometrical deformation, weld bead geometrical quality, cracks, pores, etc) are limited. Besides the complexity of simulating all phenomena within the welding process, one of the main problems in welded integrated components is the existing coupling between welding quality metrics and product geometry. Welding quality can vary for every new product geometrical variant. Thus, there is a need of analyzing rapidly and virtually the interaction and sensitivity coefficients between design parameters and welding quality to predict welding producibility. This paper presents as a result an automated and interactive welding-producibility evaluation approach. This approach incorporates a data-based of welding-producibility criteria, as well as welding simulation and metamodel methods, which enable an interactive and automated evaluation of welding quality of a large number of product variants. The approach has been tested in an industrial use-case involving a multidisciplinary design process of aircraft components. The results from analyzing the welding-producibility of a set of design variants have been plotted together with the analysis results from other engineering disciplines resulting in an interactive tool built with parallel coordinate graphs. The approach proposed allows the generation and reuse of welding producibility information to perform analyses within a big spectrum of the design space in a rapid and interactive fashion, thus supporting designers on dealing with changes and taking fact-based decisions during the multidisciplinary design process.

Taguchi-EM-AI Design Optimization Environment for SynRM Drives in Traction Applications

Multi-objective design optimization environments are used for electric vehicles and other traction applications to arrive at efficient motor drives. Typically, the environment includes characterization modules that involve the use of Electromagnetic Finite Element and State-Space models that require large number of iterations and computational time. This work proposes the utilization of a Taguchi orthogonal arrays method in conjunction with a Particle Swarm Optimization search algorithm to reduce computational time needed in the design optimization of electric motors for traction applications. The effectiveness of the Taguchi method in conjunction with the optimization environment is demonstrated in a case study involving a prototype of a Synchronous Reluctance Motor drive system.

Applying a distributed collaborative MDAO environment to study the power matching of the propulsion system and the on-board electrified systems for advanced regional and short- to medium-range jetliners

ABSTRACTThis paper deals with the study of the power matching of the propulsion system and on-board systems changing the on-board systems’ electrification level. In particular, four system architectures have been studied, each one with a different level of electrification starting from the More Electric Aircraft (MEA) to the All Electric Aircraft (AEA) systems. The mass and the power requirement of each system architectures have been analysed together with the change in engine specific fuel consumption. Then, these results have been used to quantify the influences of engine and systems power matching to the entire aircraft. In particular, the beneficial effect of system electrification has been evaluated as an increment of aircraft range. Moreover, two reference aircraft – a regional jet and a short/medium range liner – have been selected to understand the variance of the power matching changing aircraft dimensions and mission range. The study is carried out using a distributed and collaborative Multi-Disciplinary Design Analysis and Optimization (MDAO) environment. The results show a beneficial effect of systems electrification on systems mass and engine specific fuel consumption. At aircraft level, the results point out an increment of aircraft range up to 7.7% with a different trend for the two studied cases.

Low-boom low-drag optimization in a multidisciplinary design analysis optimization environment

This paper introduces a multidisciplinary design analysis and optimization environment called GENUS. The GENUS aircraft design environment's key features are that it is modular, expandable, flexible, independent, and sustainable. This paper discusses the application of this environment to the design of supersonic business jets (SSBJs). SSBJs are regarded as the pioneers of the next generation of supersonic airliners. Methodologies appropriate to SSBJs are developed in the GENUS environment. The Mach plane cross-sectional area is calculated based on the parametric geometry model. PANAIR is integrated to perform automated aerodynamic analysis. The drag coefficient is corrected by the Harris wave drag calculation and form factor method. The sonic boom intensity is predicted by the wave form parameter method, which is validated by PCBoom. The Cranfield E-5 SSBJ is chosen as a baseline configuration. Low-boom and low-drag optimization are carried out based on this configuration. Through the optimization, the sonic boom intensity is mitigated by 71.36% and the drag decreases by 20.65%.

Proof-of-concept analysis of a supplemental solar power system for aircraft

PurposeThis paper aims to analyze the viability of a solar power system as a supplemental power source for commercial and business aircraft.Design/methodology/approachFirst, a model is established to estimate the potential available power from suitable aircraft surfaces for various meteorological conditions, ground and flight mission characteristics. A proposed aircraft system architecture and an associated parametric conceptual sizing model are presented. This supplemental solar power system sizing model is integrated into an aircraft multidisciplinary design optimization environment to evaluate the aircraft-level impact on mission fuel burn. A parametric study for a business jet aircraft is performed to analyze various solar cell types and power densities for converters. Trade-off studies are performed between efficiency and weight.FindingsConsidering today’s efficiency and power-to-weight ratio of the system components, overall fuel burn reduction can be achieved. Therefore, the technology development work can start now to target short to mid-term applications. In addition, promising system integration scenarios are identified, such as the use of solar power for autonomous operation of the air conditioning system on ground, which yield potential further benefit. In conclusion, a supplemental solar power system seems a promising candidate for more efficient aircraft operation.Originality/valueThe presented novel supplemental solar power system architecture concept and its foreseen aircraft integration show potential benefits for near term applications. The results show that the break even for this technology is already reached and therefore build the foundation to further investigate the technology integration challenges. Clear directions for future research and development are outlined enabling the advancement of the technology readiness level.

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 2

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 2

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 1

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones‟ algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

Aeroelastic Applications of a Variable-Geometry Raked Wingtip

This study investigates the effects of a variable-geometry raked wingtip on the aeroelastic behavior and the maneuverability of transport aircraft with very large aspect-ratio truss-braced wings. These truss-braced wing designs are obtained from the multidisciplinary design optimization environment presented here while minimizing the fuel burn of a double-aisle aircraft having a flight mission similar to that of a Boeing 777-200 long-range aircraft. The wingtip can be swept forward and aft relative to the wing by a novel control effector mechanism. Results show that a variable-geometry raked wingtip can be used to achieve required roll control by judiciously sweeping it relative to the wing at various flight conditions. It has an added benefit that it can also be used for flutter avoidance. Such benefits of the variable-geometry raked wingtip allow the operation of truss-braced wing configurations, which have up to 10% lower fuel burn than comparable optimized conventional cantilever wing designs. Without the variable-geometry raked wingtip, such configurations fail to meet the required flutter speed and roll control capability. The variable-geometry raked wingtip is thus an enabling technology for truss-braced wing aircraft and other large aspect-ratio configurations.

Reliability analysis method based on determination of the performance function’s PDF using the univariate dimension reduction method

In addition to traditional motivations for application of the reliability analysis, significant growth of the structural design optimization utilization can be observed nowadays, where minimization of the structural weight and maximization of the structural safety are the most common objectives. Application of the existing reliability analysis methods in the context of the multi-criteria optimization of complex structures (e.g. ships), which are characterized by a large number of the design and random variables, is very time consuming due to extremely large number of the pertinent calculations. Consequently, an efficient reliability analysis method is proposed within the scope of this article. Proposed method provides very accurate results within significantly lower computational timeframes with respect to the existing reliability analysis methods, which makes it appropriate for application in computationally very demanding reliability based design optimization (RBDO) environment.

EM-Taguchi Module for Characterization of WAD

Accurate performance characterization is critical in a design optimization environment. The electromagnetic (EM) design optimization of an ocean wave linear generator buoy or wave activated device (WAD) requires the use of large number of finite element-state space, design evaluations due to the stochastic behavior of the wave and the nonlinear nature of the device. This paper proposes the utilization of Taguchi orthogonal arrays method to reduce the EM, computational time needed to accurately characterize a WAD performance corresponding to a sea wave profile and for use in a design optimization environment.

On the quasi-steady aerodynamics of normal hovering flight part II: model implementation and evaluation

This paper introduces a generic, transparent and compact model for the evaluation of the aerodynamic performance of insect-like flapping wings in hovering flight. The model is generic in that it can be applied to wings of arbitrary morphology and kinematics without the use of experimental data, is transparent in that the aerodynamic components of the model are linked directly to morphology and kinematics via physical relationships and is compact in the sense that it can be efficiently evaluated for use within a design optimization environment. An important aspect of the model is the method by which translational force coefficients for the aerodynamic model are obtained from first principles; however important insights are also provided for the morphological and kinematic treatments that improve the clarity and efficiency of the overall model. A thorough analysis of the leading-edge suction analogy model is provided and comparison of the aerodynamic model with results from application of the leading-edge suction analogy shows good agreement. The full model is evaluated against experimental data for revolving wings and good agreement is obtained for lift and drag up to 90° incidence. Comparison of the model output with data from computational fluid dynamics studies on a range of different insect species also shows good agreement with predicted weight support ratio and specific power. The validated model is used to evaluate the relative impact of different contributors to the induced power factor for the hoverfly and fruitfly. It is shown that the assumption of an ideal induced power factor (k = 1) for a normal hovering hoverfly leads to a 23% overestimation of the generated force owing to flapping.

Quantitative Assessment of Multidisciplinary Design Models for Expendable Launch Vehicles

The research effort described in this paper is centered on the development and quantitative assessment of a multidisciplinary design optimization environment for the early design phases of expendable launch vehicles. The focus of the research is on the engineering modeling aspects, with the goal of evaluating in detail the accuracy of engineering-level methods for launch vehicle design, both in terms of disciplinary errors (e.g., engine specific impulse evaluation) and of system-level sensitivities, to assess their applicability to industrial early design. Although aerospace applications of multidisciplinary design optimization can be found in literature, the systematic assessment of the models’ accuracies to the extent described in the present research is a rather new endeavor, which is critical for the advancement of this field. In fact, the widespread industrial application of multidisciplinary design optimization has often been obstructed by the difficulty of finding a suitable compromise between the analysis fidelity and computational cost. Considerable effort was therefore spent on a careful, incremental modeling process, with the purpose of overcoming such an obstacle. As a result, although it is clear that the development and tuning of a reliable multidisciplinary environment is a particularly complex and challenging task, detailed investigations showed that a good compromise can indeed be achieved for the expendable launch vehicles application. In particular, the accuracy on the payload performance was assessed to be in the order of 12% for a computational time per design cycle, allowing one to obtain physically sound design changes through the multidisciplinary design optimization, even exploiting only fast engineering-level methods.

An integrated framework for solid rocket motor grain design optimization

Traditional grain designs, which identify the best combination of geometrical parameters to improve the grain performance and meet the flight-mission requirements, are often performed manually. In this article, an integrated framework is presented to perform the design optimization of solid rocket motor propellant grains. In the proposed framework, the level set method is adapted to solid propellant burnback analysis and this technique does not have any restriction on the grain configuration and is capable of handling grains of multi-stage and various burning forms. Along with the level set method, a dedicated algorithm is developed using application programming interfaces of commercial computer-aided design software to transform the initial grain shape into a special data file that can be fed to the level set codes to activate the burnback analysis. Moreover, a hybrid optimization method incorporating genetic algorithm and sequential quadratic programming is exploited to improve the grain design efficiency. Finally, two case studies have been performed to verify the feasibility and general-purpose characteristics of the proposed grain design optimization environment. The results obtained show that the proposed design framework facilitates the grain optimization process and various grain design requirements can be met. The design cycle has been remarkably reduced because of the introduction of hybrid optimization method.

Multifidelity, Multistrategy, and Multidisciplinary Design Optimization Environment

Multifidelity, Multistrategy, and Multidisciplinary Design Optimization Environment

Optimization‐driven design of dies for profile extrusion: Parameterization, strategy, and performance

AbstractA computational design optimization environment is developed, handling, for the first time, streamline dies used for profiles in unplasticized polyvinyl chloride (uPVC) having multiple complex features, as well as simpler designs. Die cavity cross sections are described by planar contours, such as the cutting paths for wire electrical discharge machining of the plates from which streamline profile dies are constructed. Contours are parameterized using key points, and by joining the contours with ruled surfaces, the three‐dimensional geometry can be reconstructed. For the optimization a developed flow analysis on each die cross section is used with the avoid‐cross‐flow strategy. Cross sections are partitioned and the die is balanced to obtain the required flow rate through each. A robust and efficient parallel decoupled optimization strategy is developed. In application to a uPVC window profile, five cross sections were optimized. The number of design variables on each ranged from 2 to 46, and the cross section optimizations converged within one to seven cycles. Compared with the work of an experienced designer making manual changes to the computer‐aided design model, guided by computational fluid dynamics analyses, the design quality was comparable or better and computational demands similar; however, the time required from the designer was reduced seven times. POLYM. ENG. SCI., 2013. © 2012 Society of Plastics Engineers

BIM-Centric Daylight Profiler for Simulation (BDP4SIM): A methodology for automated product model decomposition and recomposition for climate-based daylighting simulation

Flexible problem formulation is required for product model-based thermal analysis using multidisciplinary design optimization (MDO) environments for speed, accuracy, scalability, and cost-effectiveness in the Architecture, Engineering, and Construction (AEC) industry. The integration of daylighting simulation into an MDO process, however, presents several implementation challenges. In current practice, the process of an architect, engineer, or daylighting consultant to determine how to analyze a given building design for daylighting performance is frequently subjective, time-consuming, and inconsistent. Furthermore, long simulation time requirements for daylighting significantly hinder the realization of many benefits from MDO. The determination of which spaces in a building are sufficiently different to warrant an independent daylighting analysis is based primarily on building physics, building design criteria, and operating schedules (e.g. occupancy schedules). This characteristic of daylighting analysis creates the opportunity to develop intelligent mechanisms to automate the identification of the building spaces for analysis using performance-based methods, simulation of spatial results, and the scaling of spatial simulation results to whole building performance metrics in a fraction of the time it takes in current practice. Such methods would result in improved speed, accuracy, scalability, and cost-effectiveness for MDO- and non-MDO-based daylighting simulation. Currently, no such methods exist in literature or in practice. This paper fills these gaps by presenting a methodology for automated product model decomposition and recomposition for climate-based daylighting simulation using Radiance. The authors validate the research with the method's application to several test cases and a large federal office building industry case study.