Optimum structural design and robust active control using singular value constraints

This paper introduces a methodology for simultaneously designing a minimum weight structure and robust active controls to reduce vibrations in an aircraft structure due to external disturbances. The design problem is posed as a mathematical optimization problem with the principal objective function being the weight of the structure. The robust control design is achieved by specifying appropriate constraints on singular values of the closed-loop transfer matrices. The control approach selected for this purpose is based on designing a dynamic compensator that simultaneously minimizes the upper bound of a quadratic performance index H ₂ and the H norm of a disturbance transfer function of a multi-input/multi-output system. The controller can tolerate both real parameter uncertainty in the structural frequencies and damping, and unmodelled dynamics. The design variables are the crosspsectional areas of the structure and the parameters used in the design of a control system. The method was applied to three structures idealized with membrane elements, shear panels and bar elements with embedded actuators and sensors simulating an active flexible aircraft wing.     

Inverse design of directional solidification processes in the presence of a strong external magnetic field

A computational method for the design of directional alloy solidification processes is addressed such that a desired growth velocity ν_f under stable growth conditions is achieved. An externally imposed magnetic field is introduced to facilitate the design process and to reduce macrosegregation by the damping of melt flow. The design problem is posed as a functional optimization problem. The unknowns of the design problem are the thermal boundary conditions. The cost functional is taken as the square of the L₂ norm of an expression representing the deviation of the freezing interface thermal conditions from the conditions corresponding to local thermodynamic equilibrium. The adjoint method for the inverse design of continuum processes is adopted in this work. A continuum adjoint system is derived to calculate the adjoint temperature, concentration, velocity and electric potential fields such that the gradient of the L₂ cost functional can be expressed analytically. The cost functional minimization process is realized by the conjugate gradient method via the FE solutions of the continuum direct, sensitivity and adjoint problems. The developed formulation is demonstrated with an example of designing the boundary thermal fluxes for the directional growth of a germanium melt with dopant impurities in the presence of an externally applied magnetic field. The design is shown to achieve a stable interface growth at a prescribed desired growth rate. Copyright © 2001 John Wiley & Sons, Ltd.     

Multi-objective robust optimization design of a front-end underframe structure for a high-speed train

A multi-objective robust design optimization of a front-end underframe structure for application in high-speed trains is proposed and the structural parameter uncertainty is considered. A finite element model of the structure is developed and verified by dynamic impact experiments. The sensitivity analysis demonstrates that the thicknesses of the centre sill have significant influences on structural crushing behaviours. The specific energy absorption and the initial peak crushing force (F_p) are taken as optimization objectives. Compared with the baseline structure, the 6-sigma robust design shows that the F_p and the structural mass are reduced by 54.86% and 13.06%, respectively, and the robust optimum is more reliable. The 6-sigma robust optimal solution has an efficient energy-absorbing capacity while satisfying the design constraint. Thus, 6-sigma robust optimization can be applied for high-speed trains.     

Single- and multiobjective optimization problems in robust parameter design

This paper reviews the evolution of off-line quality engineering methods with respect to one or more quality criteria, and presents some recent results. The fundamental premises that justify the use of robust product/process design are established with an illustrative example. The use of designed experiments to model quality criteria and their optimization is briefly reviewed. The fact that most design-for-quality problems involve multiple quality criteria motivates the development of multiobjective optimization techniques for robust parameter design. Two situations are considered: one in which response surface models for the quality characteristics can be obtained using regression and considered over a continuous factor space, and one in which the problem scenario and the experiment permit only discrete parameter settings for the design factors. In the former scenario, a multiobjective optimization technique based on the reference-point method is presented; this technique also incorporates an inference mechanism to deal with uncertainty in the response surface models caused by finite, noisy data. In the discrete-factors scenario, an efficient method to reduce computational complexity for a class of models is presented.     

Graphene–Graphene Oxide Floating Gate Transistor Memory

A novel transparent, flexible, graphene channel floating‐gate transistor memory (FGTM) device is fabricated using a graphene oxide (GO) charge trapping layer on a plastic substrate. The GO layer, which bears ammonium groups (NH₃⁺), is prepared at the interface between the crosslinked PVP (cPVP) tunneling dielectric and the Al₂O₃ blocking dielectric layers. Important design rules are proposed for a high‐performance graphene memory device: i) precise doping of the graphene channel, and ii) chemical functionalization of the GO charge trapping layer. How to control memory characteristics by graphene doping is systematically explained, and the optimal conditions for the best performance of the memory devices are found. Note that precise control over the doping of the graphene channel maximizes the conductance difference at a zero gate voltage, which reduces the device power consumption. The proposed optimization via graphene doping can be applied to any graphene channel transistor‐type memory device. Additionally, the positively charged GO (GO–NH₃⁺) interacts electrostatically with hydroxyl groups of both UV‐treated Al₂O₃ and PVP layers, which enhances the interfacial adhesion, and thus the mechanical stability of the device during bending. The resulting graphene–graphene oxide FGTMs exhibit excellent memory characteristics, including a large memory window (11.7 V), fast switching speed (1 μs), cyclic endurance (200 cycles), stable retention (10⁵ s), and good mechanical stability (1000 cycles).     

Sensitivity and optimization for shape and non‐linear boundary conditions in thermal boundary elements

This paper is concerned with the minimization of functionals of the form ∫_Γ(b) f( h ,T( b, h )) dΓ( b ) where variation of the vector b modifies the shape of the domain Ω on which the potential problem, ?²T=0, is defined. The vector h is dependent on non‐linear boundary conditions that are defined on the boundary Γ. The method proposed is founded on the material derivative adjoint variable method traditionally used for shape optimization. Attention is restricted to problems where the shape of Γ is described by a boundary element mesh, where nodal co‐ordinates are used in the definition of b . Propositions are presented to show how design sensitivities for the modified functional ∫_Γ(b) f( h ,T ( b, h )) dΓ( b ) +∫_Ω(b) λ( b, h ) ?²T( b, h ) dΩ( b ) can be derived more readily with knowledge of the form of the adjoint function λ determined via non‐shape variations. The methods developed in the paper are applied to a problem in pressure die casting, where the objective is the determination of cooling channel shapes for optimum cooling. The results of the method are shown to be highly convergent. Copyright © 2002 John Wiley & Sons, Ltd.     

Using the sequential linear integer programming method as a post‐processor for stress‐constrained topology optimization problems

This paper deals with topology optimization of load‐carrying structures defined on discretized continuum design domains. In particular, the minimum compliance problem with stress constraints is considered. The finite element method is used to discretize the design domain into n finite elements and the design of a certain structure is represented by an n‐dimensional binary design variable vector. In order to solve the problems, the binary constraints on the design variables are initially relaxed and the problems are solved with both the method of moving asymptotes and the sparse non‐linear optimizer solvers for continuous optimization in order to compare the two solvers. By solving a sequence of problems with a sequentially lower limit on the amount of grey allowed, designs that are close to ‘black‐and‐white’ are obtained. In order to get locally optimal solutions that are purely {0, 1}ⁿ, a sequential linear integer programming method is applied as a post‐processor. Numerical results are presented for some different test problems. Copyright © 2008 John Wiley & Sons, Ltd.     

Metal–Organic-Framework-Based Photocatalysts Optimized by Spatially Separated Cocatalysts for Overall Water Splitting

Efficient charge separation and utilization are critical factors in photocatalysis. Herein, it is demonstrated that the complete spatial separation of oxidation and reduction cocatalysts enhances the efficacy of charge separation and surface reaction. Specifically, a Pt@NH₂-UiO-66@MnO_x (PUM) heterostructured photocatalyst with Pt and MnO_x as cocatalysts is designed for the optimization of the NH₂-UiO-66 photocatalyst. Compared with the pristine NH₂-UiO-66, Pt@NH₂-UiO-66 (PU), and NH₂-UiO-66@MnO_x (UM) samples, the PUM sample exhibits the highest hydrogen production activity. As cocatalysts, Pt favors trapping of electrons, while MnO_x tends to collect holes. Upon generation from NH₂-UiO-66, electrons and holes flow inward and outward of the metal–organic framework photocatalyst, accumulating on the corresponding cocatalysts, and then take part in the redox reactions. The PUM photocatalyst greatly prolongs the lifetime of the photogenerated electrons and holes, which favors the electron–hole separation. Furthermore, the PUM sample facilitates overall water splitting in the absence of sacrificial agents, thereby demonstrating its potential as a modification method of MOF-type semiconductors for the overall water-splitting reaction.     

Recombination Dynamics Study on Nanostructured Perovskite Light‐Emitting Devices

The field of organic–inorganic hybrid perovskite light‐emitting diodes (PeLEDs) has developed rapidly in recent years. Although the performance of PeLEDs continues to improve through film quality control and device optimization, little research has been dedicated to understanding the recombination dynamics in perovskite thin films. Likewise, little has been done to investigate the effects of recombination dynamics on the overall light‐emitting behavior of PeLEDs. Therefore, this study investigates the recombination dynamics of CH₃NH₃PbI₃ thin films with differing crystal sizes by measurement of fluence‐dependent transient absorption dynamics and time‐resolved photoluminescence. The aim is to find out the link between recombination dynamics and device behavior in PeLEDs. It is found that bimolecular and Auger recombination become more efficient as the crystal size decreases and monomolecular recombination rate is affected by the trap density of perovskite. By defining the radiative efficiency Φ(n), which relates to the monomolecular, bimolecular, and Auger recombination, the fundamental recombination properties of CH₃NH₃PbI₃ films are discerned in quantitative terms. These findings help us to understand the light emission behavior of PeLEDs. This study takes an important step toward establishing the relationship between film structure, recombination dynamics, and device behavior for PeLEDs, thereby providing useful insights toward the design of better perovskite devices.     

Interfacially Engineered Nanoporous Cu/MnOx Hybrids for Highly Efficient Electrochemical Ammonia Synthesis via Nitrate Reduction

Electrochemical reduction of nitrate to ammonia (NH₃) not only offers a promising strategy for green NH₃ synthesis, but also addresses the environmental issues and balances the perturbed nitrogen cycle. However, current electrocatalytic nitrate reduction processes are still inefficient due to the lack of effective electrocatalysts. Here 3D nanoporous Cu/MnO_x hybrids are reported as efficient and durable electrocatalysts for nitrate reduction reaction, achieving the NH₃ yield rates of 5.53 and 29.3 mg h⁻¹ mg_cat.⁻¹ with 98.2% and 86.2% Faradic efficiency in 0.1 m Na₂SO₄ solution with 10 and 100 mm KNO₃, respectively, which are higher than those obtained for most of the reported catalysts under similar conditions. Both the experimental results and density functional theory calculations reveal that the interface effect between Cu/MnO_x interface could reduce the free energy of rate determining step and suppress the hydrogen evolution reaction, leading to the enhanced catalytic activity and selectivity. This work provides an approach to design advanced materials for NH₃ production via electrochemical nitrate reduction.     

Optimal design of support parameters for minimum force transmissibility of a flexible rotor based on H∞ and H2 optimization methods

Rotating machinery support design with the aim of reducing the force transmitted to the foundation has significant importance regarding the various applications of this machinery. This article presents H_∞ and H₂ methods for calculating the optimum support flexibility and damping of flexible rotors to minimize force transmissibility in the vicinity of the rotor’s first critical speed. First, the governing equations for the Jeffcott rotor model mounted on flexible supports are derived and the optimal parameters for the supports are analytically achieved by H_∞ and H₂ optimization procedures. The proposed approach of the tuned damper support system is similar to that designed for dynamic vibration absorber optimization. The main objective of the H_∞ optimization is to minimize the force transmitted based on fixed-point theory and the mean square transmissibility of flexible rotor is minimized in the H₂ optimization design as analytical formulae. It is proven by numerical solution that the system optimization design can effectively minimize the force transmitted to the foundation. Comparison of two optimization than with H_∞.     

Crashworthiness design optimization using successive response surface approximations

 Finite Element (FE) method is among the most powerful tools for crash analysis and simulation. Crashworthiness design of structural members requires repetitive and iterative application of FE simulation. This paper presents a crashworthiness design optimization methodology based on efficient and effective integration of optimization methods, FE simulations, and approximation methods. Optimization methods, although effective in general in solving structural design problems, loose their power in crashworthiness design. Objective and constraint functions in crashworthiness optimization problems are often non-smooth and highly non-linear in terms of design variables and follow from a computationally costly (FE) simulation. In this paper, a sequential approximate optimization method is utilized to deal with both the high computational cost and the non-smooth character. Crashworthiness optimization problem is divided into a series of simpler sub-problems, which are generated using approximations of objective and constraint functions. Approximations are constructed by using statistical model building technique, Response Surface Methodology (RSM) and a Genetic algorithm. The approximate optimization method is applied to solve crashworthiness design problems. These include a cylinder, a simplified vehicle and New Jersey concrete barrier optimization. The results demonstrate that the method is efficient and effective in solving crashworthiness design optimization problems. Received: 30 January 2002 / Accepted: 12 July 2002 Sponsorship for this research by the Federal Highway Administration of US Department of Transportation is gratefully acknowledged. Dr. Nielen Stander at Livermore Software Technology Corporation is also gratefully acknowledged for providing subroutines to create D-optimal experimental designs and the simplified vehicle model.     

Root cause analysis strategy for robust design domain recognition

Design domain identification with desirable attributes (e.g. feasibility, robustness and reliability) provides advantages when tackling large-scale engineering optimization problems. For the purpose of dealing with feasibility robustness design problems, this article proposes a root cause analysis (RCA) strategy to identify desirable design domains by investigating the root causes of performance indicator variation for the starting sampling initiation of evolutionary algorithms. The iterative dichotomizer 3 method using a decision tree technique is applied to identify reduced feasible design domain sets. The robustness of candidate domains is then evaluated through a probabilistic principal component analysis-based criterion. The identified robust design domains enable optimal designs to be obtained that are relatively insensitive to input variations. An analytical example and an automotive structural optimization problem are demonstrated to show the validity of the proposed RCA strategy.     

Hysteresis‐Free 1D Network Mixed Halide‐Perovskite Semitransparent Solar Cells

The morphology of hybrid organic–inorganic perovskite films is known to strongly affect the performance of perovskite‐based solar cells. CH₃NH₃PbI_3‐xCl_x (MAPbI_3‐xCl_x) films have been previously fabricated with 100% surface coverage in glove boxes. In ambient air, fabrication generally relies on solvent engineering to obtain compact films. In contrast, this work explores the potential of altering the perovskites microstructure for solar cell engineering. This work starts with CH₃NH₃PbI_3‐xCl_x, films with grain morphology carefully controlled by varying the deposition speed during the spin‐coating process to fabricate efficient and partially transparent solar cells. Devices produced with a CH₃NH₃PbI_3‐xCl_x film and a compact thick top gold electrode reach a maximum efficiency of 10.2% but display a large photocurrent hysteresis. As it is demonstrated, the introduction of different concentrations of bromide in the precursor solution addresses the hysteresis issues and turns the film morphology into a partially transparent interconnected network of 1D microstructures. This approach leads to semitransparent solar cells with negligible hysteresis and efficiencies up to 7.2%, while allowing average transmission of 17% across the visible spectrum. This work demonstrates that the optimization of the perovskites composition can mitigate the hysteresis effects commonly attributed to the charge trapping within the perovskite film.     

The effect of chemical surfactants on the absorption performance during NH3/H2O bubble absorption process

The objectives of this paper are to visualize the bubble behavior by shadow graphic method, to examine the effect of surfactants on the bubble type absorption, and to find the optimal conditions to design highly effective compact absorber for NH₃/H₂O absorption system. The initial concentrations of NH₃/H₂O solution and the kinds and the concentrations of surfactants are considered as key parameters. By measuring the absorption rate for each condition, two effects of the addition of surfactants, the Marangoni and the barrier effect, are compared with each other. The results show that the addition of surfactant enhances the absorption performance up to 4.81 times. The experimental correlations of the effective absorption ratio for each surfactant, 2-ethyl-1-hexanol, n-octanol, and 2-octanol, are suggested within ±15, ±10, and ±10%, respectively.     

Application of a conservation integral to an interface crack interacting with singularities

A mutual integral, which has the conservation property is applied to the problem of an interfacial crack. The stress intensity factors K ₁, K ₂, K ₃ and T-stress for the problem in an infinite medium are easily obtained by using the mutual integral without solving the boundary value problem. In doing so the auxiliary solutions are required and they are taken from the known asymptotic solutions. This method is amenable to numerical evaluation of the stress intensity factors and T-stress if the interfacial crack in a finite medium is considered.     

Evolutionary design of a generalized polynomial neural network for modelling sediment transport in clean pipes

To determine the minimum velocity required to prevent sedimentation, six different models were proposed to estimate the densimetric Froude number (Fr). The dimensionless parameters of the models were applied along with a combination of the group method of data handling (GMDH) and the multi-target genetic algorithm. Therefore, an evolutionary design of the generalized GMDH was developed using a genetic algorithm with a specific coding scheme so as not to restrict connectivity configurations to abutting layers only. In addition, a new preserving mechanism by the multi-target genetic algorithm was utilized for the Pareto optimization of GMDH. The results indicated that the most accurate model was the one that used the volumetric concentration of sediment (C_V), relative hydraulic radius (d/R), dimensionless particle number (D_gr) and overall sediment friction factor (λ_s) in estimating Fr. Furthermore, the comparison between the proposed method and traditional equations indicated that GMDH is more accurate than existing equations.     

Microenvironment Engineering to Promote Selective Ammonia Electrosynthesis from Nitrate over a PdCu Hollow Catalyst

The electrosynthesis of recyclable ammonia (NH₃) from nitrate under ambient conditions is of great importance but still full of challenges for practical application. Herein, an efficient catalyst design strategy is developed that can engineer the surface microenvironment of a PdCu hollow (PdCu-H) catalyst to confine the intermediates and thus promote selective NH₃ electrosynthesis from nitrate. The hollow nanoparticles are synthesized by in situ reduction and nucleation of PdCu nanocrystals along a self-assembled micelle of a well-designed surfactant. The PdCu-H catalyst shows a structure-dependent selectivity toward the NH₃ product during the nitrate reduction reaction (NO₃⁻RR) electrocatalysis, enabling a high NH₃ Faradaic efficiency of 87.3% and a remarkable NH₃ yield rate of 0.551 mmol h⁻¹ mg⁻¹ at -0.30 V (vs reversible hydrogen electrode). Moreover, this PdCu-H catalyst delivers high electrochemical performance in the rechargeable zinc-NO₃⁻ battery. These results provide a promising design strategy to tune catalytic selectivity for efficient electrosynthesis of renewable NH₃ and feedstocks.     

Stochastic inverse heat conduction using a spectral approach

An adjoint‐based functional optimization technique in conjunction with the spectral stochastic finite element method is proposed for the solution of an inverse heat conduction problem in the presence of uncertainties in material data, process conditions and measurement noise. The ill‐posed stochastic inverse problem is restated as a conditionally well‐posed L₂ optimization problem. The gradient of the objective function is obtained in a distributional sense by defining an appropriate stochastic adjoint field. The L₂ optimization problem is solved using a conjugate‐gradient approach. Accuracy and effectiveness of the proposed approach is appraised with the solution of several stochastic inverse heat conduction problems. Copyright © 2004 John Wiley & Sons, Ltd.