Structural Acoustic Optimization of a Composite Cylindrical Shell Using FEM/BEM

Structural acoustic optimization is performed on an eight-ply graphite epoxy cylindrical shell using finite/boundary element tools. The shell is subject to acoustic monopole source excitation. The optimization objective is to minimize the sum of the squared acoustic pressure amplitudes inside the shell. The ply angles are used as design variables and allowed to vary over the length of the cylinder. Four initial design states are selected for optimization. Reductions in the objective ranged from approximately 1 dB to 10 dB. In general, it was observed that greater longitudinal variation in the optimized design state corresponded to a lower final objective.

The vocal function of 20 speech-disordered subjects with idiopathic Parkinson's disease (PD) was assessed using both perceptual and instrumental techniques. The instrumental analysis included electroglottography and the use of a computerized airflow/air pressure analysis system (Aerophone II). Variables measured included parameters of the Lx waveform (F0, duty cycle, and closing time) as well as aerodynamic parameters such as subglottal pressure, laryngeal airway resistance, average phonatory sound pressure level, phonatory flow rate and ad/abduction rate. Values were compared to those recorded from a group of non-neurologically impaired controls matched for age and sex. Perceptual assessment revealed that 89·5% of the PD subjects exhibited deviant laryngeal features. None of the electroglottography (EGG) parameters differed significantly between the PD and control groups. However four of the five aerophone parameters did differentiate between the two subject groups. The PD group was characterized by higher levels of glottal resistance than the control subjects and lower values for subglottal pressure, average phonatory sound pressure level and phonatory flow rate. A cluster analysis based on the EGG and aerodynamic measures identified the presence of four subgroups, two which represented different expressions of hyperfunction of the larynx within the PD group. The results are discussed with reference to the expected effects of PD on vocal function.

Long-term noise exposures and cardiovascular diseases mortality: A study in 5 U.S. states

This study presents the underactuated design of a tendon-driven bioinspired robotic gripper for the stable grasping. In this study, kinematic modeling of the bioinspired underactuated robotic gripper has been proposed and optimal design variables have been found out using multi-objective evolutionary algorithms. The obtained anthropometric data of the human hand is taken as the dimension range of the input design variables in the design optimization problem. In this study, the kinematic model of the proposed gripper is obtained, and the structural multi-objective optimization problem is formulated in the static condition of the gripper. Three fitness functions have developed from the contact forces, and some geometric constraints are considered for solving the proposed multi-objective optimization problem using multi-objective grey wolf optimization algorithm.

The aim of this paper is to develop a general methodology for the optimum design of magnetic head sliders in improving the spacing characteristics between a slider and disk surface under static and dynamic operating conditions of hard disk drives and to present an application of the methodology to the IBM 3380-type slider design. To generate the optimal design variables, the objective function is defined as the weighted sum of the minimum spacing, the maximum difference in the spacing due to variation of the radial location of the head, and the maximum amplitude ratio of the slider motion. Slider rail width, taper length, taper angle, suspension position, and preload are selected as the design variables. Before the optimization of the head, the effects of these five design variables on the objective function are examined by a parametric study, and then the optimum design variables are determined by applying the hybrid optimization technique, combining the direct search method and successive quadratic programming. From the obtained results, the effectiveness of optimum design on the spacing characteristics of magnetic heads is clarified. [S0742-4787(00)03701-2]

Fiber path optimization based on a family of curves in composite laminate with a center hole

In the moving-morphable-component topology optimization, morphable components are introduced as a geometrical model mapped onto the background finite elements, and their shape parameters are utilized as design variables for topology optimization. Whereas a complex curved geometry ensuring C1 continuity can be generated using existing curved components, the component curvatures cannot be selected as design variables in the existing methods; thus geometric constraints associated with curvatures cannot also be directly imposed. To address this issue, this study proposes a curvature-based morphable component by introducing the curvilinear geometry representation in the strain-based beam formulation. Since the proposed component is parameterized by curvatures using the curvilinear equation, the component curvatures can be utilized as the design variables. This allows for directly imposing curvature constraints on structural members, thereby accounting for the manufacturability of an optimal topology. It is demonstrated that a symmetric placement of the design variables using the midpoint curvilinear coordinate system is critical in ensuring convergence of the proposed curvature-based component optimization. The symmetric curvature component is further extended to account for multiple curvatures within a single component while ensuring C1 continuity. Several examples are presented to demonstrate the benefits of the proposed multicurvature component for topology optimization.

In this study, a full-scale finite element vehicle model of a 1996 Dodge Neon is used in simulating two types of vehicle crashes, offset-frontal and side impacts. Based on an analysis of the vehicle's internal energy absorption under both impacts, twenty-one components are selected and represented by thirteen design variables for the multidisciplinary optimization including the weight, intrusion distance, and energy absorptions. The second-order polynomials are used in creating the metamodels for the objective and constraint functions. The optimization results show that the weight can be significantly reduced while decreasing the intrusion distance and keeping the original level of energy absorption. With the successfully implemented optimization scheme, a set of non-dominated (tradeoff) solutions is obtained and the final design can be selected based on the designer's preference. A simulation of 100 ms offset-frontal impact using LS-DYNA MPP v970 takes approximately 17 hours with 36 processors on an IBM Linux Cluster with Intel Pentium III 1.266 GHz processors and 607.5 GB RAM. A simulation of 100 ms side impact takes approximately 29 hours with the same condition as that of the offset-frontal simulation.

Catalytic reforming of naphtha occupies an important issue in refineries for obtaining high octane gasoline and aromatic compounds, which are the basic materials of petrochemical industries. In this study, a novel of design parameters for industrial continuous catalytic reforming reactors of naphtha is proposed to increase the aromatics and hydrogen productions. Improving a rigorous mathematical model for industrial catalytic reactors of naphtha is studied here based on industrial data applying a new kinetic and deactivation model. The optimal design variables are obtained utilizing the optimization process in order to build the model with high accuracy and such design parameters are then applied to get the best configuration of this process by new design variables. New results related to aromatic and hydrogen production have been obtained (the highest hydrogen and aromatic) in comparison with those reported in the literature and with the conventional method.

SummaryIn this work, we investigate the efficient estimation of the optimal design variables that maximize net present value (NPV) for the life-cycle production optimization during a single-well carbon dioxide (CO2) huff-n-puff (HnP) process in unconventional oil reservoirs. A synthetic unconventional reservoir model based on Bakken Formation oil composition is used. The model accounts for the natural fracture and geomechanical effects. Both the deterministic (based on a single reservoir model) and robust (based on an ensemble of reservoir models) production optimization strategies are considered. The injection rate of CO2, the production bottomhole pressure (BHP), the duration of injection and the production periods in each cycle of the HnP process, and the cycle lengths for a predetermined life-cycle time can be included in the set of optimum design (or well control) variables. During optimization, the NPV is calculated by a machine learning (ML) proxy model trained to accurately approximate the NPV that would be calculated from a reservoir simulator run. Similar to the ML algorithms, we use both least-squares (LS) support vector regression (SVR) and Gaussian process regression (GPR). Given a set of forward simulation runs with a commercial compositional simulator that simulates the miscible CO2 HnP process, a proxy is built based on the ML method chosen. Having the proxy model, we use it in an iterative-sampling-refinement optimization algorithm directly to optimize the design variables. As an optimization tool, the sequential quadratic programming (SQP) method is used inside this iterative-sampling-refinement optimization algorithm. Computational efficiencies of the ML proxy-based optimization methods are compared with those of the conventional stochastic simplex approximate gradient (StoSAG)-based methods. Our results show that the LS-SVR- and GPR-based proxy models are accurate and useful in approximating NPV in the optimization of the CO2 HnP process. The results also indicate that both the GPR and LS-SVR methods exhibit very similar convergence rates, but GPR requires 10 times more computational time than LS-SVR. However, GPR provides flexibility over LS-SVR to access uncertainty in our NPV predictions because it considers the covariance information of the GPR model. Both ML-based methods prove to be quite efficient in production optimization, saving significant computational times (at least 4 times more efficient) over a stochastic gradient computed from a high-fidelity compositional simulator directly in a gradient ascent algorithm. To our knowledge, this is the first study presenting a comprehensive review and comparison of two different ML-proxy-based optimization methods with traditional StoSAG-based optimization methods for the production optimization problem of a miscible CO2 HnP.

A surrogate model based aerodynamic shape optimization method applied to the wind deflector of a tractor-trailer in crosswind is presented in this paper. The aerodynamic drag coefficient and handling stability of the tractor-trailer subjected to crosswinds is analyzed. The numerical results show that the wind deflector can influence drag coefficient and the lateral displacement of the tractor-trailer in crosswinds in great degree. Four parameters are used to describe the wind deflector geometry: Width, Length, Height and Angle. A 30-level design of experiments (DOE) study using the optimal Latin hypercube method is conducted to analyze the sensitivity of the design variables and build a database to set up the surrogate model. The surrogate model is constructed based on the Kriging interpolation technique. The fitting precision of the surrogate model is examined using a computational fluid dynamics (CFD) and multi-body dynamics and certified using a surrogate model simulation. Finally, multi-island genetic algorithm is used to optimize the shape of the wind deflector based on the surrogate model. The maximum tolerance between the results of the CFD and multi-body dynamics simulation and the surrogate model is only 2.02 %. When using the optimal design variables, the aerodynamics drag coefficient decreases maximum by 6.23 % and the lateral displacement decreases maximum by 4.67 %.KeywordsMultidisciplinary optimizationVehicle aerodynamicsMulti-body dynamicsCrosswind

Multi-objective optimization of corrugated tube inserted with multi-channel twisted tape using RSM and NSGA-II

Material optimization of tri-directional functionally graded plates by using deep neural network and isogeometric multimesh design approach

SummaryThis article proposes an efficient approach for solving three‐dimensional (3D) topology optimization problem. In this approach, the number of design variables in optimization as well as the number of degrees of freedom in structural response analysis can be reduced significantly. This is accomplished through the use of scaled boundary finite element method (SBFEM) for structural analysis under the moving morphable component (MMC)‐based topology optimization framework. In the proposed method, accurate response analysis in the boundary region dictates the accuracy of the entire analysis. In this regard, an adaptive refinement scheme is developed where the refined mesh is only used in the boundary region while relating coarse mesh is used away from the boundary. Numerical examples demonstrate that the computational efficiency of 3D topology optimization can be improved effectively by the proposed approach.

Acoustic modeling of sequential spaces: A parametric study