Optimization Of Mechanical Systems Research Articles

Enhancing Structural Vibration Damping in Marine Machinery: A Comprehensive Numerical Investigation with Modal and Harmonic Analysis

This article presents a comprehensive study on the damping of vibrations in a motor-pump assembly using viscoelastic and constrained layer damping treatments. The assembly's structural model, designed using SolidWorks software, is subjected to modal and harmonic analyses in ANSYS. The primary goal is to mitigate vibration amplitudes originating from the motor and pump to enhance the assembly's operational performance. Three damping treatments are investigated: Free Layer Damping (FLD), Sandwich Constrained Layer Damping (CLD), and a novel Multilayer CLD approach. The viscoelastic material is modeled using the Prony series method, and its properties are incorporated into the finite element analysis Results demonstrate that the application of damping treatments significantly reduces vibration amplitudes compared to the untreated structure. Among the treatments, the Multilayer CLD approach exhibits the highest damping efficiency, reducing the maximum amplitude by approximately 52% compared to the base structure. The study showcases the advantages of utilizing viscoelastic and constrained layer damping techniques for enhancing vibration control and operational stability in industrial assemblies. The research findings contribute to the field of structural dynamics and vibration control, offering valuable insights into the design and optimization of mechanical systems subjected to dynamic loads. This study opens avenues for further research and practical applications aimed at improving the performance and reliability of motor-pump assemblies and similar industrial equipment.

A More Accurate Systems Modelling and Simulation Framework in Design and Optimization of A System During the Conceptual Phase

Modelling and simulation of complex mechanical systems involving multi-simulation environment, with great accuracy is essential as part of the conceptual design phase of a system under design. The co-simulation between system level model with various subsystems based on Model Based Design (MBD) and component level model is a perfect example. These mathematical models have distinct features such as the type of differential equations used to represent its physics, boundary conditions etc. In this study we use MBD methodology to develop a simulation model that can drive product development and optimization of mechanical systems. We also incorporate a 3-D Computational Fluid Dynamics (CFD) model as one of its subsystem into the System Level (SL) model architecture. This is done by creating a co-simulation interface between these two different modelling environments and exchange boundary conditions via a specific interface. The interaction between multi-domain models through system simulation together with the detailed fluid flow and thermal analysis of the component through CFD is finally explained. Finally, the dynamic behaviour of the complete system and its temporal and spatial scales is shown to be captured in more detail.

Some issues of multi-criteria optimization of parameters of complex systems

Objective. The purpose of the study is to substantiate the design criteria for optimality, taking into account the multi-criteria purpose and functioning of the object.Method. The study was carried out on the basis of multicriteria optimization methods, the hierarchy analysis method, the convolution method, and heuristic methods.Result. The paper describes general problems of multicriteria optimization of mechanical systems. The importance of the problem of substantiating the design criteria for optimality, taking into account the multi-criteria purpose and functioning of the object, and introducing quantitatively measurable goals from a variety of alternative options is indicated. It is noted that the choice and formation of a generalized optimality criterion is the most responsible in solving optimization problems. The need to ensure the correctness of the application of one or another convolution method is indicated. Various approaches to the formation of a generalized optimality criterion are analyzed. Their features, advantages and disadvantages are given. The possibility of correcting parametric constraints in problems of improving optimal solutions is pointed out.Conclusion. When solving multi-criteria problems, it is necessary to pay great attention to both the formulation of the problem and the choice of a system of criteria and the implemented method for solving the problem.

Locality sensitive hashing via mechanical behavior

From healing wounds to maintaining homeostasis in cyclically loaded tissue, living systems have a phenomenal ability to sense, store, and respond to mechanical stimuli. Broadly speaking, there is significant interest in designing engineered systems to recapitulate this incredible functionality. In engineered systems, we have seen significant recent computationally driven advances in sensing and control. And, there has been a growing interest – inspired in part by the incredible distributed and emergent functionality observed in the natural world – in exploring the ability of engineered systems to perform computation through mechanisms that are fundamentally driven by physical laws. In this work, we focus on a small segment of this broad and evolving field: locality sensitive hashing via mechanical behavior. Specifically, we will address the question: can mechanical information (i.e., loads) be transformed by mechanical systems (i.e., converted into sensor readouts) such that the mechanical system meets the requirements for a locality sensitive hash function? Overall, we not only find that mechanical systems are able to perform this function, but also that different mechanical systems vary widely in their efficacy at this task. Looking forward, we view this work as a starting point for significant future investigation into the design and optimization of mechanical systems for conveying mechanical information for downstream computing.

On the discontinuous dynamics of a class of 2-DOF frictional vibration systems with asymmetric elastic constraints

<abstract><p>In this paper, the discontinuous dynamic behavior of a two-degree-of-freedom frictional collision system including intermediate elastic collision and unilateral elastic constraints subjected to periodic excitation is studied by using flow switching theory. In this system, given that the motion of each object might have a velocity that is either greater than or less than zero and each object experiences a periodic excitation force that has negative feedback, because the kinetic and static friction coefficients differ, the flow barrier manifests when the object's speed is zero. Based on the discontinuity or nonsmoothness of the oscillator's motion generated by elastic collision and friction, the motion states of the oscillator in the system are divided into 16 cases and the absolute and relative coordinates are used to define various boundaries and domains in the oscillator motion's phase space. On the basis of this, the G-function and system vector fields are used to propose the oscillator motion's switching rules at the displacement and velocity boundaries. Finally, some dynamic behaviors for the 2-DOF oscillator are demonstrated via numerical simulation of the oscillator's stick, grazing, sliding and periodic motions and the scene of sliding bifurcation. The mechanical system's optimization designs with friction and elastic collision will benefit from this investigation's findings.</p></abstract>

Bayesian reliability-based robust design optimization of mechanical systems under both aleatory and epistemic uncertainties

Uncertainties can be divided into two general categories: aleatory and epistemic. Conventional reliability-based robust design optimization approaches, which disregard epistemic uncertainties due to lack of knowledge about the physical nature of systems, have previously been developed. To overcome this weakness, unlike previous methods, a Bayesian reliability-based robust design optimization method is proposed in the presence of both aleatory and epistemic uncertainties. The proposed formulation is presented as a multi-objective optimization problem. The univariate dimension reduction method is used to approximate the mean and variance of the design function. The non-dominated sorting genetic algorithm-II is used to solve the multi-objective optimization problem. To find the final optimum design from the Pareto front, Shannon’s entropy-based technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is applied. Finally, to demonstrate the applicability of the proposed method, two case studies are considered and the results are compared and discussed.

Mass Minimizing of Truss and Beam Structures Subjected to Cumulative Fatigue Damage

The work presents the methods and solutions of the optimizing design of the truss and beam structures subjected to the cumulative fatigue damage. Two basic approaches used in the optimization of mechanical systems are presented in the paper - the so-called direct search methods and the gradient methods. A short comparative and gradient approach was made. The aim was to minimize the weight of the truss or beam structure with restrictions affecting the prescribed fatigue life. The computational model assumed only quasi-static loading with different number of cycles.

Міцність, надійність і ресурс конструкцій аерокосмічної техніки і енергети-ки

This paper gives a brief overview of investigations into the strength, reliability, and life of aerospace and power engineering structures conducted along the following reseach line of the Institute of Technical mechanics of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine: the strength, reliabiliyty, and optimization of mechanical systems, launch vehicle, and spacecraft. The basic literature sources of 1991–2021 are cited. A more detailed consideration is given to the results obtained in 2014–2021 and published (monographs, articles indexed in international citation databases, and international conference papers). They involve the simulation of deformation of inhomogeneous material, in particular concrete, in heat-and-power engineering structures, the life estimation of shell structures of rocket/space hardware in the presence of stress concentrators in the form of openings, inclusions, and cracks, and the development of a methodological basis for the strength, reliability, and life of launch complexes for launch vehicles of different spacecraft classes. The methodological stages of calculation are considered, and high-intensity thermomechanical loads are classified. The life of launch complexes is determined using the notion of low- and high-cycle fatigue. Consideration is given to the development of fast projection-iteration schemes of the finite-element method and the method of local variations, which significantly reduce the computational time and may be used to advantage when a large body of calculations is needed in the design and development of new aerospace hardware and power engineering structures with the use of experiments at the developmental stage. In doing so, the effect of inelastic deformations in the vicinity of cutouts is analyzed. A numerical simulation of the strength and stability of inhomogeneous shell structures with the use of the above-mentioned new computational schemes is considered. Investigations of this type first of all involve inhomogeneous thin-walled shell structures at local loads and the effect of reinforcing inclusions on stress and strain concentration.

Advanced Metaheuristic Techniques for Mechanical Design Problems: Review

The design of complex mechanical components is a time-consuming process which involves many design variables with multiple interacted objectives and constraints. Traditionally, the design process of mechanical components is performed manually depending on the intuition and experience of the designer. In recent decades, automatic methods have been proposed to effectively search diverse and large parameter spaces. There is a growing interest in design optimization of mechanical systems using metaheuristic algorithms to improve the product lifecycle and performance and minimize the cost. Nowadays, there is a growing interest in design optimization of mechanical systems using metaheuristic algorithms to improve the product lifecycle and performance and minimize the cost. This review article demonstrates the applications of different metaheuristic algorithms in enhancing the design process of different mechanical systems. First, the basic concepts of common used metaheuristic algorithms are introduced. Then the applications of theses algorithms in optimization of different mechanical systems are discussed.

Entropy Generation in MHD Second-Grade Nanofluid Thin Film Flow Containing CNTs with Cattaneo-Christov Heat Flux Model Past an Unsteady Stretching Sheet

Entropy generation plays a significant role in several complex processes, extending from cosmology to biology. The entropy generation minimization procedure can be applied for the optimization of mechanical systems including heat exchangers, elements of nuclear and thermal power plants, ventilation and air-conditioning systems. In order to present our analysis, entropy generation in a thin film flow of second grade nanofluid holding single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) with a Cattaneo–Christov heat flux model is studied in this article. The flow is considered passing a linearly extending surface. A variable magnetic field with aligned angle ε is functioned along the extending sheet. With the aid of the homotopy analysis method (HAM), the fluid flow model is elucidated. The impressions of embedded factors on the flow are obtainable through figures and discussed in detail. It is observed that the velocity profile escalated with the increasing values of volume fraction of nanoparticles and second grade fluid parameter. The higher values of volume fraction of nanoparticles, second grade fluid parameter, non-linear heat source/sink, and thermal radiation parameter intensified the temperature profile. Surface drag force escalated with heightening values of nanoparticles volume fraction, unsteadiness, film thickness, magnetic, and second grade fluid parameters. Entropy generation increased with enhancing values of magnetic parameter, Brinkman number, and Reynolds number.

Multiobjective global optimization of mechanical systems with cracks

Multiobjective global optimization of mechanical systems with cracks

Semi‐active ℋ∞ damping optimization by adaptive interpolation

SummaryIn this work we consider the problem of semi‐active damping optimization of mechanical systems with fixed damper positions. Our goal is to compute a damping that is locally optimal with respect to the ‐norm of the transfer function from the exogenous inputs to the performance outputs. We make use of a new greedy method for computing the ‐norm of a transfer function based on rational interpolation. In this paper, this approach is adapted to parameter‐dependent transfer functions. The interpolation leads to parametric reduced‐order models that can be optimized more efficiently. At the optimizers we then take new interpolation points to refine the reduced‐order model and to obtain updated optimizers. In our numerical examples we show that this approach normally converges fast and thus can highly accelerate the optimization procedure. Another contribution of this work is heuristics for choosing initial interpolation points.

Discrete Adjoint Method for the Sensitivity Analysis of Flexible Multibody Systems

The gradient-based design optimization of mechanical systems requires robust and efficient sensitivity analysis tools. The adjoint method is regarded as the most efficient semi-analytical method to evaluate sensitivity derivatives for problems involving numerous design parameters and relatively few objective functions. This paper presents a discrete version of the adjoint method based on the generalized-alpha time integration scheme, which is applied to the dynamic simulation of flexible multibody systems. Rather than using an ad hoc backward integration solver, the proposed approach leads to a straightforward algebraic procedure that provides design sensitivities evaluated to machine accuracy. The approach is based on an intrinsic representation of motion that does not require a global parameterization of rotation. Design parameters associated with rigid bodies, kinematic joints, and beam sectional properties are considered. Rigid and flexible mechanical systems are investigated to validate the proposed approach and demonstrate its accuracy, efficiency, and robustness.

Quantitative measure for nonlinear unstable systems based on the region of attraction and its application to designing parameter optimization – inverted pendulum example

Quantitative stability measures for mechanical systems are highly needed. However, only a few such measures have been proposed for nonlinear systems. In this paper, a quantitative measure of stability for nonlinear systems based on the region of attraction (ROA) is proposed, and the measure is applied to parameter optimization of mechanical systems: multi-link inverted pendulum example. Recently, some techniques for calculating ROAs have been suggested; however, obtaining an accurate estimate of a ROA remains computationally demanding. We illustrate two techniques for efficiently estimating the proposed measure and apply them to the design parameter optimization problem for maximizing the stability measure. A number of simulations show the effectiveness of the proposed method.

Optimization of noisiness of mechanical system by using a pneumatic tuner during a failure of piston machine

Abstract The stage of construction and operation of the machines requires monitoring of the steps causing negative effects on humans and environment in the form of noise during their use. Current technologies allow for appropriate optimization of mechanical systems as part of these machines. One possible optimization of the mechanical systems is considered to be the use of pneumatic tuners. The aim of this article is to demonstrate the effect of the pneumatic tuner on noisiness of mechanical system even in case of failure of mechanical drive part. Performed experimental measurement presents the change of noise in mechanical system by changing a pressure of gaseous medium in pneumatic tuner's compression space. The solution is an issue of appropriate mechanical tuning system when there is a change of dynamic parameters of the system and thus to change the entire mechanical system noise. Subsequent obtained results set out suggestions for the use of pneumatic tuners in mechanical systems in order to achieve the lowest possible noise during their operation mode.

Hybrid artificial immune strategy in identification and optimization of mechanical systems

The paper deals with an application of the two types of hybrid artificial immune system (HAIS). First hybridization is based on hyper mutation gradient second is based on kriging method. The optimization of mathematical function and shape, topology and material properties of 3-D structures is presented. The identification of material parameters that were disrupted by a specific value of the noise is presented. Numerical examples demonstrate that the method based on the artificial immune system is a very effective technique for solving computer aided optimal design.

Soft simulator for redesigning of a chickpea harvester header

This paper proposes a new framework to tackle computer-aided modeling and evolutionary algorithms into conventional design phase of a machine, which, in turn, significantly reduces time and cost of structural optimization. The model-based engineering approach overcomes the crudity of hard modeling, field experiments and statistical analysis for finding the optimum structure of a design. Genetic algorithm incorporated with fuzzy modeling established a hybrid computational algorithm which predicts optimal sizing of a platform, developed for a chickpea harvester header. The harvesting losses of the platform’s configurations in field trials were fed to the metaheuristic approach to develop a soft simulator for redesigning of the machine. Acceptable harvesting performance of the optimized harvester in field trials confirmed the robustness feature of the experiments based simulator. Further the results validated the virtual model and verified the reliability of the automatically generated harvester. The methodology can be employed for structural optimization of mechanical systems.

Dynamic response multiobjective optimization of road vehicle ride quality—A computational multibody system approach

Computational multibody system (MBS) method is a practical technique utilized for modeling, simulation, and optimization of mechanical systems. In the methodology of computational multibody system, equations of motion are derived, formulated, and solved through a systematic, generalized, and well-structured computational-mathematical approach. In this paper, the computational multibody system formulation, based on the appended Lagrangian method, is implemented to establish the governing equations of ride dynamics for a nonlinear ride model that represents a versatile half-car two-track model of a road vehicle. The input to the system is a simulated road surface model based on the ISO road surface classification. The solution of the equation of motion is obtained using the direct integration approach along with constraint violation elimination and control techniques. Following the simulation, a time-domain multiobjective design optimization procedure is performed to improve the ride quality of the model. The ride quality comprises both ride comfort and ride safety. The optimization considers relevant objective functions including vibration isolation, suspension travel, road holding, and force index. The results of work show that the proposed method could acceptably estimate the optimal values of design variables for specific road classes and vehicle driving speeds. The simulation-based ride quality optimization performed here could facilitate improvement of suspension and tyre.

Advances in numerical computation based mechanical system design and simulation

This paper highlights the available numerical computation techniques in mechanical engineering field with focus on application of modeling and simulation within renewable energy conversion machines as a particular research case. The study makes special focus on simulation approaches based on finite elements and multibody dynamics that are currently focused within the research community. Developing the simulation model in a computer-aided design (CAD) tool is a precondition for a successful simulation-based mechanical system research. The article discusses and elaborates the methods implemented to integrate design data with other computer-aided engineering functions. The motivation is the fact that simulation-based research is useful for design optimization of mechanical systems that operate in harsh and unfriendly environment where conducting physical testing of prototypes is difficult. In addition, the manufacturing environment is benefiting from the developments in numerical computation techniques through machining simulation that significantly reduce the time-to-market and thus increase competitiveness. The study is also intended to explore the existing gaps of capabilities in current approaches in application of computational techniques in order to draw attention to future challenges and trends.

Sensitivity-Based, Multi-Objective Design of Vehicle Suspension Systems

This article deals with the dynamic response optimization of mechanical systems, based on the computation of independent state sensitivities. Specifically, the dynamic behavior of a coach is analyzed in detail so as to improve its response in terms of handling and ride comfort behaviors. To that end, the coach is modeled as an 18DOF multibody system, whose equations of motion are posed using an efficient dynamic formulation based on Maggi's equations. Next, a direct-automatic differentiation approach for the computation of independent state sensitivities is applied. This allows one to quantify the effect of 19 design parameters on the vehicle dynamic response and to compute the design sensitivities or objective function gradients. Finally, handling and ride comfort objective functions are defined and are used to carry out a multi-objective suspension design optimization process, improving the vehicle response by 70% in an effective yet automatic way.