Structural Design Optimization Research Articles

Performance reliability evaluation of high‐pressure internal gear pump

AbstractWith the development of the high‐end equipment technology, the performance requirements of the internal gear pump (IGP) under high pressure are also increasing. However, the increase of working pressure will lead to the instability of gear pump performance in terms of volumetric efficiency, noise, reliability and so on, it is necessary to reasonably evaluate the reliability level of high‐pressure IGP. The reliability analysis of the high‐pressure IGP is carried out from the aspects of flow, noise, and gear strength in this paper. First, the output flow rate and far‐field flow‐induced noise of the high‐pressure IGP were obtained through fluid numerical simulation, and experimental verification was conducted. Then, based on the time‐varying meshing stiffness, backlash function and static transmission error of the gear pair, a nonlinear dynamic model of the internal meshing gear pair was established. The time‐varying meshing force was obtained through the dynamic model of the gear pair, and then the tooth contact stress and tooth root bending stress were obtained. Finally, considering the uncertain factors affecting the performance of the high‐pressure IGP, Latin hypercube sampling (LHS) combined with dendrite network (DD) was used for random response modeling. The performance reliability of the high‐pressure IGP, including output flow rate, far‐field flow‐induced noise, and the strength of gear pair, were estimated based on the fourth moment‐based saddlepoint approximation (FMSA). The reliability analysis results can provide a theoretical basis for the structural optimization design of the high‐pressure IGP.

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

The optimal structural design is imperative in order to minimize material consumption and reduce the environmental impacts of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as the genetic algorithm (GA). However, the integration of AI-based optimization, together with visual programming (VP), in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps, including the following: (i) generation of parametric trusses in Dynamo VP; (ii) performing finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. This methodology provides a new interoperable framework with minimal interference with existing supply-chain processes, and it will be flexible to technology literacy and allow architectural, engineering and construction (AEC) professionals to employ VP, global optimization, and FEM in BIM-based projects by leveraging open-sourced software and tools, together with commonly used design software. The feasibility of the proposed workflow was tested on benchmark problems and compared with the open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction. Despite the success of this study in developing a workable, user-friendly, and interoperable framework for the utilization of VP, GA, FEM, and BIM for structural optimization, the results obtained could be improved by (i) increasing the callback function speed between Dynamo and RSA through specialized application programming interface (API); and (ii) fine-tuning the GA parameters or utilizing other advanced global optimization and supervised learning techniques for the optimization.

Multi-objective topology optimization design of thermal-mechanical coupling structure based on FPTO method

Multi-objective topology optimization design of thermal-mechanical coupling structure based on FPTO method

A multi-objective optimization design method for underwater composite sandwich structures with high acoustic transmission and low vibration performance

ABSTRACT To address the issue of reduced structural integrity and optimality resulting from the conventional serial design of sonar dome structures, this paper establishes a multi-objective optimal design model for composite sandwich structures, utilising the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The model's stability and reliability are subsequently validated. Upon this model, a structural optimization design technique is postulated for composite sandwich structures within the realm of Fluid-Structure Interaction (FSI) multi-physics coupling. This approach aims to optimize the lightweight, high-rigidity composite sandwich structure, enhancing its acoustic transmission and minimizing vibration performance under turbulent pressure pulsations. The suggested method notably enhances the efficiency of structural design while ensuring precision. The proposed method effectively addresses the deficiency of serially designed sonar domes by neglecting the synergistic effects among multiple disciplines. In summary, this approach offers technical support and new research perspectives for the design of sonar domes under the coupling of multiple physical fields.

Seismic design optimization of space steel frame buildings equipped with triple friction pendulum base isolators

To increase the seismic resilience of structures, it is necessary to utilize seismic isolation to increase structural periods and reduce story drifts. When seismic isolation is implemented, structures are capable of deforming by remaining within safe limits. Thus, more seismically resilient designs are achieved compared to conventional fixed-based structures since lighter structural design weights are attained. The principal aim of this study is to achieve the comparative design optimization of space steel frame buildings equipped with seismic base isolation and to examine the effect of seismic base isolation on optimum structural design weight by comparing the same structures with conventional rigid-based ones. For seismic base isolation, triple friction pendulums are implemented into steel frame buildings. For this aim, four different space steel frame buildings with 4-, 6-, 8-, and 10-story are treated as design examples. A novel design optimization algorithm is encoded, which includes nature-inspired metaheuristic artificial bee colony, crow search, and Archimedes optimization algorithms to achieve design optimizations of triple friction pendulums equipped with seismic-isolated space steel frame buildings. The practice code provisions of load and resistance factor design specification for structural steel buildings have been applied to control the structural design constraints of inter-story drift, top-story drift, strength, displacement, and connections geometry of beams and columns. Eventually, it has been remarked that seismic base isolation significantly reduces the structural optimal design weight of space steel frame buildings.

Design and Optimization of Heat Dissipation for a High-Voltage Control Box in Energy Storage Systems

Abstract To address the issue of excessive temperature rises within the field of electronic device cooling, this study adopts a multi-parameter optimization method. The primary objective is to explore and realize the design optimization of the shell structure of the high-voltage control box, aiming to effectively mitigate the temperature rise in internal components and enhance their thermal management efficacy without altering the fan performance, environmental conditions, or spatial layout. Initially, the study employs computational fluid dynamics methods to investigate the heat dissipation characteristics of the high-voltage control box, subsequently verifying the simulation parameters' accuracy through temperature rise tests. Building upon this foundation, the article conducts a thorough analysis of how the position and shape of the box's openings impact the device's temperature rise. The findings suggest that configuring circular openings on the front and rear sides can optimize the heat dissipation effect. Moreover, the SHERPA algorithm was employed to refine the size and distribution of the openings on the outer shell of the high-voltage control box through multi-parameter optimization, yielding locally optimal structural parameters. Post-optimization, the temperature measurement points within the high-voltage control box exhibited a maximum reduction in temperature rise of 27.16%. The pivotal contribution of this methodology is the application of a data-driven decision-making process for the enhancement of conventional heat dissipation designs. This research offers invaluable practical insights and novel perspectives on the optimization of thermal management designs for box-type electronic devices, significantly advancing the field of thermal management technology in electronic devices.

A novel design method based onmulti–objective optimization for graded lattice structure by additive manufacturing

PurposeWhile performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.Design/methodology/approachTo handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.FindingsThe initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.Originality/valueIn this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

Impact response characteristics and damage mechanism of continuous carbon-fiber-reinforced magnesium matrix composite materials

The continuous carbon-fiber-reinforced magnesium matrix composite (C_f/Mg) is a new type of composite material made of a magnesium alloy sheet and carbon-fiber-reinforced composite material with alternating layers. It has the advantages of high damage tolerance, light weight, and corrosion resistance, and has become the first choice of lightweight materials in aerospace, transportation, and other fields. Because impact-resistance serves as an important index for its structural design and performance stability, a continuous carbon-fiber-reinforced magnesium matrix composite with indirect bonding using a modified epoxy resin was designed in this study. Moreover, C_f/Mg was chosen to be the object of research through the selection of constituent materials such as magnesium alloys, carbon fibers, resins, and other properties, which matched the aim of realizing a lightweight material. With the help of hot-compression molding technology, dynamic impact mechanical behavior, and damage analysis technology, the structural design and preparation process optimization of epoxy resin carbon-fiber prepregs and magnesium alloy layer materials, as well as the dynamic impact mechanical response characteristics and damage evolution process under different impact energy conditions, were studied. Accordingly, through a combination of low-velocity impact experiments and numerical simulations, the effects of continuous multiple impacts at the same location with the same impact energy, as well as impacts with the same impact energy and different punch diameters, on the low-velocity impact damage behavior and dynamic impact response characteristics of C_f/Mg were investigated. The results of this study show that when the 5J impact is applied four times consecutively, the peak impact load gradually increases with the increasing number of impacts. Moreover, the peak impact loads of the second, third, and fourth impacts increase by 6.09%, 10.7%, and 14.5%, respectively, compared with the results of the first impact.

Aluminum oxide droplet collisions: Molecular dynamics study

In this work, the induced coalescence mechanism and dynamic contact behavior of alumina (Al2O3) droplets at different impact velocities were investigated for the first time from a microscopic point of view by molecular dynamics (MD) methods through the analysis of axial speed, shrinkage, neck radius ratio, contact force, temperature, kinetic energy, surface energy, and the amount of change in the internal energy of the droplets. The results show that the minimum speed at which collisional coalescence of Al2O3 droplets occurs is 30 m/s. When the speed is lower than 30 m/s, the droplets undergo bounce phenomena due to the Coulomb force. Under the high-speed impact, the inertia force of Al2O3 droplets acts less than the surface tension and viscous resistance. The droplets don’t get squashed in the whole collision process. For the different initial velocities, the magnitude of the contact force on a unilateral droplet during the collision process does not always increase with speed. When the collision speed is not higher than 400[Formula: see text]m/s, the contact force on the droplets eventually stabilizes at about 0.28[Formula: see text]Kcal/(mol⋅Å), whereas this value is about 0.36[Formula: see text]Kcal/(mol⋅Å) and about 0.5[Formula: see text]Kcal/(mol⋅Å) for the intervals from 500[Formula: see text]m/s to 700[Formula: see text]m/s and from 800[Formula: see text]m/s to 1000[Formula: see text]m/s, respectively. The increase of the droplet’s initial speed has a limited contribution to the temperature of the system after the collision, and the amount of loss of the total energy (the sum of kinetic energy, surface energy, and internal energy changes) becomes more pronounced, even up to about 20% when the speed reaches 900[Formula: see text]m/s. At the same time, we predicted the Al2O3 melting point and compared it with the standard melting point with an error of 2%, proving the accuracy of the model. This work can strengthen our understanding of the industrial processes with applications in high-energy nanomaterials, rocket propellants, rocket structure design and performance optimization.

Optimization design of main hinge joint structure based on weld failure analysis

From the data, structural defects and cracks evolution patterns are identified to determine a statistically significant service life of approximately 5500 h. In this paper, a statistical analysis of failure form and work time of MHJ is conducted. Microscopic test of cracks reveals four main forms of type of cracks. Improper weld technology causes defects in the metallographic structure of weld seam. Improper design causes fatigue cracks of weld seam. Improper machining of parts causes stress concentration and cracks. Improper structural design causes uneven load-bearing capacity of the overall weld structure. According to the above problems, weld structure are optimized. Detailed research is conducted on weld technology of key weld bead. The differences in microstructure and weld efficiency of three different weld technologies are determined by microscopic tests on three key weld seam structures. Therefore, it is concluded that weld bead of MHJ can use full fusion of 9–12 passes multi-pass weld form. This method can achieve a balance between weld efficiency and weld quality. According to simulation analysis and comparison, lifespan after optimization of MHJ increases from 5863 h to 10,374.8 h. Structural performance of MHJ is greatly improved after optimization. Effectiveness of optimal design is verified by zero feedback within 5 years.

A new model of thermo-mechanical actuation for twisted and coiled polymer muscles with initial curvature

The twisted and coiled polymer (TCP) artificial muscle is one type of novel soft actuator for mimicking natural skeletal muscle that can provide large linear and torsional actuation and energy density. Twisting and coiling are the pivotal steps in fabricating TCP muscles. The influence of twisting on the actuation response of TCP muscles has been extensively investigated recently. However, the influence of coiling remains unclear. Based on the finite strain theory, we establish a new thermo-mechanical actuation model for TCP muscles with initial curvature. The theoretical predictions based on the model align well with the finite element simulations, accurately capturing the actuation response of thermally-activated TCP muscles. It is revealed that twisting contributes positively to the actuation, while coiling has a passive effect. Geometrical parameters, such as the helix radius and helix angle, can effectively regulate the actuation performance of TCP muscles. Furthermore, an optimal bias angle is identified that maximizes both the recovery torque and the linear actuation. This study sheds light on the structural optimization design of TCP muscles.

Complex modal optimization of the disk brake based on thermal–structural coupling

The brake disk and friction material parameters were taken as design variables, with the negative damping ratio of the unstable mode as the optimization target. The central composite design method was employed to obtain suitable data sample points. A neural network response surface model was constructed to predict the real part values of the unstable mode. Structural optimization design was then conducted using a screening method to derive optimized parameters for the brake disk structure and physical parameters such as density, elastic modulus, and Poisson’s ratio of the friction material. The optimized coefficient of the negative damping ratio of the brake system’s unstable mode was enhanced, thereby reducing the likelihood of brake squeal. Harmonic response analysis showed a significant optimization effect on the curve of brake disk amplitude fluctuations with frequency. These findings offer valuable insights for improving the stability of disk brake systems.

Integrative Probabilistic Design of River Jetties by 3D Numerical Models of Transport Phenomena: The Case Study of Kabakoz River Jetties

Various methods are employed to investigate the effects of coastal structures in coastal areas on marine environments and transport phenomena. These methods can be categorized into physical models and numerical simulations. Due to the lack of long-term wave height data in Türkiye, numerical models are utilized to estimate wave heights generated by wind based on long-term measured wind speeds. These wave heights generated in deep sea conditions can be transported to the coast by wave transformation and interactions between coastal structures and waves, turbulence, currents induced by wind and breaking waves, coastal sediment transport rates, and changes in the coastline can be successfully predicted with the assistance of numerical models. In the scope of this study, the new “Integrative Probabilistic Design Approach of River Jetties” was developed. 3D numerical models were used for the optimum design, considering the sediment transport near the jetties and aiming to protect the coastal environment in the long term. 3D numerical modeling has been conducted to investigate the transport phenomena occurring at the outlet of the Kabakoz River in the Şile District of İstanbul Province to acquire the optimum layout and design of the coastal structures. The study presents the “Integrative Probabilistic Design Approach” for coastal protection structures by wind and wave climate, wave transformation, coastal sediment transport, shoreline change, and coastal structure probabilistic design sub-models. Monte Carlo Simulation of Hudson Limit State function conducts probabilistic design for the jetties. The greatest advantage of probabilistic design (Monte Carlo Simulation) is the prediction of uncertainties, such as wave height changes under design conditions. Following the completion of the construction of groins, the effect of probabilistic design on both design and coastal morphology can be evaluated precisely. In conclusion, in the study area, 146,237.55 m3 of sediment is transported annually from west to east and 221,043.49 m3 from east to west. In the absence of coastal structures, sediment transport from east to west is approximately 1.5 times greater than from west to east. The annual net coastal sediment transport from east to west is approximately 74,805.94 m3, while the total transport is estimated to be 367,281.04 m3. The coastline is expected to reach sediment balance within approximately two years. In this study, the coastal structure of a jetty is designed from an innovative probabilistic design perspective. The aim is to ensure the reliability of the structure and, at the same time, protect the morphology of the coastline where the structure will be constructed. The region’s wind and wave climate were initially determined using Hydrotam 3D software. Following this procedure, the length of the jetty is predicted considering the closure depth. The model parameters were calibrated from coastline morphology using satellite images and Google Earth over the past twenty years. These parameters are defined to Hydrotam 3D as input data; a trial-and-error model application procedure calibrates the coastline’s accumulation and erosion. Finally, the probabilistic design is conducted with Monte Carlo Simulation using the Hudson Equation as the limit state function. Det Norske Veritas developed a design code for marine structures in 1992, where the target reliability is 10-3 for structures with less serious failure consequences. This reliability level validated the Level IV model presented in this paper. The class of failure depends on the possibility of timely warning, and these standards can be revised by the model presented to address the effects of climate change on the design of maritime structures.

Ultimate strength failure mechanism and optimization design of marine composite deck grillage structures with opening

In this paper, the ultimate bending strength and the failure mechanism of the marine composite deck grillage structure are experimentally and numerically investigated, before the optimization design is conducted to enhance the ultimate bearing capacity. The ultimate strength experiment of the composite deck grillage structure is first carried out. Based on the improved progressive failure method and the cohesive damage theory, the numerical simulation considering fiber failure, matrix failure, shear failure and adhesive layer failure is conducted and the predicted strains, load–displacement curves, and failure modes of the specimen are compared with the experimental ones to verify the accuracy of the present method. Both experimental and predicted results show that the stiffeners and the laminated deck near the opening are the stress concentration areas, and the matrix failure is main failure mode. The optimization results show that the suitable panel thickness can reduce the stress concentration effect and avoid premature fracture in localized areas due to stress concentration. The increase of the stiffener heights can significantly increase the ultimate strength and the bending stiffness. These findings can provide support for the design of composite deck grillage structures in ships.

Benchmark problems in optimum structural design of 3D reinforced concrete frames

Benchmarking goes hand in hand with the development and establishment of efficient and robust optimization methodologies in various scientific fields. Nevertheless, benchmark problems, with known global optima, are currently missing in the optimum structural design of reinforced concrete (RC) frames. In the present study, for first time, benchmark case studies in the optimum design of RC frames are presented. The aim is that these benchmarks are used for the calibration, tuning, improvement and development of optimization algorithms to address the efficient design of concrete frames. More particularly, six three-dimensional concrete building frames are optimally designed to Eurocodes. First, exhaustive search is conducted to identify the global optimum solutions and Pareto fronts. Useful conclusions are also made with respect to the properties of the optimal solutions. Moreover, all candidate designs results are provided in an supplementary file so that they can be used in future optimization studies. Next, the performance of several well-known, single- and multi-objective optimization algorithms is assessed against the global optima to examine their efficiency and applicability in this class of optimization problems. Closing, the need for further and larger in scale benchmark case studies in the optimum design of concrete frames is emphasized.

Lifetime assessment of deep-sea manned cabin with PMMA pressure-resistant hull prior to micro-cracks

Fully-transparent cabin type, utilized in manned submersibles, is typically constructed using viscoelastic PMMA (polymethyl methacrylate) material. Accurate fatigue life assessment of manned cabin is of paramount importance to ensure structural safety. In this study, a calculation process for evaluating the fatigue life of PMMA manned cabins based on a continuum damage mechanics model combined with the viscoelastic constitutive relationship of the PMMA material in response to the absence of related specification is proposed. Fatigue tests of PMMA material are performed for determination of damage evolution model parameters and the calculation process is validated by the fatigue test data. Tailored subroutines are then developed by using ABAQUS software tool, respectively for structural analysis of a typical manned cabin with PMMA pressure-resistant hull, openings, hatches and penetration plates and simulating trapezoidal loading history acting on manned cabin. Subroutine coupling is accordingly employed to conduct parametric analysis on fatigue crack initiation life of the fully-transparent manned cabin with consideration of different outside pressure level and operation time and valuable results are obtained for identifying key areas of concern. This study intends to contribute to further cabins safety enhancement, as well as to design optimization and fatigue analysis of underwater structures involving PMMA materials.

Effect of temperature softening on the actuation performance of twisted and coiled polymer muscles

Twisted and coiled polymer (TCP) artificial muscles represent a promising class of actuators capable of emulating natural skeletal muscle, offering substantial linear actuation and energy density. The actuation characteristics of the thermally-activated TCP muscle and twisted fiber are characterized experimentally, emphasizing the influence of the temperature-softening effect. We find that the recovered torque of twisted fiber increases monotonically with temperature while showing a non-monotonical variation with the fiber bias angle. The variations of actuation strain and end torque with three structural parameters of TCP muscles, i.e., fiber bias angle, helical angle, and spring index, are comprehensively investigated. An optimal bias angle and spring index are present. A significant temperature-softening effect of precursor fiber is observed; a polymer becomes softer and more pliable as the temperature increases. A thermo-mechanical model for predicting the effect of temperature-softening on TCP muscle is established and validated with experimental data. This work facilitates precise control and guides the structural optimization design of the thermally-activated TCP muscle.

Topology optimization and bionic analysis of heat sink fin configuration based on additive manufacturing technology

Fins are extensively employed in heat sinks for high heat flux components. In this study, three distinct objective functions, namely temperature gradient minimization (TO-I type fin), average temperature minimization (TO-II type fin), and entransy dissipation minimization (TO-III type fin), are established for topology optimization design of the heat sink fin structure to effectively minimize the temperature of the heat source. By conducting a comparative analysis of the configuration features and thermal performance of optimized fins with different objective functions, it is evident that the TO-I type fin exhibits superior thermal performance. When the fin volume fraction φ is 0.3, the heat source center temperature of TO-I type fin is 2.67 K and 4.55 K lower than that of TO-II type fin and TO-III type fin, respectively. Meanwhile, the bionic analysis of the optimized fins under different objective functions using fractal theory reveals that the fractal dimension of the TO-I type fin is 1.4038, which is the closest to the average fractal dimension of many kinds of leaf veins in nature (D¯f= 1.3762), which indicates that the optimized fins have the bionic characteristics most similar to those of the leaf blade. Finally, the three topology optimization fins were fabricated using boundary-filtering optimization 3D printing technology. Comparative tests verified the advantage of minimizing the temperature gradient as the objective function of topology optimization and demonstrated its potential for thermal performance and lightweighting applications, especially under high heat source operating conditions.

Morphogenesis of free-form surface structures based on geometrically nonlinear isogeometric analysis

Free-form surface structures have taken the forefront in space structure research owing to their free and flexible expressiveness and aesthetic visual effects. Yet, their irregular shapes and large span of the initial structure often lead to the problem of large displacement, necessitating the incorporation of geometric nonlinearity in the analysis. In this paper, we employ structural optimization design principles to investigate the morphogenesis of free-form surface structures while considering their geometric nonlinearity. Particularly, we explore both single-objective and double-objective shape optimization of free-form surface structures by employing structural strain energy and the first natural frequency as optimization indexes and the vertical coordinates of control points as optimization variables. The effectiveness of the proposed method is finally verified by several examples.

Tidal turbine blade design optimization based on coupled deep learning and blade element momentum theory

The practical design optimization of blade structures is crucial for enhancing the power capture capability of tidal turbines. However, the significant computational costs required for directly optimizing turbine blades through numerical simulations limit the practical application of blade structure optimization. This paper proposes a framework for tidal turbine blade design optimization based on deep learning (DL) and blade element momentum (BEM). This framework employs control points to parameterize the three-dimensional geometric shape of the blades, uses convolutional neural networks to predict the hydrodynamic performance of each hydrofoil section, and couples BEM to forecast the performance of tidal turbine blades. The multi-objective non-dominated sorting genetic algorithm II is employed to optimize the geometric parameters of turbine blades to maximize the power coefficient and minimize the thrust coefficient, aiming to obtain the optimal trade-off solution. The results indicate that the prediction of the DL-BEM model agrees well with experimental data, significantly improving optimization efficiency. The optimized tidal turbine blades exhibit excellent power coefficients and reduced thrust coefficients, achieving a more balanced structural solution. The proposed optimization framework based on DL accurately and rapidly predicts the performance of tidal turbines, facilitating the design optimization of high-performance tidal turbine blades.