Stress Constraints Research Articles

Multi-constrained topology optimization of prefabricated joints in large-span latticed structures

In recent years, topology optimization (TO) has shown great potential in the optimal design of engineering structures. In this study, a parameterized level set (PLS) method capable of solving the compliance minimization problem with both stress and volume constraints is proposed to improve the design efficiency of nodal connections in large-span latticed structures. 3D topology optimization of assembled hub (AH) joints is conducted based on the proposed method. The performances of the optimal designs are compared with those of the traditional joints in terms of volume, stress distribution and compliance value. Different connection types and complex loading conditions are considered to satisfy the requirements of engineering practice. It is indicated that the proposed PLS method exhibits good stability and high computing efficiency during the optimization of AH joints. Compared with the study cases with a single volume constraint, the maximum von Mises stress is effectively controlled by simultaneously introducing the stress and volume constraints. In addition, the variation in the volume constraint has much greater influence on the compliance results than the stress constraint. The compliance continuously increases when the volume constraint decreases from 100% to 40%, while the difference in compliance is less than 1.5% with or without stress constraints. It is demonstrated that the performances of AH joints are significantly improved after the TO design. The reduction rates of mass are in the range of 25.2 % to 35.2 %, and the compliance value is reduced by 0.5 % to 7.6 % for all the study cases.

Exploring the Relationships Among (COVID)-19 Stress, Leisure Constraints, and Happiness for Adults During the (COVID)-19 Pandemic in Korea.

Objectives: The emergence of COVID-19 and its consequences has led to fears, worries, discomfort, depression, and anxiety for human beings worldwide. In this study, we examined the relationships among COVID-19 stress, leisure constraints, and happiness of Korean adults. Methods: We employed on-line convenience sampling to recruit participants. The sample consisted of Korean adults. A total of 600 surveys were distributed, we retained 293 responses for analysis. Results: COVID-19 stress subcomponents significantly impacted on individual happiness. Our findings align with research focusing on positive correlates between perceived COVID-19 stress and leisure constraints subcomponents. We also found that as COVID-19 stress decreased, perceived happiness increased. Conclusions: Future research is proposed to explore the mechanism of how leisure constraints influence the engagement of physical activities and strategies of leisure constraints negotiation to gain the benefits of happiness in the pandemic crisis. Managerial implications and future research are discussed from the perspectives of constraint negotiation and happiness.

A comparison performance analysis of eight meta-heuristic algorithms for optimal design of truss structures with static constraints

Metaheuristics have been successfully used for solving complex structural optimization problems. Many algorithms are proposed for truss structure size and shape optimization under some constraints. This study considers eight population-based meta-heuristic methods: African Vultures Optimization Algorithm (AVOA), Flow Direction Algorithm (FDA), Arithmetic Optimization Algorithm (AOA), Generalized Normal Distribution Optimization (GNDO), Stochastic Paint Optimizer (SPO), Chaos Game Optimizer (CGO), Crystal Structure Algorithm (CRY) and Material Generation Algorithm (MGO). These meta-heuristics methods are used to optimize the size of three aluminum truss structures. Optimization aims to reduce the weight of the truss members while meeting a set of displacement and stress constraints. The performance of these methods is assessed by solving and optimizing three well-known truss structure benchmarks under some constraints. The results show that the Stochastic Paint Optimizer (SPO) outperforms the other algorithms in terms of accuracy and convergence rate.

Non-probabilistic reliability-based topology optimization (NRBTO) scheme for continuum structures based on the strength constraint parameterized level set method and interval mathematics

In this paper, a study on non-probabilistic reliability-based topology optimization (NRBTO) scheme for continuum structures based on the parameterized level set method (PLSM) is conducted. The P-norm is used to replace the local stress constraint with a single comprehensive stress constraint that approximates the maximum stress to optimize the structure model with minimum volume. In the interval-set model, the stress constraint is transformed into the non-probabilistic reliability-based scheme and the reliability is evaluated by the optimization feature distance (OFD). In the NRBTO scheme, the unknown-but-bounded (UBB) uncertainties of the material and external load of the optimized structure are considered. By interpolating the level set function (LSF) with the multiquadric (MQ) splines, the partial differential equation (PDE) is transformed into an ordinary differential equation (ODE). In addition, the interval parameter vertex method is employed to obtain the stress constraint interval, and the shape derivative and adjoint vector methods are used to obtain the evolution velocity field of LSF. The optimality criterion (OC) method is used to solve the optimization problem. Finally, three examples are given, and the optimization model of stiffness constraint is introduced, which not only verifies the applicability of the topology optimization scheme based on non-probabilistic reliability but also compares the difference between the topology optimization with strength constraint and the topology optimization with stiffness constraint.

Stress-based evolutionary topology optimization via XIGA with explicit geometric boundaries

This paper presents a novel approach to stress-based topology optimization that employs NURBS representations of explicit geometric boundaries to address stress minimization and stress-constrained problems. The proposed methodology is compatible with CAD systems and utilizes Extended IsoGeometric Analysis (XIGA) to ensure an accurate representation of stress field in the evolving structure. A p-norm aggregation scheme is used to measure global stress levels, and the aggregated stress constraint is augmented to the objective (compliance) via a Lagrange multiplier in stress-constrained problems. The proposed approach introduces a novel and efficient Lagrange multiplier trail strategy aimed at reducing computational costs. Additionally, a normalization scheme and a partial differential equation filter are presented to stabilize the highly nonlinear stress-based optimization. Validation studies demonstrate the effectiveness and characteristics of the proposed approach. Moreover, control points of the structural design can be directly edited to further improve strength performance. Comparative studies show clear advantages of the proposed methodology in terms of computational efficiency compared to other Finite element analysis (FEA)-based optimization methods. Overall, this paper presents a practical and novel approach that addresses the limitations of existing FEA-based optimization methods in terms of accuracy, flexibility, and degree of freedom (DOF) cost, and makes a significant contribution to the field of stress-based topology optimization.

High-Fidelity Gradient-Based Wing Structural Optimization Including Geometrically Nonlinear Flutter Constraint

Lightweight high-aspect-ratio wings make aircraft more energy efficient thanks to their lower induced drag. Because such wings exhibit large deflections, design optimization based on linear flutter analysis of the wing undeformed shape is inadequate. To address this issue, we develop a framework for integrating a geometrically nonlinear flutter constraint, which considers in-flight deflections, into a high-fidelity gradient-based structural optimization. The wing mass and stress constraints are evaluated on a linear built-up (detailed) finite element model to capture realistic structural features. The geometrically nonlinear flutter constraint is based on a condensed low-order beam representation of the built-up finite element model, which captures the impact of in-flight deflections with tractable computational effort for optimization. The flutter constraint is differentiated with respect to the detailed structural model sizing variables using the adjoint method to enable large-scale optimizations. The framework is demonstrated by minimizing the mass of a wingbox model subject to the geometrically nonlinear flutter constraint along with stress and adjacency constraints. The geometrically nonlinear flutter constraint adds a penalty of up to 60% of the baseline mass due to the impact of in-flight deflections on the flutter onset speed and its mechanism. In contrast, a linear flutter constraint evaluated on the undeformed wing adds a mass penalty of only 10%. This methodology can help design energy-efficient aircraft with high-aspect-ratio wings, which require geometrically nonlinear flutter analyses early in the design cycle.

Swarm intelligence hybridized with genetic search in multi-objective design optimization under constrained-Pareto dominance

The inclusion of uncertainty in structural design optimization led to more complex design optimization formulations, where uncertainty quantification has significant influence on solution methods and computing times. Designs maintaining steady levels of performance, under uncertainty, are called robust and the combination of both robustness and performance optimality leads to a methodology called Robust Design Optimization (RDO). In this work a new approach to the RDO of angle-ply composite laminate structures is proposed. The key concept of this methodology is the hybridization between the principles of Particle Swarm Optimization and Genetic Algorithms, through the evolution of multiple populations based on local and global constrain-dominance. The RDO problem is here defined as the bi-objective minimization of the structural weight (optimality) and the determinant of the variance–covariance matrix (robustness) of the system’s response functionals, subject to stress and displacement constraints. A numerical structural design problem, representing a composite laminate engine hood shell, shows the capabilities of the proposed approach. Results display the good convergence properties of the proposed hybridizations both in the search and objective spaces.

Optimal Design of Planar Steel Frames Using the Hybrid Teaching–Learning and Charged System Search Algorithm

In this study, a novel effective algorithm called HTC which results from a hybridization process between the teaching–learning-based optimization (TLBO) and charged system search (CSS) algorithms is proposed and utilized to optimize planar steel frames. Among the features of the proposed algorithm, simplicity and low number of setting parameters can be mentioned. The main goals of this hybridization process are to establish a balance between exploration and exploitation, increase the rate of convergence, and avoid getting trapped in the local optimal point. Moreover, the purpose of optimizing steel frames is to calculate their minimum weight by choosing suitable sections as well as considering the stress and displacement constraints in accordance with the requirements of the AISC design regulations using the load and resistance factor design (LRFD) method. To evaluate the performance of the HTC algorithm, standard benchmark steel frames are examined, and the results of the proposed algorithm are compared with other metaheuristic optimization methods. According to the outcomes of the comparison, the proposed algorithm has better performance than the other methods.

A Tool for the Design of Turbomachinery Disks for an Aero-Engine Preliminary Design Framework

Disks in gas turbines are optimized for minimum weight, while satisfying both geometry and stress constraints, in order to minimize the engine production, operation, and maintenance costs. In the present paper, a tool is described for the preliminary mechanical design of gas turbine disks. A novel formulation is presented, where the disk weight minimization is achieved by maximizing the stresses developed in the disk. The latter are expressed in the form of appropriately defined design and burst margins. The computational capabilities of the tool developed are demonstrated through comparisons to calculations with a higher fidelity tool. The importance of accurately calculating thermal stresses is demonstrated and the ability of the tool for such calculations is discussed. The potential and efficiency of the tool are illustrated through a proposed re-design of the disks of a well-documented ten-stage compressor. Finally, the integration of the tool into an overall engine design framework is discussed.

Learning Stress with Feet and Grids

This paper investigates quantity-insensitive stress learning using the MaxEnt learner of Pater and Prickett (2022) and compares the performance of the learner equipped with three different constraint sets: a foot-based constraint set and two grid-based constraint sets, one drawn directly from Gordon (2002), and one that changes the formulation of the main stress constraint to match the foot-based learner. The learner equipped with the foot-based constraint set succeeds at learning all the languages from the Gordon (2002) typology that it can represent; the structural ambiguity of the foot-based representations is not a problem in this regard. The foot-based learner also learns the languages as quickly in terms of number of epochs as the faster of the grid-based learners, which is the one with the revised main stress constraint. We conclude that the foot-based learner and the grid-based learner fare similarly well in this initial comparison on a typologically grounded set of learning problems.

Stress-based topology optimization for fiber composites with improved stiffness and strength: Integrating anisotropic and isotropic materials

Fiber-reinforced materials offer high stiffness- and strength-to-mass ratios to lightweight composite structures. To design stiff, strong, and lightweight fiber-reinforced composite structures, we propose a multimaterial anisotropic stress-constrained topology optimization framework that simultaneously optimizes geometry, distribution of anisotropic (i.e., orthotropic) and isotropic material phases, and local orientations of fiber reinforcements in the anisotropic phase. To achieve high performance in both stiffness and strength, we discover that both isotropic and anisotropic materials are needed: anisotropic materials are preferred in uniaxial members to increase stiffness, while isotropic materials are crucial at multi-axially stressed joints to enhance strength. We introduce multimaterial interpolation schemes to characterize both the stiffness and strength of composites made up of anisotropic and isotropic materials. The characterization of strength is enabled by a novel load factor-based yield function interpolation that consistently integrates anisotropic Tsai–Wu and isotropic von Mises yield criteria. We optimize stress-sensitive domains considering materials with various levels of stiffness and strength anisotropy as well as multiple load cases. The anisotropic stress constraints in the proposed framework effectively inform geometries to reduce stress concentration in fiber composites. The proposed framework provides a rational design paradigm for composite structures, capitalizing on dissimilar stiffness and strength properties of anisotropic and isotropic materials, to potentially benefit various engineering applications.

Exploring Influences of Eating Behaviors Among Emerging Adults in the Military

ObjectiveIdentify factors influencing eating behaviors among emerging adults in the military. DesignFocused ethnography using interviews, observations, and artifacts for data. SettingThree US Naval installations. ParticipantsThirty-two active-duty Sailors aged 18–25 years. AnalysisQualitative data were organized in NVivo and analyzed sequentially to categorize culturally relevant domains and themes using a social ecological model (SEM). Descriptive statistics were used to describe questionnaire data in SPSS (version 27.0, IBM, 2020). ResultsLeaders encouraged healthy eating through policies and messages, but cultural contradictions and environmental barriers undermined Sailors' efforts to eat healthily. Stress and resource constraints (intrapersonal), peer pressure (social), unhealthy food environments and lack of access to food preparation (environmental), and eating on the go because of mission-first norms (cultural) promoted unhealthy eating behaviors. Nutrition and culinary literacy (intrapersonal); peer support and leadership engagement (social); access to healthy, convenient, and low-cost foods (environmental); and indoctrination to healthy eating during recruit training (cultural) positively influenced eating behaviors. Conclusion and ImplicationsThe eating behaviors of service members are influenced by many modifiable factors. Targeted education, leadership engagement, and policies that make nutritious foods easily accessible, appealing, and preferred are needed.

Structure-Circuit Resistor Integrated Design Optimization of Piezoelectric Energy Harvester Considering Stress Constraints

A piezoelectric energy harvester (PEH) transduces mechanical energy into electrical energy, which can be utilized as an energy source for self-powered or low-power devices. Therefore, maximizing the power of a PEH is a crucial design objective. It is well known that structural designs are firstly conducted for controlling resonance characteristics, and then circuit designs are pursued through impedance matching for improving power. However, a PEH contains solid mechanics, electrostatics, and even a circuit-coupled multi-physics system. Therefore, this research aims to design a PEH considering a circuit-coupled multi-physics. As a design process, a conceptual design is developed by topology optimization, and a detailed design is developed sequentially by applying size optimization as a post-processing step to refine the conceptual design results for manufacturable design. In the two optimization processes, design optimizations of a structure coupled with circuit resistor are performed to maximize the power, where the electrical and mechanical interactions between PZT, substrate, and circuit resistor are simultaneously considered. Additionally, stress constraints are also added for structural safety to ensure operational life of PEH. As a result of the proposed design methodology, a manufacturable design of PEH having maximum power and operational life is obtained with power density of 6.61 μWg−2mm−3.

Enhanced dominance of soil moisture stress on vegetation growth in Eurasian drylands.

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982-2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD-SWC relation and VPD-greenness relation are both non-linear, while the SWC-greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD-SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia.

Leaf angle as a leaf and canopy trait: Rejuvenating its role in ecology with new technology.

Life on Earth depends on the conversion of solar energy to chemical energy by plants through photosynthesis. A fundamental challenge in optimizing photosynthesis is to adjust leaf angles to efficiently use the intercepted sunlight under the constraints of heat stress, water loss and competition. Despite the importance of leaf angle, until recently, we have lacked data and frameworks to describe and predict leaf angle dynamics and their impacts on leaves to the globe. We review the role of leaf angle in studies of ecophysiology, ecosystem ecology and earth system science, and highlight the essential yet understudied role of leaf angle as an ecological strategy to regulate plant carbon-water-energy nexus and to bridge leaf, canopy and earth system processes. Using two models, we show that leaf angle variations have significant impacts on not only canopy-scale photosynthesis, energy balance and water use efficiency but also light competition within the forest canopy. New techniques to measure leaf angles are emerging, opening opportunities to understand the rarely-measured intraspecific, interspecific, seasonal and interannual variations of leaf angles and their implications to plant biology and earth system science. We conclude by proposing three directions for future research.

Topology Optimization of fiber reinforced structures considering stress constraint and optimized penalization

The use of materials reinforced with fibers has been increasing due to their advantages, for example, the ratio between its mass and strength. For this reason, new additive manufacturing technologies have been developed for this material type. Some technologies allow tailoring fiber orientation, creating space for applying optimization techniques. On this account, many works dedicated to optimizing fiber orientation have been currently published. However, the critical issue of the stress yield criteria should be addressed. Thus, this work proposes to solve the Topology Optimization problem of minimizing the volume of the structure considering local stress constraints, determining the material distribution and the fiber orientation by using a proposed method named NDFO-adapt. The penalization used in the method is a field optimized together with the material distribution and the fiber angle. The same approach is extended to the penalization of SIMP and β parameters of threshold projection. This strategy enlarges the solution space and facilitates the discovery of previously unachievable local minima while eliminating the need for a heuristic selection of continuation methods. The Augmented Lagrangian method is used to deal with the local stress constraints. A mesh refinement scheme developed in the FEniCS project is proposed. Numerical examples are presented to illustrate the performance of the proposed method.

High-Fidelity Aerostructural Optimization with a Geometrically Nonlinear Flutter Constraint

When designing aircraft, avoiding dynamic aeroelastic instabilities such as flutter is a key requirement. One way to meet this requirement is to use a multidisciplinary design optimization subject to a flutter constraint. Flutter-constrained design optimizations have used geometrically linear detailed models, which do not accurately predict flutter for very flexible aircraft, or geometrically nonlinear low-order models, which do not accurately trade off cruise range and structural mass. This paper presents a framework for integrating a geometrically nonlinear, subsonic flutter constraint that captures the large in-flight deflections of very flexible aircraft into high-fidelity gradient-based aerostructural optimization. The cruise range and stress constraints are computed accurately with detailed aerostructural analyses, which use a built-up finite element model coupled to Reynolds-averaged Navier–Stokes computational fluid dynamics. The detailed model is condensed to a low-order aeroelastic model to compute the geometrically nonlinear flutter constraint and its adjoint derivatives with computational cost and robustness suitable for optimization. The framework is demonstrated by maximizing the cruise range of a subsonic high-aspect-ratio wing with respect to panel thicknesses, sweep, and span. The impact of the geometrically nonlinear flutter constraint highly depends on the in-flight deformation level. At low deflection levels, sweeping the wing backward is the most effective flutter prevention method, and the flutter constraint has little impact on the achievable cruise range. At high deflection levels, shortening the wing span is necessary to suppress flutter, reducing the achievable cruise range by up to 5.9%. This work is a step toward making multidisciplinary design optimization a practical tool for designing the energy-efficient, very flexible aircraft of the future, which require geometrically nonlinear flutter analyses early in the design cycle to prevent flutter.

Nonlinear stiffness mechanism designed by topology optimization reduces backpack vibration

This paper develops a nonlinear stiffness mechanism to reduce the vibration of the suspended-load backpack and its peak force applied to human. The suspension system between the human and load is a mechanism with nonlinear force deflection behavior. Compared with the common linear vibration system, the nonlinear dynamics model of double-mass system actuated by human legs was established. An optimization formulation considering the static deflection constraint was established to reduce the peak force and obtain the target force deflection behavior. The optimization result reflects that the target force deflection behavior has the characteristic of high-static-low-dynamic stiffness and can significantly reduce the peak force imposed on human body compared with the generic backpack. The nonlinear stiffness mechanism is creatively designed by implementing a new design method based on topology optimization. Geometrically nonlinear finite element analysis is employed to obtain the reaction force of the mechanism under different displacement loads. A topology optimization model considering stress constraint was constructed based on the target nonlinear force deflection behavior. A test bench was built to test the practical force deflection behavior of the nonlinear stiffness mechanism. The experiments under different loads and speeds were conducted. The results show that the suspended-load backpack with the nonlinear stiffness mechanism reduces the peak dynamic force by 73.34% under the specified experimental circumstance and by 59.12% in all experimental conditions compared with the generic backpack.

Bed Shear Stress in Experimental Flash Flood Bores over Dry Beds and over Flowing Water: A Comparison of Methods

Hydraulic parameters, including bed shear stress, are challenging to calculate for flash floods. Applying theoretical equations to strongly unsteady flows requires comprehensive and accurate flow data that are difficult to collect for natural events. To empirically evaluate the extent to which simpler calculations can reasonably predict shear stresses in rapidly changing hydrographs, and to determine how bed shear stresses differ for hydraulic bores propagating over dry beds compared to shallow water, we conducted laboratory flume experiments on idealized short-duration flash floods with bores. We compared the Saint-Venant shallow water equation, which theoretically captures the depth-averaged momentum balance of gradually varying unsteady flow to eight simpler methods, with assumptions that are not met in these flows. The Saint-Venant method predicts higher shear stresses immediately after bore arrival, but all of the simpler methods are nonlinearly correlated with the Saint-Venant method even when flow is rapidly changing. While none of the methods we evaluated should strictly apply to rapid changes in depth and velocity of bores, the correlations we found between methods just after bore arrival suggest that, for applications where shear stresses must be calculated but data are insufficient to apply the full Saint-Venant equations, simpler methods may provide meaningful shear stress constraints. Compared to flood bores propagating over a dry bed, bores propagating over shallow flowing water had steeper water surfaces but resulted in significantly lower bed shear stresses immediately after bore arrival.

Role of Carrier Media and Types of Indigenous MVA Isolates on Soil Quality in Corn Plants in the Dry Land of West Nusa Tenggara

Corn plants have many benefits and are needed by the government as a national food reserve. West Nusa Tenggara (NTB) maize production fluctuated. If managed optimally, dry land agriculture in NTB can provide benefits for increasing agricultural production, especially corn production. The sustainability of dry land farming systems must be continuously improved even with various farming strategies with the main objective of improving soil fertility and overcoming drought stress constraints. One of the efforts to increase the productivity of NTB's dry land is the use of arbuscular vesicular mycorrhizal biofertilizers which are an alternative to improve the quality of soil and plants. Arbuscular vesicular mycorrhiza will colonize and infect roots maximally if using a carrier media that is compatible with MVA inoculant. Appropriate MVA carrier media will provide optimal environmental conditions for host plant growth. The aim of the research was to determine the role of Indigenous MVA and carrier media on soil quality in dryland maize. The research was carried out on corn plants using different carrier media and native MVA types. The study was designed as a factorial study using a completely randomized design (CRD) with 2 factors, namely the type of indigenous MVA isolates with 3 treatment levels and the Carrier Media Type factor with 4 treatment levels. There were 12 treatment combinations that were repeated 3 times so that 36 treatment combinations were obtained which were carried out at the Green House of the Faculty of Agriculture, Nahdhatul Wathan University, Mataram from December 2020 to February 2021. The results showed that the MVA type factor, the MVA isolate had a significantly different effect for all observation parameters, namely soil water content, soil pH, soil total N content and soil available P content, the best isolate was Glomus sp. The carrier media factor gives the result that the type of carrier media has a significant effect on the parameters of observing soil water content, soil total N content and soil pH with the best carrier media being rice husk charcoal biochart