Optimal Geometry Research Articles

Development of novel concave and convex trowels for higher interlayer strength of 3D printed cement paste

Past experimental results have shown that the use of nozzle trowels can enhance the interlayer strength of 3D printed cement paste. In this study, the design is further optimized by introducing concave and convex shapes onto the nozzle trowel design. A technique for accurate simulation of the interlayer stresses with the influence of nozzle trowels is established, and it is found that the nozzle trowels double the maximum shear stress and increase the maximum pressure by about 114 %. Moreover, the concave and convex nozzle trowels with removal of interlayer notch further increase the interlayer strength by 35 %. A theoretical model is also proposed to predict the interface geometry and then validated by the experimental observations on the concave and convex trowels. These findings not only result in 3D printed cement paste with much higher interlayer strength, but also emphasize the importance of nozzle designing with optimal interlayer stresses and interface geometries in the application of 3D concrete printing (3DCP).

Maximizing the Absorbing Performance of Rectangular Sonic Black Holes

This study examines the absorption performance of rectangular sonic black holes (SBHs), which are designed to provide broadband anechoic termination for rectangular waveguides. The SBHs explored in this work consist of a series of opposing rib pairs embedded within the waveguide, where the distance between the ribs in each pair decreases towards the end of the structure according to a specific profile. A computationally efficient mathematical model, combined with an evolutionary optimization algorithm, is employed to determine the optimal geometrical parameters, including the SBH profile, which maximize absorption performance over a broad frequency range. As the optimal geometries feature very fine internal structures, which pose challenges for practical implementation, micro-perforated plates are incorporated to introduce additional losses. Numerical simulations and optimizations are again utilized to identify the geometrical and physical parameters that maximize the absorption performance of these modified structures. The results demonstrate superior absorption performance, even with internal structures compatible with contemporary manufacturing processes. The results of the numerical simulations are validated via a comparison with detailed and accurate mathematical model.

3D-Printed Latticed Microneedle Array Patches for Tunable and Versatile Intradermal Delivery.

Using high-resolution 3D printing, a novel class of microneedle array patches (MAPs) is introduced, called latticed MAPs (L-MAPs). Unlike most MAPs which are composed of either solid structures or hollow needles, L-MAPs incorporate tapered struts that form hollow cells capable of trapping liquid droplets. The latticestructures can also be coated with traditional viscous coating formulations, enabling both liquid- and solid-state cargo delivery, on a single patch. Here, a library of 43 L-MAP designs is generated and in-silico modeling is used to down-select optimal geometries for further characterization. Compared to traditionally molded and solid-coated MAPs, L-MAPs can load more cargo with fewer needles per patch, enhancing cargo loading and drug delivery capabilities. Further, L-MAP cargo release kinetics into the skin can be tuned based on formulation and needle geometry. In this work, the utility of L-MAPs as a platform is demonstrated for the delivery of small molecules, mRNA lipid nanoparticles, and solid-state ovalbumin protein. In addition, the production of programmable L-MAPs is demonstrated with tunablecargo release profiles, enabled by combining needle geometries on a single patch.

Optimization and evaluation of thermo-hydraulic performance of solar air heaters equipped with different roughness geometries

Solar air heaters have poor thermal efficiency. Applying artificial roughness elements is a common approach to enhance thermal performance of a solar air heater. In this study, fluid flow and heat transfer characteristics of solar air heaters equipped with six different roughness geometries, including inline cubical elements, staggered cubical elements, rectangular baffles, square ribs, V-shaped baffles, and V-shaped ribs, were assessed. First, parameters of each roughness geometry were optimized and then thermo-hydraulic performance of solar air heaters having optimum roughness geometries was compared. For each roughness geometry, two design parameters were selected and 25 numerical experiments were designed based on the full factorial design of experiment approach. The thermo-hydraulic performance parameter (THPP) was set out as the objective function and its relationship with roughness parameters was defined using the non-parametric regression response surface method. Finally, the optimum values of roughness parameters were determined using the nonlinear programming by quadratic Lagrangian (NPQL) technique. Comparing the performance of solar air heaters having optimum roughness geometries showed that rectangular baffles led to the largest and inline cubical elements brought about the smallest THPP at almost all Reynolds numbers. The maximum THPP of rectangular baffles was 2.28 at the Reynolds number of 25,000.

Optimizing the Electrode Geometry of an In-Plane Unimorph Piezoelectric Microactuator for Maximum Deflection

Piezoelectric microactuators have been widely used for actuation, sensing, and energy harvesting. While out-of-plane piezoelectric configurations are well established, both in-plane deflection and asymmetric electrode placement have been underexplored in terms of actuation efficiency. This study explores the impact of asymmetric electrode geometry on the performance of slender unimorph actuators that deflect in-plane, where actuator length is much larger than width or thickness. After validating the finite element modeling method against experimental data, the geometric parameters of the proposed unimorph model are manipulated to explore the effect of different electrode geometries and layer thicknesses on actuation efficiency. Four key findings were that (1) the fringing field within the piezoelectric material plays a measurable role in performance, (2) symmetry in electrode placement is generally nonoptimal, (3) optimal electrode geometry is independent of scale, and (4) the smaller the ratio of width to thickness, the larger the deflection. The findings contribute to the development of efficient design strategies that optimize the performance of planar actuators for potential implications for microelectromechanical systems (MEMS). To aid designers of piezoelectric unimorph actuators in determining the optimal electrode geometry, three types of parameterized figures and two types of simulation apps are provided.

Numerical Evaluation of Hydroformed Tubular Adhesive Joints under Tensile Loads

Adhesive joints are widespread in the aerospace, aeronautics, and automotive industries. When compared to conventional mechanical joints, adhesive joints involve a smaller number of components, reduce the final weight of the structure, enable joining dissimilar materials, and resist the applied loadings with a more uniform stress state distribution compared to conventional joining methods. Hydroformed tubular adhesive joints are a suitable solution to join tubes with identical cross-sections, i.e., tubes with the same dimensions, although this solution is seldom addressed in the literature regarding implementation feasibility. This work aims to numerically analyze, by cohesive zone modelling (CZM), hydroformed tubular adhesive joints between aluminum adherends subjected to tensile loads, considering the variation of material parameters (type of adhesive) and geometrical parameters. Initially, a validation of the proposed CZM approach is carried out against experimental data. Next, the aim is to numerically evaluate the tensile characteristics of the joints, measured by the maximum load (Pm) and energy of rupture (ER), considering the main geometrical parameters (outer tube diameter of the non-hydroformed adherend or dENHA, overlap length or LO, tube thickness or tAd, and joggle angle or q). CZM validation was successfully performed. The numerical study determined that the optimal geometry uses the adhesive Araldite® AV138, higher dENHA and LO highly benefit the joint behavior, tAd has a moderate effect, and q has negligible influence on the results.

Heat spreading effect on the optimal geometries of cooling structures in a manifold heat sink

Embedded cooling is a promising solution to address thermal challenges of power electronics. The present work investigates heat spreading effect on the optimal geometries of cooling structures within a single-phase manifold heat sink in laminar regime by integration of topology optimization (TO) and Bayesian optimization (BO). Such integration is for the manual parameter tuning issue in the density-based TO of conjugate heat transfer, and the TO process is accelerated by using a dual-level simulator and the optimality criteria optimizer combined with the stochastic gradient descent method. The heat spreading effect significantly alters the optimal geometries, due to the change of thermal resistance constitutions. Physical analyses on the BO-TO-generated geometries give two guidelines for improving the cooling structures here: (a) Heat source-coolant distance should increase properly for narrow heating area and small Biot number; (b) Highly-thermal-conductivity solid can be filled into low-velocity regions directly connecting to hot area. As an example, a fabrication-friendly cooling structure is devised in the case of concentrating heating following these guidelines, avoiding the computationally-expensive optimization process and the over-complicated geometries. The CFD simulations show this design can significantly reduce the thermal resistance with minor increase of pressure loss as the Reynold number from 50 to 300.

Cooperative, Close and Remote Steric Effects on the Structural and Optical Properties of Copper(I) Bis‐Phenanthroline Complexes

AbstractThe synthesis as well as the structural, optical and computational characterization of seven new highly hindered homoleptic copper(I) phenanthroline complexes (namely C1–C7) is reported along with the comparison with the benchmark derivatives. Despite limited steric hindrance in direct proximity of the copper(I) coordination site, X‐ray structures show that the higher hindered derivatives of the series display a more optimal tetrahedral geometry with minimal D2 symmetry distortion. A novel remote control of the geometry, with steric hindrance away from the coordination site, leads to a favorable arrangement as demonstrated by structural and computational data. In addition, electrochemical and steady‐state and time‐resolved photophysical studies are presented which further support the beneficial effects on the ground‐state redox and excited‐state properties when both remote and close steric effects are exploited. Indeed, both an increase of the photoluminescence quantum yield and a prolongation of the excited state lifetime is observed for the highly‐substituted derivative C6 compared to benchmark counterparts on account of the reduced excited‐state flattening distortions imparted by the additional steric constraints.

An Extensive Parametric Analysis and Optimization to Design Unidimensional Periodic Acoustic Metamaterials for Noise Attenuation

The presented research delineates an extensive study aimed at obtaining and comparing optimal designs and geometries for one-dimensional periodic acoustic metamaterials to attenuate noise within the audible frequency range of 20 Hz to 20 kHz. Various periodic designs, encompassing diverse geometric parameters and shapes—from Basic-Periodic to Semi-Periodic, Tapered-Diverging, and Tapered-Converging unit cells of repeated patterns—are examined to identify the most effective configurations for this application. A thorough parametric analysis is executed employing FE-Bloch’s theorem across these four configurations to determine their bandgaps and to identify the most effective geometry. A normalization process is utilized to extend the domain of the analysis and the range of the system parameters studied in this work, totaling 202,505 design cases. Finally, the optimal design is identified based on achieving the best bandgaps coverage. The study concludes with the presentation of frequency domain acoustic pressure responses at multiple sensing points along the filters, validating the performance and the obtained bandgaps through these optimal geometries.

Design of poly(vinyl pyrrolidone) and poly(ethylene glycol) microneedle arrays for delivering glycosaminoglycan, chondroitin sulfate, and hyaluronic acid

Osteoarthritis (OA) is a prevalent joint disorder characterized by cartilage and bone degradation. Medical therapies like glucosaminoglycan (GAG), chondroitin sulfate (CS), and hyaluronic acid (HA) aim to preserve joint function and reduce inflammation but may cause side effects when administered orally or via injection. Microneedle arrays (MNAs) offer a localized drug delivery method that reduces side effects. Thus, this study aims to demonstrate the feasibility of delivering GAG, CS, and HA using microneedles in vitro. An optimal needle geometry is crucial for the successful application of MNA. To address this, here we employ a multi-objective optimization framework using the non-dominated sorting genetic algorithm II (NSGA-II) to determine the ideal MNA design, focusing on preventing needle failure. Then, a three-step fabrication approach is followed to fabricate the MNAs. First, the master (male) molds are fabricated from poly(methyl methacrylate) using mechanical micromachining based on optimized needle geometry. Second, a micro-molding with Polydimethylsiloxane (PDMS) is used for the fabrication of production (female) molds. In the last step, the MNAs were fabricated by microcasting the hydrogels using the production molds. Light microscopy (LIMI) confirms the accuracy of the MNAs manufactured, and in vitro skin insertion tests demonstrate failure-free needle insertion. Subsequently, we confirmed the biocompatibility of MNAs by evaluating their impact on the L929 fibroblast cell line, human chondrocytes, and osteoblasts.

Modular Open Chamber Stand for Biomass Densification Using the Example of Miscanthus × Giganteus Greef Et Deu

This article presents a modular open chamber stand which simulates the densification process that occurs in a single channel of a pelletising die. The results of the verification tests confirmed the suitability of this stand for determining the optimal geometry of the channel. The test material was the biomass of Miscanthus × giganteus which is considered to be a difficult material for pressure densification; therefore, it was decided that it would be a good material for verifying the stand. The stand consists of four modules: an introductory section with a diameter of D = 12 and 10 mm, a conical part with an angle of α = 10°, 20°, 30°, 40°, a cylindrical part with lengths L = 5, 15, 25, 35, 45 mm and diameter d= 8 mm and a pellet receiving module. The stand is able to heat the densification channel. Individual modules can be assembled into test combinations; this results in a change in channel geometry without the necessity to manufacture many singular channels. The optimum geometry of the channel for miscanthus with a moisture content of 13%, densified at 100 °C was determined. It should be a channel with D = 10 mm, α = 40° and L = 18 mm.

Multi-Objective Optimization of the Seawall Cross-Section by DYCORS Algorithm

The purpose of this research is to develop a new method for automatically optimizing the seawall cross-section with composite slopes and a berm, considering both overtopping discharge and construction cost. Minimizing these competing multi-objectives is highly challenging due to the intricate geometry of seawalls. In this study, the surrogate model optimization algorithm DYCORS (Dynamic COordinate search using Response Surface models) is employed to search for the optimal seawall geometry, coupled with the ANN (Artificial Neural Network) model for determining the overtopping discharge. A total of 20 trials have been run to evaluate the performance of our methodology. Even the worst-performing Trial 7 among these 20 trials shows a satisfactory performance, with a reduction of 17.67% in overtopping discharge and a 12.1% decrease in cost compared to the original solution. Furthermore, compared to other optimization schemes using GAs (Genetic Algorithms) with the same decision vectors, constraints, and multi-objective functions, the methodology has been proven to be more effective and robust. Additionally, when facing different combinations of wave conditions and water levels, there was a 27.8% reduction in objective function value compared to the original solution. The optimal results indicate that this method can still be effectively applied for optimizing the seawall cross-section as it is a general method.

Influence of the Geometric Shape of the Courtyard of Traditional Wooden Folk Houses on the Lighting Performance of Their Central Room: A Case Study of the Traditional Folk Houses of the Tujia People in Western Hunan, China

Although traditional Chinese wooden residential buildings have historically adapted to their respective regions, they face challenges in meeting modern living standards, particularly with regard to insufficient indoor natural lighting. This study focuses on three representative Tujia residences: the “L-shaped” dwellings, the “U-shaped” dwellings, and the courtyard residences, with the aim of improving their indoor lighting performance. Using Ecotect 2011 software for computer simulations, the study investigates the impact of altering the geometric shapes of courtyards in traditional wooden residential buildings on the lighting of the central room. The results indicate that, for the “L-shaped” dwellings, the geometric dimensions of the courtyard have little impact on the lighting of the central room. For the “U-shaped” dwellings, the optimal courtyard geometry is achieved with a well index (WI) of 1, balancing residential functionality, economic considerations, and indoor lighting performance. Regarding the courtyard residences, the best results are obtained by minimizing the building height while maximizing the well depth index to 1. Additionally, the study shows that a square layout of 90° ∗ 90° is most favorable for courtyards, effectively balancing lighting performance, functionality, and aesthetics. These findings provide valuable insights for the renovation of existing traditional residences and the design of new buildings, aiming to enhance overall indoor lighting effectiveness.

Integrating deep convolutional surrogate solvers and particle swarm optimization for efficient inverse design of plasmonic patch nanoantennas.

Plasmonic nanoantennas with suitable far-field characteristics are of huge interest for utilization in optical wireless links, inter-/intrachip communications, LiDARs, and photonic integrated circuits due to their exceptional modal confinement. Despite its success in shaping robust antenna design theories in radio frequency and millimeter-wave regimes, conventional transmission line theory finds its validity diminished in the optical frequencies, leading to a noticeable void in a generalized theory for antenna design in the optical domain. By utilizing neural networks, and through a one-time training of the network, one can transform the plasmonic nanoantennas design into an automated, data-driven task. In this work, we have developed a multi-head deep convolutional neural network serving as an efficient inverse-design framework for plasmonic patch nanoantennas. Our framework is designed with the main goal of determining the optimal geometries of nanoantennas to achieve the desired (inquired by the designer) S 11 and radiation pattern simultaneously. The proposed approach preserves the one-to-many mappings, enabling us to generate diverse designs. In addition, apart from the primary fabrication limitations that were considered while generating the dataset, further design and fabrication constraints can also be applied after the training process. In addition to possessing an exceptionally rapid surrogate solver capable of predicting S 11 and radiation patterns throughout the entire design frequency spectrum, we are introducing what we believe to be the pioneering inverse design network. This network enables the creation of efficient plasmonic antennas while concurrently accommodating customizable queries for both S 11 and radiation patterns, achieving remarkable accuracy within a single network framework. Our framework is capable of designing a wide range of devices, including single band, dual band, and broadband antennas, with directivities and radiation efficiencies reaching 11.07 dBi and 75 %, respectively, for a single patch. The proposed approach has been developed as a transformative shift in the inverse design of photonics components, with its impact extending beyond antenna design, opening a new paradigm toward real-time design of application-specific nanophotonic devices.

Geometry optimization of wall-jet collection device: A study of flow-field dynamics and particle motion

Wall-jet collection has been recognized as an advanced technique for mining polymetallic nodules that has significant potential for practical engineering applications. Optimizing the geometry of the collection device can improve collection efficiency and reduce environmental disturbance. In this study, 24 distinct structures of nodule-collection device were investigated using a computational fluid dynamics–discrete element method, which was validated by comparing with the experimental data. A key parameter, the wall-jet half-width coefficient Cc, was employed to examine the collection performance, including the collection efficiency, collection flow field, and particle trajectory. An assessment indicator derived from energy-consumption and substrate-disturbance metrics was proposed, and this allowed the identification of optimal device structures tailored to various requirements. The results showed that based on collection efficiency–jet flow rate (η–q) response curves, the collection performance can be categorized into two distinct patterns. When Cc ≤ 1.56, induced flow will occur, and η can reach 1.0; when Cc > 1.56, a moving vortex that disturbs the particle trajectories is generated, and the jet escapes rightward, resulting in a decrease in η. The influences of geometric parameters on Cc exhibit coupled relationships, which is particularly noticeable in the relationship between the tangential angle of the jet and its thickness. The optimal device geometry varies for different criteria, and maximum reductions in substrate disturbance and jet energy consumption of 48.46% and 19.64%, respectively, were obtained with different optimization criteria. This study is expected to provide data to support the optimization of the structure of wall-jet collection devices.

Multi-Objective Reverse Design and Pattern Analysis of Solid Propellant Grains

Solid propellant grain reverse design aims to discover optimal grain geometries by shape optimization methods to match the desired solid motor performance curves. To maximize the performance matching degree and the propellant loading fraction simultaneously, this study develops a multi-objective evolutionary neural network for the grain reverse design, where the burning surface regression calculation is efficiently employed using the fast-sweeping method. Then, grain shape feature extraction and pattern analysis are achieved through image singular value decomposition and self-organizing mapping, respectively. Finally, the design case of a dual-thrust motor and a Mars ascent vehicle show that the method can well balance the performance-matching degree and propellant loading fraction. Moreover, without any training data set, it can generate dozens of grain shape patterns, highlighting their diversity and providing new ideas for solid rocket motor designers. Our method can offer a new pathway for the research field of solid rocket motor design.

Computational study on the impact of geometric parameters on the overall efficiency of multi-branch channel heat sink in the solar collector

Enhancing the thermal performance of electronic devices is a persistent challenge. Liquid-cooled Multi-branch-channel heat sinks (MBCHSs) offer a promising solution. The present study focuses on optimizing MBCHS hydrothermal efficiency and temperature uniformity. Various MBCHSs, including a foundational case and cases denoted as 1 through 4, have been developed to assess the impact of geometric parameters on performance. Using a performance evaluation criterion (PEC), it quantitatively assesses hydrothermal improvements in each model. Additionally, this study explores the use of a water-based ternary hybrid nanofluid (THNF) with GO-Al2O3-ZnO ternary hybrid nanoparticles in an optimized multi-branch channel. Furthermore, an analysis and generation of entropy were examined. The COMSOL software has been employed for the simulation of the problem in this study. This promising fluid replacement for pure water demonstrates superior performance and temperature control. The findings indicate that among the various cases, case 2 exhibits the highest PEC. At Reynolds number 500, the optimal MBCHS geometry (case 2) featuring THNF with a volumetric fraction of 0.06 exhibits a 16.63% higher Heat Transfer Coefficient (HTC) compared to pure water. In contrast, MBCHS, with the same volumetric fraction, demonstrates a 29.82% lower Nusselt number. Contrastingly, at a volumetric fraction of 0.06, MBCHS displays a pressure drop 70.27% higher than that of pure water. Overall, the PEC of MBCHS with a volumetric fraction of 0.06 has decreased by 41% compared to pure water. At Reynolds number 500, lamina-shaped nanoparticles exhibit a 50.34% and 56.56% higher HTC in comparison to spherical and pure water, respectively. Moreover, the PEC for lamina-shaped nanoparticles at Reynolds 500 undergoes a 49.58% and 62.37% reduction when compared to spherical and pure water, respectively.

Exact pretransition effects in kinetically constrained circuits: Dynamical fluctuations in the Floquet-East model.

We study the dynamics of a classical circuit corresponding to a discrete-time version of the kinetically constrained East model. We show that this classical "Floquet-East" model displays pre-transition behavior which is a dynamical equivalent of the hydrophobic effect in water. For the deterministic version of the model, we prove exactly (i) a change in scaling with size in the probability of inactive space-time regions (akin to the "energy-entropy" crossover of the solvation free energy in water), (ii) a first-order phase transition in the dynamical large deviations, (iii) the existence of the optimal geometry for local phase separation to accommodate space-time solutes, and (iv) a dynamical analog of "hydrophobic collapse."

Enhancing Clay-Based 3D-Printed Mortars with Polymeric Mesh Reinforcement Techniques.

Additive manufacturing (AM) technologies, including 3D mortar printing (3DMP), 3D concrete printing (3DCP), and Liquid Deposition Modeling (LDM), offer significant advantages in construction. They reduce project time, costs, and resource requirements while enabling free design possibilities and automating construction processes, thereby reducing workplace accidents. However, AM faces challenges in achieving superior mechanical performance compared to traditional methods due to poor interlayer bonding and material anisotropies. This study aims to enhance structural properties in AM constructions by embedding 3D-printed polymeric meshes in clay-based mortars. Clay-based materials are chosen for their environmental benefits. The study uses meshes with optimal geometry from the literature, printed with three widely used polymeric materials in 3D printing applications (PLA, ABS, and PETG). To reinforce the mechanical properties of the printed specimens, the meshes were strategically placed in the interlayer direction during the 3D printing process. The results show that the 3D-printed specimens with meshes have improved flexural strength, validating the successful integration of these reinforcements.

Beyond Linear Response: Equivalence between Thermodynamic Geometry and Optimal Transport.

A fundamental result of thermodynamic geometry is that the optimal, minimal-work protocol that drives a nonequilibrium system between two thermodynamic states in the slow-driving limit is given by a geodesic of the friction tensor, a Riemannian metric defined on control space. For overdamped dynamics in arbitrary dimensions, we demonstrate that thermodynamic geometry is equivalent to L^{2} optimal transport geometry defined on the space of equilibrium distributions corresponding to the control parameters. We show that obtaining optimal protocols past the slow-driving or linear response regime is computationally tractable as the sum of a friction tensor geodesic and a counterdiabatic term related to the Fisher information metric. These geodesic-counterdiabatic optimal protocols are exact for parametric harmonic potentials, reproduce the surprising nonmonotonic behavior recently discovered in linearly biased double well optimal protocols, and explain the ubiquitous discontinuous jumps observed at the beginning and end times.