Geometric Variables Research Articles

High-Throughput Spectroscopy of Geometry-Tunable Arrays of Axial InGaAs Nanowire Heterostructures with Twin-Induced Carrier Confinement.

Predicting the optical properties of large-scale ensembles of luminescent nanowire arrays that host active quantum heterostructures is of paramount interest for on-chip integrated photonic and quantum photonic devices. However, this has remained challenging due to the vast geometrical parameter space and variations at the single object level. Here, we demonstrate high-throughput spectroscopy on 16800 individual InGaAs quantum heterostructures grown by site-selective epitaxy on silicon, with varying geometrical parameters to assess uniformity/yield in luminescence efficiency, and emission energy trends. The luminescence uniformity/yield enhances significantly at prepatterned array mask opening diameters (d0) greater than 50 nm. Additionally, the emission energy exhibits anomalous behavior with respect to d0, which is notably attributed to rotational twinning within the InGaAs region, inducing significant energy shifts due to quantum confinement effects. These findings provide useful insights for mapping and optimizing the interdependencies between geometrical parameters and electronic/optical properties of widely tunable sets of quantum nanowire heterostructures.

Performance sensitivity analysis and aerodynamic optimization of compressor cascades by a turbulence adjoint method

Sensitivity, which is useful for evaluating the contributions of input variations to output changes, favors designers exploiting the most sensitive design parameters and completing design optimization in aerospace. This study introduces the turbulence adjoint method due to its low computational cost in calculating sensitivities with high accuracy and then solves the adjoint partial differential equations with respect to both the Reynolds-averaged Navier–Stokes and turbulence model equations with the assistance of an automatic differentiation tool. By utilizing the turbulence adjoint method, the sensitivities of aerodynamic performance to the blade profile modifications of two-dimensional and three-dimensional compressor cascades are calculated, allowing for the investigations of the impact of geometric variations on the changes in the flow field. Ultimately, aerodynamic optimization of the compressor cascades is conducted. After optimization, the adiabatic efficiency of the two-dimensional cascade increases by 3.11%, and it increases by 1.15% for the three-dimensional cascade. The variations in flow fields of both the original and optimized cascades are illustrated to discover the origins of performance improvements. The changes in blade profile are almost consistent with those forecasted from sensitivity analysis, demonstrating the potential superiority of the adjoint method for aerodynamic design.

TopoSinGAN: Learning a Topology-Aware Generative Model from a Single Image

Generative adversarial networks (GANs) have significantly advanced synthetic image generation, yet ensuring topological coherence remains a challenge. This paper introduces TopoSinGAN, a topology-aware extension of the SinGAN framework, designed to enhance the topological accuracy of generated images. TopoSinGAN incorporates a novel, differentiable topology loss function that minimizes terminal node counts along predicted segmentation boundaries, thereby addressing topological anomalies not captured by traditional losses. We evaluate TopoSinGAN using agricultural and dendrological case studies, demonstrating its capability to maintain boundary continuity and reduce undesired loop openness. A novel evaluation metric, Node Topology Clustering (NTC), is proposed to assess topological attributes independently of geometric variations. TopoSinGAN significantly improves topological accuracy, reducing NTC index values from 15.15 to 3.94 for agriculture and 14.55 to 2.44 for dendrology, compared to the baseline SinGAN. Modified FID evaluations also show improved realism, with lower FID scores: 0.1914 for agricultural fields compared to 0.2485 for SinGAN, and 0.0013 versus 0.0014 for dendrology. The topology loss enables end-to-end training with direct topological feedback. This new framework advances the generation of topologically accurate synthetic images, with applications in fields requiring precise structural representations, such as geographic information systems (GIS) and medical imaging.

Numerical Investigation of Two-Phase Shock Waves in CO2 Flows Using a Modified Hertz–Knudsen Model

Abstract Understanding the complex behavior of two-phase shocks in CO2 flows is essential for a variety of applications, including carbon capture and storage () and transcritical refrigeration cycles. This study presents a comprehensive numerical investigation of two-phase shock waves using the multispecies user-defined real gas model in Ansys Fluent. The simulations are performed for de-Laval nozzles, exploring the two-phase shock features for three-dimensional (3D), two-dimensional (2D), and two-dimensional axisymmetric geometries. The nonequilibrium condensation, subsequent evaporation, and denucleation occurring across the shock are modeled through a set of user-defined scalar transport equations implemented within Ansys Fluent. The two-phase computational fluid dynamics (CFD) simulations are carried out in proximity to the critical point where real gas effects are relevant. The CO2 real gas properties are computed using an in-house Python code and integrated into the solver via user-defined functions as external look-up tables. This study provides valuable insights into the physical processes underlying two-phase shocks in CO2 flows and their sensitivity to geometric variations and thermodynamic conditions. The findings contribute to the development and modification of predictive models and optimized designs for systems involving two-phase CO2 flows. The results highlight the influence of geometry configurations and thermodynamic conditions on shock location and intensity, providing comparisons for shock waves occurring in two-phase flows and supercritical single-phase flows.

Neural fields for rapid aircraft aerodynamics simulations

This paper presents a methodology to learn surrogate models of steady state fluid dynamics simulations on meshed domains, based on Implicit Neural Representations (INRs). The proposed models can be applied directly to unstructured domains for different flow conditions, handle non-parametric 3D geometric variations, and generalize to unseen shapes at test time. The coordinate-based formulation naturally leads to robustness with respect to discretization, allowing an excellent trade-off between computational cost (memory footprint and training time) and accuracy. The method is demonstrated on two industrially relevant applications: a RANS dataset of the two-dimensional compressible flow over a transonic airfoil and a dataset of the surface pressure distribution over 3D wings, including shape, inflow condition, and control surface deflection variations. On the considered test cases, our approach achieves a more than three times lower test error and significantly improves generalization error on unseen geometries compared to state-of-the-art Graph Neural Network architectures. Remarkably, the method can drastically accelerate high fidelity numerical solver, achieving a five order of magnitude speedup on the RANS transonic airfoil dataset.

Current-Induced Field-Free Switching of Co/Pt Multilayer via Modulation of Interlayer Exchange Coupling and Magnetic Anisotropy

Current-induced field-free magnetic switching using spin–orbit torque has been an important topic for decades due to both academic and industrial interest. Most research has focused on introducing symmetry breakers, such as geometrical and compositional variation, pinned layers, and symmetry-broken crystal structures, which add complexity to the magnetic structure and fabrication process. We designed a relatively simple magnetic structure, composed of a [Co/Pt] multilayer and a Co layer with perpendicular and in-plane magnetic anisotropy, respectively, with a Cu layer between them. Current-induced deterministic magnetic switching was observed in this magnetic system. The system is advantageous due to its easy control of the parameters to achieve the optimal condition for magnetic switching. The balance between magnetic anisotropic strength and interlayer coupling strength is found to provide the optimal condition. This simple design and easy adjustability open various possibilities for magnetic structures in spin-based electronics applications using spin–orbit torque.

AdapTUI: Adaptation of Geometric-Feature-Based Tangible User Interfaces in Augmented Reality

With the advents in geometry perception and Augmented Reality (AR), end-users can customize Tangible User Interfaces (TUIs) that control digital assets using intuitive and comfortable interactions with physical geometries (e.g., edges and surfaces). However, it remains challenging to adapt such TUIs in varied physical environments while maintaining the same spatial and ergonomic affordance. We propose AdapTUI, an end-to- end system that enables an end-user to author geometric-based TUIs and automatically adapts the TUIs when the user moves to a new environment. Leveraging a geometry detection module and the spatial awareness of AR, AdapTUI first lets users create custom mappings between geometric features and digital functions. Then, AdapTUI uses an optimization-based adaptation framework, which considers both the geometric variations and human-factor nuances, to dynamically adjust the attachment of the user-authored TUIs. We demonstrate three application scenarios where end-users can utilize TUIs at different locations, including portable car play, efficient AR workstation, and entertainment. We evaluated the effectiveness of the adaptation method as well as the overall usability through a comparison user study (N=12). The satisfactory adaptation of the user-authored TUIs and the positive qualitative feedback demonstrate the effectiveness of our system.

Influence of Pnictogen and Ligand Framework on the Lewis Acidity and Steric Environment in Pnictogen Pincer Complexes.

Pnictogen pincer complexes are a fascinating class of compounds due to their dynamic molecular and electronic structures, and valuable stoichiometric or catalytic reactivity. As recognition of their unique chemistry has grown, so too has the library of pincer ligands employed and pnictogen centres engaged to prepare them. Here we computationally study how the choice of pincer ligand framework and pnictogen influence the electronic and steric outcomes of the complexes obtained. The most relevant electronic parameter is the pnictogen-centred electrophilicity, which has been quantified by fluoride ion affinities and LUMO energies, while the most relevant steric parameter is the crowding around the central pnictogen, which has been quantified by the %Vbur values and visualized using steric maps. The resulting trends are analyzed with reference to binding pocket size, acceptor orbital type, electronic delocalization, π-donor strengths, and heteroatom incorporation. Thus, considering 16 ligand frameworks and 4 heavy pnictogen centres, this study provides a broad-spectrum view of stereo-electronic variation in pnictogen pincer complexes, which, together with a recent study on geometric variation in the same family, provides a substantial dataset to guide future molecular design and reactivity studies.

Inverse-designed 3D sequential metamaterials achieving extreme stiffness

Mechanical metamaterials signify a groundbreaking leap in material science and engineering. The intricate and experience-dependent design process poses a challenge in uncovering architectural material sequences with exceptional mechanical properties. This study introduces inverse-designed 3D sequential metamaterials with outstanding mechanical attributes, achieved through a novel computational framework. The explored sequences based on Schoen's I-graph–wrapped package (IWP) and Schwarz Primitive (Schwarz P) surpass the Hashin-Shtrikman upper bound of Young's modulus at relative densities of 0.24 and 0.43, outperforming previous records. Optimized Body-Centered-Cubic (BCC) truss-based sets outperform traditional ones by 72.7%. This innovative approach can be extended for metamaterial customization, involving the optimization of multi-directional Young's modulus, total stiffness, and the addition of isotropy constraints. The paper explores the characteristics and implications of this innovation, emphasizing the impact of geometric and topological variations on mechanical performance. These metamaterial sequences offer unparalleled adaptability, and hold significant potential in structural engineering and adaptive mechanical systems, opening avenues for technological advancements.

Geometric morphological variation characteristics of loropetalum chinense leaves (r. Br.) Oliv. (hamamelidiaceae) and their response to intra-specific competition

This study aimed to explore the geometric morphological variation characteristics of the leaves of the understory plant Loropetalum chinense under different competitive pressures. Specifically, the leaf morphological indices were calculated, and multiple comparison analysis and Fisher linear discriminant model were employed to decipher the morphological variability based on contour outlines. The results revealed that the leaf morphological indices exhibited significant differences among various sample plots. The lower stand density and DBH (diameter at breast height) facilitated more water and air exchange and led to a rounded leaf shape. The results provided a theoretical basis for the study of response of leaf morphological evolution to forest competition. Bangladesh J. Bot. 53(3): 681-687, 2024 (September) Special

Geometric morphologic variation ormosia henryi prain leaves from different hunan provenances

This study was envisaged to explore the variation characteristics of Ormosia henryi Prain leaves from four different areas of Hunan provenance of China based on analyzing the geometric morphologic information of the leaf. Specifically, the leaf morphological indices were firstly calculated, and multiple comparison analysis, canonical analysis of the principal coordinates and fisher linear discriminant model were employed to decipher the morphological variability based on contour outlines. The results showed that the leaf morphological indices exhibited significant differences between the samples of different areas. Variability also exists between the Ormosia henryi of four areas of the provenance. The results provide a theoretical basis for the study of genetic diversity and genetic improvement of Ormosia henryi. Bangladesh J. Bot. 53(3): 773-781, 2024 (September) Special

Research and clearance analysis on of steam twin-screw expander employed in indutrial waste heat recovery

In actual factories, screw expanders frequently operate under partial loads.To address the lack of theoretical research and the risks of errors in engineering design associated with steam pressure differential power generation under these conditions,a simulation of the twin-screw expander's working process was developed. The rotor profile was designed, geometric variables such as rotor mesh clearance were calculated, and models for leakage and heat transfer were established. A suction pressure correction model was proposed for the suction process under partial loads, along with correction parameters to simplify simulations.Experimental results demonstrate that the twin-screw expander operates stably under highly fluctuating conditions, demonstrating excellent variable load performance.As the load decreases, the loss of suction pressure reduces the expander's pressure differential, leading to lower leakage and improved efficiency. When the load is reduced from 100 % to 65 %, the volumetric efficiency increases from 78.87 % to 84.76 %, and the isentropic efficiency rises from 66.81 % to 74.25 %.Compared to experimental data, the flow calculation error of the suction pressure correction model presented in this study is controlled within 3 %.This model addresses performance calculations under partial loads, ensuring that theoretical models better align with real-world applications and supporting accurate selection of twin-screw expanders.This model enables appropriate selection of expanders to reduce pressure losses and enhance economic efficiency.

Impact response of 3D printed cornstalk-inspired structures: The effect of indenter shape on penetration

This paper reports the mechanical response and damage tolerance of 3D-printed cornstalk-inspired structures subjected to impact loading. Specimens were subjected to dynamic indentation tests at multiple impact energies with flat, hemispherical, and conical indenters. The mechanical properties of the base material (ABS) were measured across varying strain rates using a Shimadzu® Universal Testing Machine and a Split Hopkinson Pressure Bar. The effect of geometrical variations of the constituents on energy-absorbing capability was also investigated. Damage characteristics were interrogated through X-ray CT scans and provided detailed failure modes associated with each indenter shapes. Further, finite element simulations provided insights into the penetration mechanisms associated with the different indenter shapes. The results demonstrated that test specimens impacted by flat indenters absorbed ∼25 % less energy than those impacted by hemispherical and conical indenters. Among the various indenters, the conical shape had the highest duration of contact force within the specimen before experiencing failure by matrix cracking and complete perforation.

Comparative Analysis of Modular Pin-Fin Heat Sink Performance: Influence of Geometric Variation on Heat Transfer Characteristics

The advancement of digital technology in the age of Industrial Revolution 4.0 has driven other engineering sectors to keep up with the progressive demand for high-performance computing and electronics. Thermal management plays a critical role in maintaining the performance of electronic devices by keeping the system temperature at an optimal level and preventing overheating. A heat dissipation device widely employed in computing and other electronic systems’ heat management is a fin-type heat sink, owing to its robust and simple design. In this work, the authors evaluated heat sinks of different pin-fin cross-sectional geometry, arranged in a staggered configuration, in terms of heat transfer characteristics under forced convection. Three basic geometries were chosen on the grounds of manufacturing easiness and market availability: circular, square, and hexagonal. All the tested geometries had approximately the same hydraulic diameter. Therefore, the results could be compared to each other. The investigation revealed that the square cross-section induced an excellent convection coefficient, hence higher heat dissipation, compared to the counterparts. The tradeoff between heat transfer performance and size-related parameters, such as surface area and material volume, is also discussed in this paper.

Spatial analysis of Holocene delta compound clinoforms

Recognition of compound delta clinoforms has led to a new understanding of delta progradation and architecture. Limited study has been dedicated to spatially delineate three dimensional morphologies of subaqueous deltas and their migration away from active sediment sources. Qualitative and quantitative analyses of 38 Holocene deltas lead to the observation of two main gradient breaks at tens-of-meters water depth and variable subaqueous geometries. Geometric variability was captured relative to riverine-sediment sources and basinal energies and presents steeper shoreline and subaqueous delta clinoforms, reaching 1°, separated by a gently-dipping 0.11° platform with widths from few kilometers (Ebro Delta) to 200 kilometers (Amazon Delta). In wave-dominated systems, the platform is absent ahead of the sediment source but widens laterally away as a smooth arcuate surface, whereas in tide-dominated systems the platform widens ahead of active sources and narrows ahead of starved ones while hosting erosional features and tidal channel/bar couplets.

Thermodynamics-Informed Neural Networks for the Design of Solar Collectors: An Application on Water Heating in the Highland Areas of the Andes

This study addresses the challenge of optimizing flat-plate solar collector design, traditionally reliant on trial-and-error and simplified engineering design methods. We propose using physics-informed neural networks (PINNs) to predict optimal design conditions in a range of data that not only characterized the highlands of Ecuador but also similar geographical locations. The model integrates three interconnected neural networks to predict global collector efficiency by considering atmospheric, geometric, and physical variables, including overall loss coefficient, efficiency factors, outlet fluid temperature, and useful heat gain. The PINNs model surpasses traditional simplified thermodynamic equations employed in engineering design by effectively integrating thermodynamic principles with data-driven insights, offering more accurate modeling of nonlinear phenomena. This approach enhances the precision of solar collector performance predictions, making it particularly valuable for optimizing designs in Ecuador’s highlands and similar regions with unique climatic conditions. The ANN predicted a collector overall loss coefficient of 5.199 W/(m2·K), closely matching the thermodynamic model’s 5.189 W/(m2·K), with similar accuracy in collector useful energy gain (722.85 W) and global collector efficiency (33.68%). Although the PINNs model showed minor discrepancies in certain parameters, it outperformed traditional methods in capturing the complex, nonlinear behavior of the data set, especially in predicting outlet fluid temperature (55.05 °C vs. 67.22 °C).

Efficient photon-pair generation in layer-poled lithium niobate nanophotonic waveguides

Integrated photon-pair sources are crucial for scalable photonic quantum systems. Thin-film lithium niobate is a promising platform for on-chip photon-pair generation through spontaneous parametric down-conversion (SPDC). However, the device implementation faces practical challenges. Periodically poled lithium niobate (PPLN), despite enabling flexible quasi-phase matching, suffers from poor fabrication reliability and device repeatability, while conventional modal phase matching (MPM) methods yield limited efficiencies due to inadequate mode overlaps. Here, we introduce a layer-poled lithium niobate (LPLN) nanophotonic waveguide for efficient photon-pair generation. It leverages layer-wise polarity inversion through electrical poling to break spatial symmetry and significantly enhance nonlinear interactions for MPM, achieving a notable normalized second-harmonic generation (SHG) conversion efficiency of 4615% W−1cm−2. Through a cascaded SHG and SPDC process, we demonstrate photon-pair generation with a normalized brightness of 3.1 × 106 Hz nm−1 mW−2 in a 3.3 mm long LPLN waveguide, surpassing existing on-chip sources under similar operating configurations. Crucially, our LPLN waveguides offer enhanced fabrication reliability and reduced sensitivity to geometric variations and temperature fluctuations compared to PPLN devices. We expect LPLN to become a promising solution for on-chip nonlinear wavelength conversion and non-classical light generation, with immediate applications in quantum communication, networking, and on-chip photonic quantum information processing.

Coordination of energy loss and fish friendliness for a low-head tubular-pump blade based on a multi-objective optimization model

Tubular pumps and turbines are the water-to-electricity conversion devices widely used in pumped hydro storage systems for low heads and high flow rates. An ecological concern is the high proportion of fish injuries caused by the rotating blades. In this study, a tubular pump blade is retrofitted to balance the energy loss and fish friendliness through multi-objective optimization, combining computational fluid dynamics with a mathematical blade strike model. Sensitivity analysis identifies nine geometric variables out of thirteen for optimizing blade design. An approximation model is developed to implement optimization algorithm and achieve the objective function. By artificially assigning weights to targeted performance metrics, three scenarios are obtained: the optimal efficiency scheme (A), the optimal fish friendliness scheme (C) and the balanced scheme (B). Scheme C achieves a fish survival ratio of 100 % at multiple flow rates (for fish lengths of Lf/D=1/12), but results in a 6.4 % decrease in efficiency compared to scheme A. Additionally, a negative blade attack angle can improve flow pattern. Considerable reduction in fish mortality can be obtained by equipping the rotor with a larger size but lower shaft speed, while also limiting the fish size to pass through the pump running at a reduced flow rate.

Simulation model for electrical and agricultural productivity of an olive hedgerow Agrivoltaic system

Given the need to promote a more sustainable energy model that contributes to the fight against Climate Change and the consequent advancement of photovoltaics, Agrivoltaics is presented as a solution to the conflict over land use, since it makes it possible to reconcile agricultural production and photovoltaic power simultaneously on the same piece of land. However, it is a new production model and there are still many aspects to research. This work presents a mathematical model to simulate the spatial distribution of the solar radiation in the canopy of the crop of an agrivoltaic plant in which N-S solar trackers are alternately combined with olive groves in hedgerows. In this way, simulation has the advantage of predicting the expected behaviour of one or more configurations of agrivoltaic installations and, on the basis of this simulated behaviour, making decisions during the design phase to optimize their performance. To do this, various models have been integrated to simulate both the behaviour of irradiance on its way from the Sun to the crop, using geometric-vector analysis, and the irradiance absorption processes on its way through the canopy of the crop. Thus, the global model presented allows estimating the electrical and oil production of an agrivoltaic plant such as the one described. From this global model, electrical and oil productions have been systematically simulated for a set of agrivoltaic plants whose design parameters range around the intermediate values of an agrivoltaic facility with olive groves in hedgerows spaced 10 m apart and alternated with 3 m wide and 3 m hight N-S solar trackers. For this intermediate facility, the annual productions of oil and electricity are 789kg/year·ha and 891MWh/year·ha, respectively. Finally, the oil and energy productions of all the simulated agrivoltaic facilities and their design parameters have been interrelated obtaining mathematical equations to determine in a simple way the influence on the productions of the geometrical design variables of the agrivoltaic installation (height of the solar trackers, width of the collectors and distance between hedgerows). Therefore, the model presented makes it possible to advance in the evaluation of the possible integration of olive groves in agrivoltaic systems and their profitability, constituting an important benefit for the implementation of agrivoltaics in the Mediterranean regions where olive groves play a significant role in agricultural production systems.

Natural geometrical variations of Italian Phyllostachys edulis bamboo culms for construction purposes

Amid the increasing scarcity of raw materials, utilizing bamboo as a renewable building material offers significant environmental and economic benefits for the European construction sector. However, in Europe, the use of bamboo for construction remains limited due to a lack of studies on geometrical and material characteristics of European-cultivated bamboo species. Although bamboo is not typically grown in Europe, the number of bamboo plantations is steadily increasing in countries like Spain, France and Italy. Bamboos growing in temperate climates, however, are exposed to different environmental conditions during growth compared to bamboos from subtropical and tropical climates, such as those in China or Vietnam. As bamboo’s geometric properties are strongly influenced by the environmental conditions during growth, it is essential to investigate how bamboo culms of the same species grown in Europe compare to those from other regions. The present article reports findings on the geometry and geometric imperfections of 90 four-meter Italian bamboo culms. First, the Italian Phyllostachys edulis bamboo culms examined in this study are briefly introduced. Following, geometric imperfections of bamboo culms are defined, and the geometry measurement concept is presented. Subsequently, variations in internode lengths, diameters, wall thicknesses, ovalities, stem tapers and pre-deflections are described and analyzed. Finally, the findings from the Italian culms are compared with those from Asian Phyllostachys edulis. In summary, this article enhances the understanding of the geometric properties of bamboo grown in Europe, thereby advancing the use of cultivated bamboo culms in Europe and improving the overall understanding of bamboo characteristics across different climatic zones.