Dimensional Parameters Research Articles

Effect of maxillary molars distalization using clear aligners and fixed orthodontic appliances on the positional and dimensional temporomandibular joint parameters: a three-dimensional comparative study

Effect of maxillary molars distalization using clear aligners and fixed orthodontic appliances on the positional and dimensional temporomandibular joint parameters: a three-dimensional comparative study

Design and Experimental Demonstration of Wavelength‐Selective Metamirrors on Sapphire Substrates

The increasing demand for novel mirror coating designs for new generation of gravitational wave detectors is stimulating significant research interest in investigations of reflective properties of metasurfaces. Given this strong interest, this article details a systematic methodology for fabricating reflecting metasurfaces (metamirrors) designed to operate at target wavelengths of 1064 or 1550 nm. The proposed metasurfaces consist of silicon cylindrical nanoparticles placed on a sapphire substrate. First, the dimensional parameters of the structures are thoroughly selected through numerical simulations combined with material characterization. The configurations are subsequently analyzed analytically to reveal the mirror effect, which arises from the excitation of electric and magnetic dipole moments. Following this, the metasurfaces are fabricated and experimentally characterized, demonstrating reflectivity exceeding 95% around the design wavelengths, which is in good agreement with theoretical predictions. Overall, the work demonstrates the feasibility and detailed methodology for the fabrication of thin, lightweight metamirrors capable of achieving near‐perfect reflectivity at the specified target wavelengths.

A Matrix-Based Approach to Unified Synthesis of Planar Four-Bar Mechanisms for Motion Generation With Position, Velocity, and Acceleration Constraints

Abstract This paper introduces a novel matrix-based approach for the simultaneous type and dimensional synthesis of planar four-bar linkage mechanisms, accommodating various practical constraints, including position, velocity, acceleration, and joint placements. Traditional design processes segregate type synthesis, the determination of joint and link configurations, from dimensional synthesis, which involves specifying link sizes and pivot locations. This segregation often leads to complexities in addressing the complete design challenge. The novel methodology proposed in this paper departs from the conventional sequential design approach by concurrently evaluating type and dimensional parameters using a data-driven matrix formulation. The crux of the paper’s methodology involves formulating a singular design equation through a transformation matrix, parameterized by the Cartesian parameters of the mechanism’s dyads. This formulation linearly expresses a broad range of constraints, facilitating the identification of viable solutions through singular value decomposition and null space analysis. This integrated approach not only simplifies the synthesis process but also provides direct insights into the mechanism’s parameters, encompassing both type and dimensions, thereby obviating the need for further interpretative steps common to the use of quaternions and kinematic mapping. In essence, the paper presents two main contributions: the development of a unified design equation capable of encompassing a wide array of constraints within the mechanism synthesis process, and the introduction of an algorithm that effectively identifies all potential planar four-bar linkage mechanisms by accurately satisfying up to five constraints. This approach promises to enhance the design and optimization of mechanical systems by offering a more holistic and efficient pathway to mechanism synthesis.

Changes in the ideal body shape associated with adolescent rowing-ergometry performance following a 6-week training intervention: New scaling insights using three-dimensional allometry.

Scaling, to remove the effects of body size, is an important methodological approach for enabling an equitable comparison of performance differences between individuals who vary in anthropometric characteristics. Many previous studies using scaling in sport have done so based on only one or two anthropometric characteristics, with only one study to date adopting a three-dimensional approach. To apply a three-dimensional allometric model to rowing ergometer performance (REP) in adolescents, and to detect whether key 'scaling' parameters remain stable when scaling REP both before and after a 6-week training intervention. Novel three-dimensional allometric models were used, incorporating body mass, stature and waist circumference (WC) to detect the most appropriate body size dimension(s) and scaling parameters associated with REP before and after a 6-week training intervention. Using this more flexible and sensitive three-dimensional allometry demonstrated that, following 6-weeks of training, there was a change in the ideal body shape associated with REP. Before training, taller, but not heavier, adolescents performed better. After 6-weeks of training, older participants with a greater body mass but smaller WC performed better. Scaling approaches are important for evaluating performance differences between individuals of differing body size. The findings from the current study (using a novel three-dimensional allometry approach) emphasise that relatively subtle changes in individuals' behavioural characteristics, such as changes in their training/fitness status, can result in quite dramatic changes in the body dimension characteristics and scaling parameters deemed to be key for performance in activities such as REP.

Simultaneous Optimization Approach for UV-C Radiator to Enhance Mechanical Properties of Semi-Finished Potato Tuber (Innovator) for Extended Storage Period

The efficacy of surface treatment technology is highly dependent on the dimensional and operational parameters. UV-C as a commonly used surface treatment technology required fine-tuning to achieve maximum storability of semi-finished products. This study therefore applied a simultaneous optimization approach for the multi-objective function to obtain the best possible combination of variables in the irradiation process (dose (15-45mJ/cm2, storage period (3-9d), and distance from the light (40-80cm)) that offer maintained properties of semi-finished potato tuber for extended storage life. The optimum values are obtained at the ~40.5mJ/cm2, 7 days, and 48cm granting a 756N, 6.7N, and 9N for compressive, bending, and cutting force resistance, respectively. Further insight into the surface functionality was studied using FT-IR and SEM analysis as a result similar spectral makeup was noted but a shift of absorption peak was observed in the irradiated sample at 30 and 45mJ/cm2. Also, a similar granular structure was observed from the morphologies.

Generation of broadband airborne ultrasound using an Harmonic Acoustic Pneumatic Source

This paper presents a new type of airborne transducer for generating broadband ultrasound with a high Sound Pressure Level (SPL). The concept is based on the Harmonic Acoustic Pneumatic Source (HAPS) that uses pressurized air in conjunction with a flow chopper made up of a rotating cage with slots connected to a specific exhaust. The fundamental frequency depends on the number of slots and the rotation speed of the cage. An analytical model of the HAPS coupled with a numerical model of the exhaust is used to predict the radiated acoustic pressure and to estimate the influence of dimensional parameters on pressure level generated by the source. Experiments are conducted with two cages: one with one slot in order to generate pulses periodically and one with 122 slots to generate periodic sound. The level of sound pressure is measured as a function of distance (0.004 to 0.5 m), the cage rotation (up to 11 krpm) and directivity (0 to 90°). For the fundamental frequency at 22 kHz, the maximum SPL of 150 dB (632 Pa rms) is /measured at 0.004 m, and decreases to 122 dB (35 Pa rms) at 0.5 m. At 0.5 m, the second and third harmonics can generate a SPL equal or greater than 115 dB above 22 kHz and up to 66 kHz. Discrepancies between the experiments results and numerical model are observed in terms of SPL, directivity and in-axis pressure.

Multi-biomarker approach for predicting cardiac magnetic resonance parameters at 30 days after ST-segment elevation myocardial infarction

Abstract Background Prior data showed associations of circulating Proprotein Convertase Subtilisin / Kexin type 9 (PCSK9) and inflammatory/anti-fibrotic Cellular Communication Network factor 1 (CCN1) at index ST-segment elevation acute myocardial infarction (STEMI) with left ventricular ejection fraction at 6 and 12 months, respectively and for CCN1 also with infarct size. Purpose PCSK-9, CCN1 and reference biomarkers high-sensitivity Troponin T (hsTNT) and N-terminal pro-brain natriuretic peptide (NTproBNP) were measured in patients from the CLEVER-ACS trial (clinicaltrials.gov NCT01529554) at presentation with STEMI and correlated with clinically relevant cardiac magnetic resonance (CMR) parameters at 30 days. Methods Associations between baseline biomarkers (PCSK-9, CCN1, hsTNT, NTproBNP) and CMR parameters at 30 days were evaluated using Spearman correlation and linear regression analysis (dichotomised at their median). Receiver operating characteristic (ROC) and area under the curve (AUC) were determined for significant values based on correlation analysis; AUC > 0,7 considered relevant. CMR parameters comprised left ventricular structural and functional parameters including scar mass and microvascular obstruction. Results We identified 56 STEMI patients (mean age 61.7 ± 11.2 (SD) years) who completed 30 days follow-up with biomarker data. Among biomarkers, significant associations with CMR parameters were only found for hsTNT, and NTproBNP. The strongest associations were found for left ventricular ejection fraction (LVEF; hsTNT RSp =-0.66; NTproBNP RSp =-0.57), left ventricular scar (LVSCAR; hsTNT RSp =0.58; NTproBNP RSp =0.56) and scar mass (SM; hsTNT RSp =0.65; NTproBNP RSp =0.55). Conversely, left ventricular end-diastolic volume index (LVEDVI; hsTNT RSp =0.47; NTproBNP RSp =0.32), left ventricular end-systolic volume index (LVESVI; hsTNT RSp =0.51; NTproBNP RSp =0.39) and microvascular obstruction (MVO; hsTNT RSp =0.34; NTproBNP RSp =0.34) were significantly, albeit only modestly associated. ROC and AUC analysis yielded relevant associations of biomarkers with CMR parameters LVEF (hsTNT=0.79; NTproBNP=0.81), LVSCAR (hsTNT=0.84; NTproBNP=0.76) and scar mass (hsTNT=0.83; NTproBNP=0.78). Furthermore, relevant associations of biomarkers with CMR were found for LVEDVI (hsTNT=0.79; NTproBNP=0.72), LVESVI (hsTNT=0.84; NTproBNP=0.72) and MVO (hsTNT=0.72; NTproBNP=0.71). Conclusion Baseline levels of hsTNT and NT-proBNP are strong predictors for functional and dimensional CMR parameters of the left ventricle including clinically relevant imaging surrogates of myocardial injury shortly after STEMI.ROC LVEF

Evaluation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using a high figure-of-merit plasmonic multimode refractive index optical sensor

In recent years, following the outbreak of the COVID-19 pandemic, there has been a significant increase in cases of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and related deaths worldwide. Despite the pandemic nearing its end due to the introduction of mass-produced vaccines against SARS-CoV-2, early detection and diagnosis of the virus remain crucial in preventing disease progression. This article explores the rapid identification of SARS-CoV-2 by implementing a multimode plasmonic refractive index (MMRI) optical sensor, developed based on the split ring resonator (SRR) design. The Finite Difference Time Domain (FDTD) numerical solution method simulates the sensor. The studied sensor demonstrates three resonance modes within the reflection spectrum ranging from 800 nm to 1400 nm. Its material composition and dimensional parameters are optimized to enhance the sensor’s performance. The research indicates that all three resonance modes exhibit strong performance with high sensitivity and figures of merit. Notably, the first mode achieves an exceptional sensitivity of 557 nm/RIU, while the third mode exhibits a commendable sensitivity of 453 nm/RIU and a Figure of Merit (FOM) of 45 RIU−1. These findings suggest that the developed MMRI optical sensor holds significant potential for the early and accurate detection of SARS-CoV-2, contributing to improved disease management and control efforts.

Nonlinear vibration analysis of sandwich plates with inverse-designed 3D auxetic core by deep generative model

Building on a deep generative model (DGM), this paper introduces an innovative sandwich plate structure featuring an inverse-designed auxetic 3D lattice core and conducts a detailed investigation of its nonlinear vibration characteristics and effective Poisson's ratios under various parameter settings. By incorporating a conditional estimator and quality loss evaluation functions, the enhanced conditional generative adversarial networks are capable of designing 3D truss auxetic topologies that achieve customized negative Poisson's ratios without reliance on subjective experience. Additionally, lattice specimens are created using 3D metal printing, and the mechanical properties of these DGM-based 3D auxetic structures are validated through vibration experiments and finite element models. These structures exhibit significantly superior natural frequencies compared to those obtained through conventional topology optimization methods reported in existing literature. The study also explores the impact of different functionally graded configurations, temperature variations, boundary conditions, and dimensional parameters on the natural frequency, nonlinear vibration response, and effective Poisson's ratio of the inverse designed auxetic sandwich plates.

Dot-array porous medium model for windscreen and its simulation accuracy analysis

Porous medium models have long been prevalent numerical computation tools. Although they exhibit swift computational speed, their accuracy in simulating windscreen perforation structures is challenged. This paper introduces the innovative dot-array porous medium (DAPM) model, which accurately portrays the perforation structure and material characteristics of a windscreen by establishing virtual holes on the porous medium. Not only does it simplify modeling by eliminating complex perforation processes, but it also adeptly simulates the flow behavior of the windscreen. The comprehensive comparison between the DAPM model and the physical mesh model, traditional porous medium model, as well as wind tunnel test results, demonstrates that the DAPM model not only possesses rapid computational speed but also delivers outstanding precision in results. In terms of velocity distribution, vortex distribution, and flow intensity in the flow field, the model indicates a high level of accuracy, clearly exceeding that of the porous medium model. Moreover, the DAPM model showcases high versatility and adjustability in practical applications. By adjusting dimension parameters, it demonstrates the capability to precisely simulate any windscreen with holes arranged in a matrix pattern. This research provides an efficient and reliable tool for the numerical simulation of windscreens, with broad application prospects.

Compact Ultra-Wideband MIMO Antenna for 5G Communication Systems

Ultra-wideband (UWB) technology is highly respected in modern communication systems because it can enable high-speed, high-data-rate communication over short distances. It is still difficult to achieve optimal multiple-input multiple-output (MIMO) performance in real-world multipath settings, even with breakthroughs in traditional antenna designs. UWB-MIMO antenna solutions have been created and simulated in order to address this problem and fulfill present demands. Nevertheless, maintaining high antenna efficiency and the requirement for antenna designs tailored to a particular bandwidth are two of the difficulties UWB systems must overcome. Recently, a variety of optimization strategies have been employed to obtain high gain and UWB performance by fine-tuning antenna characteristics. The major obstacles are resolved by the optimization process, including the time and computational resource requirements. The difficulty is further compounded by the intricacy of accurately modifying antenna settings to maximize gain. A multi-objective advancement for the design and improvement of the reduced UWB-MIMO test radio wire for 5G was offered as a solution to these problems. In order to attain the UWB feature, we first aim to use a single elliptical-square form antenna that operates from 3.4 to 70 GHz with isolation larger than 29.54 dB. Furthermore, we optimize the impedance bandwidth by tuning the parameters of the structural dimensions using the improved proportional topology optimization (IPTO) technique. Additionally, we present the orthogonal correction using the binarized convolutional neural network (BCNN).

Design and analysis of a thick-panel origami-inspired soft crawling robot with multiple locomotion patterns

Abstract Due to the flexibility obtained through both materials and structures, soft robots have wide potential applications in complicated internal and external environments. This paper presents a new soft crawling robot with multiple locomotion patterns that integrate inchworm motion and various turning motions. First, the conceptual design of the proposed robot is presented by introducing thick-panel origami into the synthesis of a crawling robot, resulting in a Waterbomb-structure-inspired hybrid mechanism. Second, all locomotion patterns of the robot are precisely described and analyzed by screw theory in an algebraic manner, which include inchworm motion, restricted planar motion, quantitative turning motion, and marginal exploration motion. Then, the output motion parameter for each locomotion pattern is analytically modeled as a function of the robotic dimensional parameters, and the robot can thus be designed and controlled in a customized way for the expected output motion. Finally, the theoretical analysis and derivations are validated by simulation and physical prototype building, which lay the foundations for the design and manufacture of small-scale soft crawling robots with precise output motions in a complex planar environment.

Hard rock fragmentation by dynamic conical pick indentation under confining pressure

Mechanical mining and excavation in deep metal mines can be regarded as the process of crushing hard rock by conical pick indentation. In this study, a confining pressure loading device was designed and used to carry out dynamic conical pick indentation crushing tests under confining pressure conditions on three types of granite with varying strengths, using the Split Hopkinson Pressure Bar (SHPB). The objective was to quantitatively investigate the effect of confining pressure and rock strength on the indentation crushing characteristics of deep hard rocks. The results indicate that as the confining pressure increases from 5 MPa to 20 MPa, the dimensional parameters such as volume, diameter and depth of the impact groove decrease linearly, while parameters such as the specific energy, indentation force, indentation index and energy utilization rate progressively increase. The increase in the confining pressure inhibits the formation of internal cracks in the rock, enhancing its resistance to pick indentation, which in turn makes rock fragmentation more difficult. This creates unfavorable conditions for efficient rock breaking. Furthermore, rock strength plays a crucial role in the pick indentation process. The higher the rock strength, the greater its resistance to pick indentation, leading to increased energy consumption, accelerated wear of the conical picks, and reduced efficiency in rock breaking.

Graphene nanoribbon resonant tunneling diode with dual connection between contacts

In this paper, we numerically study the transport properties of a resonant tunneling diode (RTD) based on graphene nanoribbon (GNR) with an H-type antidote between the contacts. The structure may also be thought of as having two parallel (W-shape) parts connecting the contacts, each having a wider channel region sandwiched between two narrower barrier regions. The energy at which quasi-bound states occur in each part depends on the dimensional parameters of the respective portion in the structure. We study how the transmission through quasi-bound states is influenced by the edge states on the contacts and dimensional parameters such as barrier length and also by the ambient temperature. The results are compared with those of an RTD with a single part connecting the contacts. Transmission peaks at different energies are observed for an RTD with asymmetrical lower and upper parts between the contacts. This is then utilized for the creation of two negative differential resistance (NDR) peaks. For numerical computation, the non-equilibrium Green’s function formalism (NEGF) based on the nearest neighbor tight-binding model is employed.

Prediction on seismic performance levels of reinforced concrete beams by considering crack development

The plastic rotation angle or deflection is typically used as the indicator to evaluate the earthquake-induced damage and classify the seismic performance levels of reinforced concrete (RC) beams. Herein, one of the most important issues is to determine the seismic performance level limits of RC beams. Whereas, different countries provided their specific method to determine the limit values by considering the loading-carrying capacity of RC beams, which could not be used to describe the earthquake-induced seepage of structures, especially for underground structures. Therefore, in this study, the seismic performance level limits of RC beams were predicted by using the machine learning methods and considering the development of cracks. Firstly, the seismic performance level limits of RC beams were presented after discussing the methods in different codes and the development of cracks. Then an earthquake performance test database of RC beams was established after collecting 452 test results of RC beams, and Pearson correlation analysis was conducted for feature selection to determine the input mechanical parameters and dimensional parameters for machine learning. Meanwhile, the correlation between the inputs and limit values was analyzed using the mutual information method. Regression models of seven machine learning methods were then established to predict the performance level limits of RC beams, and the hyperparameters of the machine learning models were optimized with the TPE optimization algorithm and cross-validation. The generalization ability of the prediction models was evaluated and the accuracy of predicted results by different methods was analyzed. Finally, the predicted seismic performance level limits of RC beams could be used to evaluate the earthquake-induced damage of RC beams by combining them with the seismic behavior of RC beams.

Design and static and dynamic analysis of floor vibration isolators for high-speed train.

With the increasing speed of high-speed train, it is more and more difficult to reduce the vibration and noise inside the train. The floor of the train, as a carriage component in direct contact with passengers, is of great significance to improve its vibration and sound isolation performance to ensure the comfort of passengers. In this article, a floor vibration isolator with quasi-zero stiffness is designed based on the dimensional parameters of the traditional floor vibration isolator, and the vibration isolation performance is analyzed by the finite element model of the floor vibration isolator from the static and dynamics aspects, respectively. The load-displacement curves of the floor vibration isolator are obtained through static simulation calculations, and the dynamic analysis of the floor vibration isolator is carried out by simulation methods, which verifies the low-frequency vibration isolation performance of the floor vibration isolator under different working conditions, and the vibration isolator has a good prospect for development.

Uniformity enhancement of flow field through optimizing nozzle structure for jet electrochemical machining

To improve the processing quality during the Jet electrochemical machining (JECM) process, a single-orifice nozzle and dual-orifice nozzles with different inclination angles were designed, where the fluid dynamic behavior was numerically simulated. Then, through the L49 (74) orthogonal design and error analysis, the influence of nozzle dimension on the flow field characteristics was analyzed. Finally, the nozzle with optimal structure and dimension was obtained and validated by experiment. Results show that the dual-orifice nozzles had better flow field uniformity than the single-orifice nozzle. In the dual-orifice nozzle, the increase of the inlet inclination angle can improve the flow field uniformity. The influence of the nozzle dimension parameters on the flow field uniformity is prioritized as follows: the outlet slit width > upper chamber diameter > the height of the inflow chamber > the height of the transition chamber. After optimization, the optimal dimension parameters were obtained under the upper chamber diameter of 16 mm, the jet outlet slit width of 0.4 mm, the height of the inflow chamber of 7 mm, and the height of the transition chamber of 23 mm. The flow velocity dispersions under the pressures of 0.3, 0.4, and 0.5 MPa can be reduced by 25.41 %, 25.17 %, and 28.16 %. The findings can help understand the flow behavior and guide the structure optimization for improving JECM quality.

Energy harvesting from transverse galloping using a two-degree-of-freedom flow energy harvester

Abstract A two degree-of-freedom (2-DOF) galloping piezoelectric energy harvesting system where both oscillators are excited by the incoming flow is studied in this paper. A coupled lumped-parameter model is developed to simulate the electro-fluid-structural coupling behaviour assuming a quasi-steady aerodynamic flow field. The differential equations governing the dynamics of the lumped system are converted into nonlinear algebraic equations employing the harmonic balance method (HBM) and then solved using Newton’s method. The approximate analytical solutions are compared to the solutions obtained by numerical integration, and the results agree, both qualitatively and quantitatively. The solutions were subsequently used to investigate the effects of the bluff body dimension, mechanical, electrical, aerodynamic, and electromechanical parameters on the performance of the harvester and to illustrate how to optimise some of these parameters to reduce the cut-in wind speed and maximise the power output of the energy harvester. It will be shown that the energy harvesting performance could be significantly improved by introducing piezoelectric transducers on both oscillators and including both masses in the incoming flow. A comparative study between the proposed 2-DOF flow energy harvesting system, a single-degree-of-freedom (SDOF) galloping piezoelectric energy harvester (GPEH), and other configurations of 2-DOF GPEH shows that the present 2-DOF GPEH generates the largest power peak.

Accurate numerical calculation method for liquid crystal phase shifter loaded with metallic NaM

ABSTRACT Metallic Nanowire Filled Membrane (NaM) exhibit immense potential in enhancing liquid crystal phase shifters (LCPSs) performance. However, conventional numerical calculation methods are inadequate for accurately simulating LCPSs loaded with NaM due to the significant dimensional disparities between the nanoscale NaM and the millimetre or even centimetre-scale LCPS. In this paper, a novel calculation technology is proposed to accurately simulate the electromagnetic (EM) response of LCPSs integrated with NaM, including phase shift and figure of merit (FoM). The effective constitutive tensors of the NaM are extracted and utilised to construct the EM model for characterising the NaM properties. Three NaM-LCPSs are simulated using the proposed EM model and compared with measurement results. The findings reveal that the proposed calculation method exhibits an error of less than 20%, while previously reported numerical calculation method demonstrated error as high as 60%. Furthermore, leveraging the proposed calculation method, the performance of a NaM-LCPS is optimised by systematically varying its dimensional parameters. The results demonstrate a substantial improvement in the FoM of the NaM-LCPS, increasing from 67°/dB to 120°/dB, significantly expanding the potential applications of NaM-LCPSs.

Resonant-mode metasurface thermal super mirror by deep learning-assisted optimization algorithms

A “super-mirror” having ultrahigh infrared reflectance is achieved by an optimized photonic contrast grating metasurface. Finding ways to achieve this exceptional performance can be enabled by implementing global optimization and machine learning elements, such as Bayesian optimization and genetic algorithm. Here, we acquired an optimized grating design made of high-index germanium, which excites resonances that result in ultralow emittance at certain wavelengths. Our optimizations assisted in the discovery of hybridized coupling of Fabry-Pérot modes and guided modes in a monolithic microscale multilayered coating. We demonstrate constraints in the given geometric variable ranges improves the overall performance of algorithms. We also show the enhanced performance of a deep learning Feedforward Neural Network, which is implemented as the inverse design using the network trained with dataset obtained from Bayesian optimization and Genetic Algorithm approaches. The performance of the Feedforward Neural Network-assisted design produced normal emissivity difference by only +3.5 %, with lower sensitivity to grating dimensional parameter variations. The improvement is achieved by predicting and better understanding of the optical physics of resonant gratings. The proposed few-layer grating coating can be applied to space components, enclosures, and vessels to suppress thermal radiative heat loss.