Rapid Design Research Articles

Non-volatile double-tunable vortex metalens design based on Sb2S3 using deep neural network and particle swarm optimization algorithm

A dual-tunable vortex metalens is proposed that leverages deep neural network (DNN) and particle swarm optimization algorithm (PSO), incorporating the use of the phase-change material Sb2S3, which enables simultaneous tunable of both the focal length of the focused vortex beam and the topological charge. The control of traditional vortex metalens relies on changing the polarisation state of the incident light; however, its control range is limited. We employed neural network algorithms to learn the complex mapping relationship between the unit structure and the phase, achieving a fast and accurate prediction of the vortex metalens's phase. Compared with traditional simulation methods, the application of this neural network significantly reduces the time consumption of the design process and avoids the need for re-simulation. Furthermore, our design transcends limitations associated with specific wavelengths and enables the rapid design of tunable metalens across the 1–1.5 μm wavelength range, offering flexibility for the development of dual-tunable metalens. Based on this scheme, we simulated vortex metalens with tunable focal length and topological charge, and the results showed that the simulation results were consistent with the theoretical predictions.

An analytical method for free vibrations of the fuel rod with non-uniform mass of small modular reactor

The intricate internal structure of fuel rods results in a non-uniform mass distribution, making it imperative to employ analytical methods for accurate assessment. The study utilizes Euler beam theory to derive the transverse vibration equation for beams with varying mass distribution. The approach involves transforming the non-uniform mass beam into a multi-segment beam with concentrated mass points. Modal function relationships between adjacent uniform segments are established based on continuous conditions at connection points. This transformation leads to the conversion of the variable coefficient differential equation into a nonlinear matrix equation. The Newton-Raphson method is then applied to calculate the characteristic equation and mode shapes, essential for determining natural frequencies. To validate precision, the results obtained are compared with those derived from the finite element method. Furthermore, the developed method is employed to assess the impact of gas plenum location and length on the natural frequency of fuel rods. The proposed methodology serves as a rapid design tool, particularly beneficial during the design phase of fuel rods with non-uniform mass distribution, aiding in configuring structural aspects effectively.

Finite Element Simulation Parameter Calibration and Verification for Stem Cutting of Hydroponic Chinese Kale

The finite element simulation is a valid way for the rapid development of the root-cutting mechanism for hydroponic Chinese kale. The stem of the hydroponic Chinese kale was simplified as a transverse isotropic elastic body, and axial compression, three-point bending, and shear tests were performed. The ANSYS/LS-DYNA19.2 software was adopted for stem shear simulation, and the regression equation of the maximum simulated shear force was established. The optimized mechanical parameters were determined by minimizing the deviation between the maximum shear force obtained from the simulation and test. The three-dimensional scanning method was employed to establish the geometric model of the hydroponic Chinese kale stem. The cutting finite element simulation model and test platform were constructed. Displacement, deformation, and force measured from simulation and test were compared. Through measurement and simulation calibration, an axial elastic modulus of 6.22 MPa, axial Poisson’s ratio of 0.46, radial elastic modulus of 3.56 MPa, radial Poisson’s ratio of 0.44, radial shear modulus of 0.8 MPa, and a failure strain of 0.08 were determined. During the cutting simulation and test, the resulting maximum displacement deviations of the marking points on the end of the stem were 0.68 mm along the X-axis and 2.83 mm along the Y-axis, while the maximum deviations of the cutting and clamping force were 0.49 N and 0.77 N, respectively. The deformation and force variation laws of the kale stem in the cutting simulation and test process were basically consistent. It showed that the mechanical parameters calibrated by the simulation were accurate and effective, and the stem cutting simulation results with the finite element method were in good agreement with that of the cutting test. The study provided a reference for the rapid optimization design of the root-cutting mechanism for hydroponic Chinese kale harvest.

Rapid design for large-scale parallel CFRP cable with multi-source experimental data

With advancements in material properties and reduced costs, carbon fibre reinforced polymer (CFRP) cables are gaining popularity in engineering applications due to their superior strength-to-mass ratio and durability. However, the tensile strength of large-scale parallel CFRP cables remains a critical issue, warranting further research and engineering expertise. To address this issue, this paper proposes a method to rapidly predict and adaptively correct the tensile strength of large-scale parallel CFRP cables using multi-source experimental data and an integrated approach that incorporates Monte Carlo simulations, Neural Network algorithms, and Genetic algorithms. This comprehensive method takes into account the influence of various factors including small-scale material strength and its coefficient of variation, cable length, the number of parallel wires, installation errors, and anchorage errors. Validated by reported experimental data, the method demonstrates its effectiveness in accurately predicting the tensile strength of parallel CFRP cables. Moreover, a design method for large-scale parallel CFRP cables is proposed based on the reliability theory. Lastly, the efficiency and effectiveness of the proposed method are validated through the design and optimization of a cable-stayed bridge featuring a main span of 1984 m, utilising both parallel steel and CFRP cables.

Rapid, iterative design approach for preliminary configuration of a High Altitude, Long Endurance aircraft

This paper presents a rapid iterative design approach, used to develop a preliminary configuration of an Unmanned Aerial Vehicle (UAV), which is to perform a High-Altitude, Long Endurance (HALE) mission. First, based on a set of requirements, an initial aircraft concept is developed.The rapid iterative design approach revolves around an energy-based flight profile simulation, which is updated with an improved aerodynamic model of the aircraft during every iteration. An aircraft configuration is defined by a set of constant parameters. A corresponding flight profile consists of an altitude and velocity profile, as a function of time. The behaviour of the aircraft is simulated based on the specified flight profile.For sizing the aircraft components exposed to the airstream, the aerodynamic design phase aims to create an airframe which achieves the performance outlined in the flight performance simulation, utilizing the obtained aircraft parameters. Using the geometric data, a 3D-model of the aircraft is created, which is essential for the aircraft’s weight and balance calculations and for determining the airframe shape exposed to the airflow. A Computational Fluid Dynamics (CFD) simulation is conducted to obtain the actual aerodynamic characteristics of the airframe. If the performance requirement of the flight performance simulation is not met, another iteration of the aerodynamic design phase is required.The design framework stands out due to its rapid iteration capability, accessibility, and straightforward application, making it particularly advantageous for educational settings in which students engage with aircraft design. The approach aims to offer satisfactory results for an initial aircraft conceptualization.This design framework emerged from the DLR Design Challenge 2023, an annual competition hosted by the German Center for Aerospace Research, where student teams develop preliminary aircraft designs. This years challenge tasked the teams with designing an aircraft system to restore internet coverage over a disaster-affected region. The described approach was used to develop the Sentinel System of the DHBW Ravensburg team. However, the simulation and development process is not limited to applications within this challenge.

Use of a micro acoustic chamber for rapid iterative design, teaching, and demonstration in the development of innovative lower-carbon mass timber assemblies

Mass timber construction offers a range of benefits to the design industry, including the potential for sustainability and reduced building embodied carbon, biophilia, speed of assembly, and prefabrication. However, these benefits can create acoustical challenges for sound isolation between spaces. Thus, the University of Oregon’s Institute for Health in the Built Environment, in collaboration with the TallWood Design Institute, has developed a micro acoustic chamber as a conceptual testbed, educational resource, and demonstration tool for design professionals and students, to develop new and innovative mass timber acoustic assemblies, understand acoustic implications of material choices in composite form, and comparatively analyze the performance of acoustic detailing decisions more rapidly at a small scale. The chamber hosts specimens that are 813 mm × 813 mm and up to 300 mm thick, far smaller than a typical laboratory acoustic floor/ceiling assembly test chamber, creating known limitations; however, test samples can be cost and material efficient, allowing relative performance differences between assemblies to be evaluated quickly and easily for initial design feedback. This presentation will share how the use of a micro acoustic chamber has been integrated into design education, student, and industry pilot research to accelerate the development of mass timber acoustic solutions.

Accelerated design of Al−Zn−Mg−Cu alloys via machine learning

A machine learning-based alloy rapid design system (ARDS) was proposed to customize the preparation strategies for the desired properties or predict the alloy properties following the preparation strategies. For achieving this, three regression algorithms: linear regression (LR), support vector regression (SVR), and back propagation neural network (BPNN), were employed separately to train the multi-property prediction model, in which the machine learning (ML) model built using SVR was proved to be the best. Then, inspired by the generative adversarial network (GAN) algorithm, the ARDS was constructed. The predictive reliability of ARDS was examined, and for the accurate prediction of the preparation strategies, the upper limits of ultimate tensile strength (UTS), yield strength (YS), and elongation (EL) are about 790 MPa, 730 MPa, and 28%, respectively. Moreover, an ARDS-designed aluminum alloy with superior mechanical properties (764 MPa for UTS, 732 MPa for YS, and 10.1% for EL) was experimentally fabricated, further verifying the reliability of ARDS.

Modular vector assembly enables rapid assessment of emerging CRISPR technologies

The diversity of CRISPR systems, coupled with scientific ingenuity, has led to an explosion of applications; however, to test newly described innovations in their model systems, researchers typically embark on cumbersome, one-off cloning projects to generate custom reagents that are optimized for their biological questions. Here, we leverage Golden Gate cloning to create the Fragmid toolkit, a modular set of CRISPR cassettes and delivery technologies, along with a web portal, resulting in a combinatorial platform that enables scalable vector assembly within days. We further demonstrate that multiple CRISPR technologies can be assessed in parallel in a pooled screening format using this resource, enabling the rapid optimization of both novel technologies and cellular models. These results establish Fragmid as a robust system for the rapid design of CRISPR vectors, and we anticipate that this assembly approach will be broadly useful for systematic development, comparison, and dissemination of CRISPR technologies.

Printing PEDOT:PSS optimized using Response surface method (RSM) and genetic algorithm (ga) via modified 3D printer for perovskite solar cell applications

Despite significant improvements in solar cell fabrication processes, there are still significant challenges in the fabrication technology owing to poor production efficiency, large equipment and preparatory costs, substrate dependencies, material limitation, etc. This research proposes the use of a modified extrusion-based three-dimensional (3D) printing technology to print thin films of PEDOT:PSS (Poly 3,4-ethylenedioxythiophene:poly styrene sulfonate) for perovskite solar cell (PSC) applications and beyond. The main objective of the research is to induce the benefits of 3D printing technology into thin film printing for PSC applications. The central composite design (CCD) of the response surface method (RSM) in design expert software (Design Expert V13) and a genetic algorithm (GA) in MATLAB software are used to design and optimize the experiment, respectively. Accordingly, a uniformly thin PEDOT:PSS film with a 115 nm thickness is printed with the modified 3D printer at a print speed of 82 mm/s, a bed temperature of 80 °C, and an extrusion start position of 160 mm with a 0.1 mm inner diameter blunt needle and a 0.25 mm x-distance offset. To validate the printed PEDOT:PSS film for PSC application, other PSC layers, except for aluminum electrodes, are spin-coated on top of the 3D-printed PEDOT:PSS film, and the PSC is tested for its performance using a solar simulator. From the test, a competitive open-circuit voltage of 860 mV was produced. In general, printing PSC layers by modifying a cheap and easily available 3D printer has the benefits of excellent material utilization, substrate independence, rapid design, manufacture, and testing of solar cells in the electronic industry.

Optimization of concentration parameters for maximizing bacteriophage recovery value using response surface methodology: A case study on determining the optimal concentration parameters for Erwinia amylovoraEA1T1.B3 phage

AbstractBacteriophages have emerged as effective antimicrobial agents in combating pathogenic bacteria. To successfully apply phages in real‐life scenarios, it is crucial to optimize their large‐scale production, concentration and purification processes. In this study, our objective was to optimize the phage concentration parameters with a high recovery rate within a shorter time and minimum chemical consumption. We isolated and characterized a specific Erwinia amylovora phage. Subsequently, we employed response surface methodology (RSM) combined with a three‐factor central composite design to optimize the phage recovery. The factors considered were polyethylene glycol (PEG) concentration, NaCl concentration and incubation time. The optimized values for PEG, NaCl and incubation time, which resulted in a maximum recovery rate of 85.37%, were determined as 18%, 2.38 M and 0 h, respectively. This finding indicates that the concentration step, which traditionally took up to 18 h with a recovery rate of 65%, can now be accomplished in a significantly shorter time with an improved recovery rate. Our study demonstrates the effectiveness of RSM to identify the optimum conditions for phage precipitation. This approach allows for the rapid and efficient design of precipitation protocols tailored to specific bacteriophages, resulting in shorter processing times and higher recovery rates.

Design method for engineering the initial structure of a spectrometer.

A well-considered initial structure plays a key role in the design of an exceptional spectrometer. Previously, the design method for the optical initial structure (MOIS) that has only focused on the optical properties based on simple imaging formulas and coma-free conditions has been extensively researched. However, as the shape and size of any optical component are not considered for the MOIS, the optical parameters before and after optimization are very different, which results in a loss of reference value of the initial structure. In order to address the aforementioned issues, a more efficient design method for engineering initial structure (MEIS) of the spectrometer is proposed, where not only the above optical properties are considered but also the relative position and size of any optical component in order to avoid the interference between the optical components. For the MEIS, three important anti-interference conditions between components are deduced through ray tracing, and the relevant imaging formulas are derived by geometric optics, which leads to the rapid calculation of component parameters and the acquisition of an initial structure satisfying the corresponding design requirements by setting reasonable spacing margins. To verify the validity of the MEIS, a wide-band high-resolution spectrometer system with a large CCD Toucan 216 is designed within a wavelength range of 700-1000nm and a resolution of 0.5nm. Compared with the MOIS, the positions of each component in the MEIS are more rationalized, which significantly eliminates the complex optimization processes. For the MEIS, changes only in the position of the image plane occur with minimal variations in the axial and vertical wheelbase (less than 0.5mm) as well as the deflection angle (only 0.5°), with favorable evaluation indices. The MEIS has an important reference value for the rapid and efficient design of excellent spectrometers.

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System.

With the development of intelligent vehicle technology, the probability of road traffic accidents occurring has been effectively reduced to a certain extent. However, there is still insufficient research on head injuries in human vehicle collisions, making it impossible to effectively predict pedestrian head injuries in accidents. To study the efficacy of a combined active and passive safety system on pedestrian head protection through the combined effect of the exterior airbag and the braking control systems of an intelligent vehicle, a "vehicle-pedestrian" interaction system is constructed in this study and is verified by real collision cases. On this basis, a combined active and passive system database is developed to analyze the cross-influence of the engine hood airbag and the vehicle braking curve parameters on pedestrian HIC (head injury criterion). Meanwhile, a hierarchy design strategy for a combined active and passive system is proposed, and a rapid prediction of HIC is achieved via the establishment of a fitting equation for each grading. The results show that the exterior airbag can effectively protect the pedestrian's head, prevent the collision between the pedestrian's head and the vehicle front structure, and reduce the HIC. The braking parameter H2 is significantly correlated with head injury, and when H2 is less than 1.8, the HIC value is less than 1000 in nearly 90% of cases. The hierarchy design strategy and HIC prediction method of the combined active and passive system proposed in this paper can provide a theoretical basis for rapid selection and parameter design.

Stability Analysis of the Output Speed in a Hydraulic System Powered by an Inverter-Fed Motor

The stability of the output speed of a hydraulic system has a great influence on the working performance of hydraulic equipment. It changes with the system working conditions. The increase in leakage caused by the wear of the hydraulic kinematic pair and the slip of the motor lead to the instability of the output speed. Although the hydraulic system can satisfy the output requirements of the active control scheme with ex ante decision making or the passive feedback control strategy with ex post compensation, it also causes an increase in system complexity and manufacturing cost. The speed stiffness as a basic characteristic of the output of the hydraulic system has not been sufficiently investigated and evaluated. In this paper, the IFMDH (inverter-fed, motor-driven hydraulic) system is taken as the object, and the coupling relationship of each link of the system is revealed by mathematical modelling. The reliability of the model is verified under a wide range of speed and load variations in combination with experiments. By redefining the speed stiffness quantification method, the effects of load conditions, motor stiffness, and speed ratio at the output end on the speed stability of the system are discussed in conjunction with the system coupling mechanism model. The conclusions show that the motor stiffness and the addition of a speed reducer have a significant effect on the system speed stiffness, where changing the output speed ratio has a significant effect on the speed stiffness. The conclusions of the study provide technical support for the rapid design, selection, and system optimisation of hydraulic systems in common scenarios.

Multi-Objective Optimization Design of an Origami-Inspired Combined Cushion Airbag

To improve the cushioning performance of soft-landing systems, a novel origami-inspired combined cushion airbag is proposed. The geometry size, initial pressure, and exhaust vent area of the cushion airbags are designed preliminarily using a theoretical model. The finite element models, including the returnable spacecraft and cushion airbags, are established via the control volume method (CVM) to analyze the impact dynamic behavior and cushioning performance during the landing attenuation process. The cushioning performance of the cushion airbags in complex landing environments are studied to investigate the influence of horizontal velocity, lateral velocity and nonhorizontal landing surfaces. Four design parameters of the cushion airbags, including the initial pressure, venting threshold pressure, exhaust vent area and polygon edge number, are employed to study their influence on the cushioning performance. A multi-objective optimization model of the cushion airbags based on the neural network and multi-objective water cycle algorithm is established to realize the rapid optimization design. The Pareto front of the maximum overload and specific energy absorption is obtained. The analysis results show that the maximum overload of the proposed combined cushion airbags is 7.30 g. The system with the anti-rollover design can avoid rollover and achieve outstanding cushioning performance in complex landing environments. The maximum overload of the returning spacecraft is decreased by 16.4% from 7.30 g to 6.10 g after multi-objective optimizations. This study could provide the technical support for the soft-landing system design of returnable spacecrafts.

UV-assisted robotic arm freeforming of SiOC ceramics from a preceramic polymer

Material extrusion is a very common and facile additive manufacturing technique for ceramic materials, allowing for rapid design and fabrication of 3D structures without expensive tools. However, fabricating sophisticated structures with large spanning parts and overhanging features using this technology is still a challenge. Here, UV-assisted additive manufacturing is enabled by performing material extrusion with the assistance of UV light using mixture of a preceramic polymer and a photopolymer. The rheological properties of the ink were investigated under UV light radiation to optimize the printing parameters to achieve excellent printability. Complex ceramic structures were fabricated with this method, such as spiral and truss structures, which would be very difficult to obtain using traditional material extrusion without sacrificial supports. These structures have potential application in lightweight ceramic components, such as sandwich structures.

Enhanced anti-cancer potency of sustainably synthesized anisotropic silver nanoparticles as compared with L-asparaginase

Acute lymphoblastic leukemia (ALL), a hematologic cancer that involves the production of abnormal lymphoid precursor cells, primarily affects children aged 2 to 10 years. The bacterial enzyme L-asparaginase produced from Escherichia coli is utilised as first-line therapy, despite the fact that 30 % of patients have a treatment-limiting hypersensitivity reaction. The current study elucidates the biosynthesis of extremely stable, water-dispersible, anisotropic silver nanoparticles (ANI Ag NPs) at room temperature and investigation of its anti-tumor potency in comparison to L-asparaginase. The optical, morphological, compositional, and structural properties of synthesized nanoparticles were evaluated using UV–Vis-NIR spectroscopy, Transmission Electron Microscopy (TEM), Fourier Transform Infrared Spectroscopy, and X-ray Diffractometer. The UV–Vis-NIR spectra revealed the typical Surface Plasmon Resonance (SPR) at 423 nm along with additional NIR absorption at 962 nm and 1153 nm, while TEM images show different shapes and sizes of Ag nanoparticles ranging from 6.81 nm to 46 nm, together confirming their anisotropic nature. Further, the MTT assay demonstrated promising anticancer effects of ANI Ag NPs with an IC50 value of ∼7 μg/mL against HuT-78 cells. These sustainable anisotropic silver nanoparticles exhibited approximately four times better cytotoxic ability (at and above 10 μg/mL concentrations) than L-asparaginase against HuT-78 cells (a human T lymphoma cell line). Apoptosis analysis by Wright-Geimsa, Annexin-V, and DAPI staining indicated the role of apoptosis in ANI Ag NPs-mediated cell death. The measurement of NO, and Bcl2 and cleaved caspase-3 levels by colorimetric method and immunoblotting, respectively suggested their involvement in ANI Ag NPs-elicited apoptosis. The findings indicate that the biogenic approach proposed herein holds tremendous promise for the rapid and straightforward design of novel multifunctional nanoparticles for the treatment of T cell malignancies.

Analysis method of permanent magnet eddy current brake under impact load

Permanent magnet eddy current brake (PMECB) with high damping performance is widely used in engineering vibration suppression and braking. In this study, based on the braking dynamics of PMECB under impact load, the analysis method related to the damping characteristics are established, including a static magnetic model with flux leakage, a uniform damping force model with demagnetization effect and skin effect, and an acceleration damping force model with magnetic field distortion. The comparison of the analysis method, numerical simulation and experimental results verifies that the analysis method can reproduce the damping law under impact load. The results show that the maximum displacements of the analysis method and numerical simulation deviate from the experimental results within 3%. The analysis method can complete the calculation of the damping characteristics within a few seconds. The variations of the thickness, conductivity of the conductive cylinder, and air gap thickness have significant effects on the nonlinear and critical characteristics of the velocity-damping force curve, which can be corrected by changing the coefficients in the analysis method. In summary, the proposed analysis method can provide insights for rapid engineering design and optimization calculation of the PMECB by its completeness, accuracy, adaptability and rapidity.

Rapid Design Method of Heavy-Loaded Propeller for Distributed Electric Propulsion Aircraft

On Distributed Electric Propulsion (DEP) aircraft, the deployment of numerous high-lift propellers with small diameters on the wing’s leading edge significantly enhances lift during low-speed flight. The increase in the number of propellers leads to a decrease in diameter, which increases the disc loading. In this paper, a rapid design method applicable to heavy-loaded propellers is developed and does not require iterative calculations compared to traditional heavy-loaded propeller design methods, enabling rapid completion of the propeller design. The results of CFD computation show that the relative thrust error of the method proposed in this paper is within 5% for disc loading ranging from 600 Pa to 1400 Pa, features a high-accuracy design of propellers with required thrust, and high thrust coefficients are achieved within large advance ratio range.

Inverse artificial neural network assisted rapid multiband antenna design for multiple custom requirements

Inverse artificial neural network assisted rapid multiband antenna design for multiple custom requirements

Rapid Design of an ICU Ventilator: An Approach Based on Smart Switching of Compressed Air-Oxygen.

Breathing support is provided by regulating volume or pressure of lungs using ventilators. Due to COVID-19 pandemic, there was a sudden shortage of resuscitating devices such as ventilators. Additionally, ventilators being one of the primary critical care devices are also very costly. In order to address this situation, a number of low-cost designs have been proposed, however, many of these lack either an efficient control system or a hardware comparable to a standard ICU ventilator. In this regard, this article presents a comprehensive cost-effective solution that covers all aspects of the ventilator design (named as NED-Vent) such as hardware/pneumatic assembly, electronic design, user interface and control system. The proposed design works on compressed air-oxygen switching via proportional valves to produce basic volume and pressure modes as well as their derivatives such as assist ventilation, intermittent ventilation and spontaneous modes. The NED-Vent also features an interactive single-knob-single-touch user interface along with an automated mechanism for adjusting air-oxygen ratio in breathing gas mixture as an improvement on existing designs. The pressure regulated control is based on two mathematical models of human lungs with dynamic lung parameters estimated using machine learning approach. Additionally, the controller is tuned to optimized stability using Jury's Test and Ziegler-Nichols methods. The obtained results of breath profile are validated for the employed mathematical models (SLSC & SLMC) as well as the tuning methods in compliance with the tolerances provided by international standards.