Parametric Design Research Articles

Grid-connected virtual synchronous generator transient suppression based on proportional differential control and frequency low-pass filtering

Abstract The virtual synchronous generator (VSG) technology has a wide range of applications in various distributed generation units. However, sudden changes in power command at grid connection can lead to severe oscillations in the output power and frequency of virtual synchronous generators. In addition, existing oscillation suppression methods are either based on complex parameter designs or change the original inertial support characteristics and power frequency drop characteristics. In this paper, a new transient suppression method is proposed, i.e., a proportional differential controller is added behind the power error and an additional low-pass filter is placed behind the output frequency. Finally, by establishing a simulation platform, it is verified that the proposed scheme can greatly reduce the overshoot, regulation time and frequency offset of the active power.

Analysis and Controller Design for Parameter Varying T-S Fuzzy Systems with Markov Jump

In this paper, we investigate a novel T-S fuzzy parameter varying system with Markov jump, in which parameters depend not only on a Markov chain but also on linear parameter varying elements that take values in convex polytopic sets. Stable conditions and the gain-scheduling controller design method for this system are obtained. Applying Lyapunov function depending on the operation mode and full block S-procedure lemma, we obtain stochastic stabilization conditions. We find that this novel system has two distinct advantages. On the one hand, it inherits the advantages of traditional T-S fuzzy systems in handling nonlinear objects under the frame of T-S fuzzy systems; on the other, it obtains the advantages of dealing with time-varying characteristics from the point of linear parameter varying (LPV) systems. Finally, the theory results are illustrated via numerical simulation.

Optimization of BIPV Utilization with Parametric Approach: Case Study on Nearly Zero Carbon Building Studio Design in Medan, Indonesia

Buildings significantly consume fossil energy, leading to substantial carbon emissions contributing to global warming and rising sea levels. These environmental impacts pose serious challenges, necessitating a shift towards sustainable building designs. By integrating clean energy solutions into building architecture, we can reduce the environmental burden of emissions. This approach mitigates adverse effects on living organisms and ecosystems and promotes long-term sustainability and resilience in urban development. Building-Integrated Photovoltaic (BIPV) systems represent one such approach for substituting fossil energy. However, implementing BIPV effectively necessitates comprehensive analysis considering numerous parameters and variables. This paper introduces building design strategies employing the BIPV approach. The decision-making process in designing alternatives utilizes parametric methods, recognized for their ability to yield optimization results for various variables through the development of design algorithms. The study focuses on the design of a studio building at the University of North Sumatra. Comparative analysis of the results obtained through parametric design aims to identify the most favorable design outcomes. The research includes developing a parameterized design algorithm, workflow, and assessment results for selecting optimal design alternatives. The results indicate that the placement of PV panels on the side area (PVOS) has more potential than placement on the top area (PVOT). Despite the PVOT area being observed to be 0.57% smaller than PVOS, PVOS shows a significant increase in total Incident Radiation (IR), average IR, and total Energy Generated by 137.14%, 128.40%, and 132.97%, respectively.

Design of nonlinear locking mechanism for shape memory alloy archwire of miniature orthodontic device

The locking mechanism between bracket and shape memory alloy (SMA) archwire in the newly developed domestic orthodontic device is the key to controlling the precise alignment of the teeth. To meet the demand of locking force in clinical treatment, the tightening torque angle of the locking bolt and the required torque magnitude need to be precisely designed. For this purpose, a design study of the locking mechanism is carried out to analyze the correspondence between the tightening torque angle and the locking force and to determine the effective torque value, which involves complex coupling of contact, material and geometric nonlinear characteristics. Firstly, a simulation analysis based on parametric orthogonal experimental design is carried out to determine the SMA hyperelastic material parameters for the experimental data of SMA archwire with three-point bending. Secondly, a two-stage fine finite-element simulation model for bolt tightening and archwire pulling is established, and the nonlinear analysis is converged through the optimization of key contact parameters. Finally, multiple sets of calibration experiments are carried out for three tightening torsion angles. The comparison results between the design analysis and the calibration experiments show that the deviation between the design analysis and the calibration mean value of the locking force in each case is within 10%, and the design analysis method is valid and reliable. The final tightening torque angle for clinical application is determined to be 10° and the rated torque is 2.8 N∙mm. The key data obtained can be used in the design of clinical protocols and subsequent mechanical optimization of novel orthodontic devices, and the research methodology can provide a valuable reference for force analysis of medical devices containing SMA materials.

Development of a personalized mask design method using three-dimensional scan data

Purpose This study aims to develop a novel design method to make personalized masks for the effective prevention of pandemic respiratory infectious disease.Design/methodology/approachThe changes in facial shape during speaking were analyzed using a three-dimensional (3D) scanning technique. In total, 13 anthropometric items were measured, and mask patterns were generated using a parametric pattern design method. Three sizing methods were proposed to reflect not only static but also dynamic body dimensions on the mask patterns.FindingsA significant increase or decrease was observed in 10 out of 13 measurement items. Based on this, four items were selected to be used in the mask pattern design. The nose and cheek areas of a mask were fixed to protect the respiratory tract against viruses. The lower jaw area was deformed to improve the fit.Social implicationsThis study is expected to provide fundamental data to understand the changes in facial shape during movement. In addition, it is expected that the development of individualized personal protective equipment with movement adaptability will facilitate an effective response to various pandemic respiratory diseases.Originality/valueIn order to develop a personal protective equipment (PPE) that has a good fit and can protect against pandemic respiratory infectious diseases, morphological analysis was attempted using 3D facial data. It would be possible to design various products and equipment to be worn on the face by using the method proposed in this study.

Fracture mechanics of bi-material lattice metamaterials

The advent of additive manufacturing technology empowers precise control of multi-material components or specific defects in lightweight lattice metamaterials, however, fracture mechanics and toughening design strategies in such metamaterials remain enigmatic. By incorporating theoretical analysis, numerical simulation, and experimental investigation, our study reveals that stretch-bend synergistic strut deformations caused by bi-material components or topology defects contribute notably tougher lattice structures surpassing its ideal single-material lattices. A peak fracture energy at a critical modulus ratio was found in a designed bi-material lattice composed of triangular soft struts and hexagonal stiff struts, which originates from the shift of fracture modes at crack tip from strut bending to stretching dominated failure modes as the modulus of soft struts increases, where the compromise in competition between bending-enhanced and stretching-weakened energy dissipations of struts deformations results in the maximized fracture energy. A parametric design protocol was proposed to optimize fracture energy of bi-material lattices through tuning the modulus ratio and relative density. Furthermore, the concept of stretch-bend synergistic toughening can also be applied to make tougher single-material lattices with specific topological defects. Our findings not only provide physical insights into directing crack propagation but also provide quantitative guidance to optimize fracture resistance within low-density tough lattice metamaterials.

Multi-Objective Optimization of a Folding Kinetic Facade System Proposal for Thermal, Daylight, and Energy Performances

Efficient utilization of daylight and energy resources significantly influences the quality of indoor spaces, user comfort, and overall efficiency. This study presents a folding facade proposal through the design alternatives offered by kinetic architecture and parametric design to enhance efficiency. This alternative design method integrates and coordinates the design components simultaneously and makes any intervention easier when compared with traditional design methods. In this context, the method is based on computational models, aiming to find the most efficient design alternative by optimization. The proposed facade design specifically targets an indoor office space within a university. The modular system, integrated into existing windows, facilitates a folding movement. This dynamic feature aims to optimize illumination within the space, effectively controlling daylight without causing disruptions to users. Simultaneously, the design seeks to balance energy consumption and ensure thermal comfort. The results show that it provides a significant improvement over the base case. The proposed kinetic façade system improved indoor thermal comfort by 22.09-31.99% while slightly increasing energy use (2% at most). Although it provided an average of 59% improvement in spatial Daylight Autonomy (sDA), 13.30% - 87.38% was achieved compared to the base case. However, the desired value by LEED was achieved very little in Annual Sunlight Exposure (ASE). In conclusion, the proposed kinetic facade system proves to be a valuable intervention for enhancing the indoor environment of an office space at Dokuz Eylül University

Parametric design methodology for yoke-magnetization in magnetic flux leakage detection systems

Magnetic flux leakage (MFL) testing is a widely employed non-destructive testing (NDT) method, particularly for ferromagnetic materials. This paper proposes a systematic design procedure for the yoke-magnetization component in MFL systems utilizing permanent magnets. The dimensions of the yoke-magnetization are parameterized, and the design methodology is formulated in the form of analytical equations based on fundamental engineering principles and optimization techniques. The proposed design procedure outlines all the required parameters and metrics to establish a yoke-magnetization configuration tailored for a specified application, thereby facilitating scalability. The theoretical framework identifies the optimal operating point that maximizes leakage flux while minimizing the magnetic field amplitude. A genetic algorithm is employed to minimize the dimensions of the permanent magnets while maintaining a sufficient magnetic field strength for specimen magnetization. An experimental setup is constructed to validate the accuracy of the proposed design procedure. The experimental results exhibit consistency with finite element method (FEM) simulations conducted using a case study. Specifically, the findings reveal that the thickness of the magnetic bridge significantly impacts the leakage fluxes at defect sites within the specimen. When the thickness of the magnetic bridge is 10 mm, slightly smaller than the optimal thickness of approximately 11 mm, the leakage flux at the defect site leaks out towards the surrounding air insignificantly. In contrast, a thickness of 15 mm is observed to strongly improve the leakage flux at the defect site.

A Comparative Evaluation of Conveyor Belt Disc Brakes and Drum Brakes: Integrating Structural Topology Optimization and Weight Reduction

Topology optimization is a well known and sophisticated method for designing structures. Through a finite element analysis, this method optimizes the design and material distribution to obtain an ideal strength-to-weight ratio and improved strain-to-weight ratio. This study involves the development of a comprehensive model for a brake using the ANSYS Parametric Design Language. The purpose of the model is to accurately characterize the geometry of the disc or drum. The technique of a complex eigenvalue analysis is used to identify the presence of unstable modes occurring at distinct frequencies, indicating instability. A braking force of 17,492 kN was exerted at a rotational velocity of 55 rad/s for 10 s. The optimization process resulted in significant mass reduction while maintaining structural integrity. In the drum brake, the mass was reduced from 114.01 kg to 104.07 kg, while the disc brake’s mass decreased from 68.81 kg to 56.68 kg.

Novel symmetry corrugate hierarchical honeycomb for superior crashworthiness

Honeycombs are extensively utilized as energy absorber due to their stabilized mechanical properties. Therefore, we propose a novel symmetry-corrugate hierarchical design strategy to construct symmetry-corrugate hierarchical honeycombs (SCHH). Crashworthiness and mechanical properties of SCHH are investigated by experiments and numerical simulation. SCHH exhibits a stable and efficient mechanical property in the compression test. Furthermore, numerical simulations have been conducted to investigate the parametric design of SCHH. The results show the effects of different period coefficients φT and amplitude coefficients φA on deformation modes and crashworthiness. Specifically, as φT increases and φA decreases, the deformation changes from progressive deformation mode (P-mode) to mixed deformation mode (M-mode) to global bending deformation mode (G-mode). P-mode and M-mode have better crashworthiness. The effect of φT on the crashworthiness of SCHH is more significant than φA. In addition, SCHH provides the highest crashworthiness compared with other honeycombs. Specifically, the energy absorption capacity and crushing stability are improved by 53.8 % and 68.5 %, respectively, compared with conventional honeycomb. Eventually, a crashworthiness prediction model of SCHH is developed by machine learning algorithms, and the model is verified to have high accuracy. In this study, the proposed strategy and methods are expected to further improve the crashworthiness of honeycomb.

Co-design studio with different design environments: Analogue design, designing within the design and parametric design

Co-design studio with different design environments: Analogue design, designing within the design and parametric design

A pointwise weighting prediction variance–high-dimensional model representation model-based global optimization approach for ship hull parametric design

Ship hull optimization techniques based on computer-aided design/computational fluid dynamics can effectively enhance the efficiency and stability of ship designs, with significant application prospects. To enhance the potential of ship hull optimization, increasing design variable dimensionality is essential, but can cause a significant increase in hydrodynamic simulations. To reduce simulations required for high-dimensional ship hull optimization, a new surrogate method, pointwise weighting prediction variance–high-dimensional model representation (PWPV-HDMR), which uses pointwise weighting prediction variance (PWPV) to aggregate different a priori assumptions, is developed. Moreover, a differential evolution algorithm is used to identify promising hull design parameters, using the PWPV-HDMR model instead of costly simulation as the fitness function. The proposed approach is tested on the hydrostatic resistance optimization of KRISO Container Ship. The results show that PWPV-HDMR outperforms kriging-HDMR, with a better resistance optimization effect, illustrating the effectiveness of the PWPV-HDMR-based global optimization approach in discovering promising ship hull parameters.

Parametric Design Method of Buildings Based on Convolutional and Deep Neural Networks

The application of AI technology in architectural software has brought various innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them, and analyzes the application of these technologies in architectural image recognition, generation, design optimization and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design. The application of AI technology in architectural software has brought numerous innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them; it also analyzes the application of these technologies in architectural image recognition, generation, design optimization, and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design.

Study on Vibration and Noise of Railway Steel–Concrete Composite Box Girder Bridge Considering Vehicle–Bridge Coupling Effect

A steel–concrete composite beam bridge fully exploits the mechanical advantages of the concrete structure and steel structure, and has the advantages of a fast construction speed and large stiffness. It is of certain research value to explore the application of this bridge type in the field of railway bridges. However, with the rapid development of domestic high-speed railway construction, the problem of vibration and noise radiation of high-speed railway bridges caused by train loads is becoming more and more serious. A steel–concrete composite beam bridge combines the tensile characteristics of steel and the compressive characteristics of concrete perfectly. At the same time, it also has the characteristics of a steel bridge and concrete bridge in terms of vibration and noise radiation. This feature makes the study of the vibration and noise of the bridge type more complicated. Therefore, in this paper, the characteristics of vibration and noise radiation of a high-speed railway steel–concrete composite box girder bridge are studied in detail from two aspects: the theoretical basis and a numerical simulation. The main results obtained are as follows: Relying on the idea of vehicle–rail–bridge coupling dynamics, a structural dynamics analysis model of a steel–concrete combined girder bridge for a high-speed railroad was established, and numerical program simulation of the vibration of the vehicle–rail–bridge coupling system was carried out based on the parametric design language of ANSYS 18.0 and the language of MATLAB R2021a, and the structural vibration results were analyzed in both the time domain and frequency domain. By using different time-step loading for the vehicle–rail–bridge coupling vibration analysis, the computational efficiency can be effectively improved under the condition of guaranteeing the accuracy of the result analysis within 100 Hz. Based on the power flow equilibrium equation, a statistical energy method of calculating the high-frequency noise radiation is theoretically derived. Based on the theoretical basis of the statistical energy method, the high-frequency noise in the structure is numerically simulated in the VAONE 2021 software, and the average contribution of the concrete roof plate to the three acoustic field points constructed in this paper is as high as 50%, which is of great significance in the study of noise reduction in steel–concrete composite girders.

Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI.

Geometric distortion is a serious problem in MRI, particularly in MRI guided therapy. A lack of affordable and adaptable tools in this area limits research progress and harmonized quality assurance. To develop and test a suite of open-source hardware and software tools for the measurement, characterization, reporting, and correction of geometric distortion in MRI. An open-source python library was developed, comprising modules for parametric phantom design, data processing, spherical harmonics, distortion correction, and interactive reporting. The code was used to design and manufacture a distortion phantom consisting of 618 oil filled markers covering a sphere of radius 150mm. This phantom was imaged on a CT scanner and a novel split-bore 1.0 T MRI magnet. The CT images provide distortion-free dataset. These data were used to test all modules of the open-source software. All markers were successfully extracted from all images. The distorted MRI markers were mapped to undistorted CT data using an iterative search approach. Spherical harmonics reconstructed the fitted gradient data to 1.0±0.6% of the input data. High resolution data were reconstructed via spherical harmonics and used to generate an interactive report. Finally, distortion correction on an independent data set reduced distortion inside the DSV from 5.5±3.1 to 1.6±0.8mm. Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI have been developed. The utility of these tools has been demonstrated via their application on a novel 1.0 T split bore magnet.

Directive transportation in smart cities with line connectivity at distinctive points using mode control algorithm

This article examines the operational functionality of intelligent transport systems to enhance smart cities by reducing traffic congestion. Given the increasing populations of smart cities, there is a growing demand for public transit systems to address the issue of traffic congestion. Therefore, the suggested system is developed using a few parametric design models, which combine point-to-point protocol and mode control optimization. The multi-objective parametric design for a smart transportation system is conducted using min–max functions to minimize the waiting time period for end users. Furthermore, customers are given the option to utilize a line following mechanism that offers suitable connectivity, along with independent identification and revitalize functions. The predicted model effectively eliminates the delay produced by transportation devices when positioning units are involved, ensuring that individual messages are delivered without any interruptions. In order to evaluate the results of the proposed system model, four different scenarios were examined. A comparison analysis revealed that the suggested method achieves a suitable directional flow for 96% of smart transport units. Additionally, it reduces delays and waiting periods by 2% and 6% respectively, while increasing energy consumption by 29%.

Research on the artistic form and image expression effect of public sculpture based on intelligent and parametric design

With the modernization of cities, public sculptures are constantly being designed and constructed. The artistic form and image expression effect of sculpture based on intelligent and parametric design needs to be designed and developed to guide and assist the construction of sculpture. This paper applies the NAS architecture search method to explore the field of image expression effect models. Through the end-to-end search of the experiment designed in this paper, the separable convolution lightweight design is used, and the new model AestheticNet is used to predict the image form effect score distribution. Secondly, this paper proposes optimization strategies combining image expression effect theory and convolutional neural network, including improvement of Loss function self-weighted Loss, two-dimensional Attention mechanism – introduction of CBAM, and adaptive pooling layer. Optimization of several aspects, such as adaptive input. Finally, the validation set is compared with other existing image-morphological effect model algorithms, which proves the effectiveness of the customized search scheme. It demonstrates the efficacy of the AestheticNet model compared to other algorithms by validating its prediction of public sculpture image form effect ratings. The artistic form using intelligent and parametric design methodologies may improve. Image expression of sculptures may be enhanced by applying the image form effect model, which should be pervasive. We can use it to intelligently and parametrically guide the design and manufacture of sculptures.

Parametric design and performance evaluation of TPMS porous vitrified bond diamond grinding wheel using digital light processing

Porous vitrified bond diamond grinding wheels are commonly used for grinding hard and brittle materials. However, uneven pore distribution and low porosity affect the grinding performance of the wheel significantly. In this study, three types of triply periodic minimal surface porous vitrified bond diamond grinding wheels—Gyroid, Diamond, and Lidinoid–were prepared through parametric designing and digital light processing 3D printing. The grinding wheel achieved a uniform distribution and an interconnected pore structure. The key to high-performance grinding wheel via stereolithography 3D printing lies in the preparation of the slurry with high solid loading, low viscosity and uniform stability. Hence, the effect of surface modifiers on the slurry, along with the effect of sintering temperature and the microscopic and mechanical properties, was investigated. By grinding the SiC ceramics, the material removal rate, grinding temperature, and surface roughness were compared to those achieved using a conventional solid-structure grinding wheel. The results show that the slurry with the highest solid content of 80 wt% (58 vol%) and viscosity of 4.21 Pa s (30 s−1) can be prepared using surface-modified particles. The diamond grinding wheel sintered at 680 °C exhibits the best comprehensive performance. A grinding wheel prepared using stereolithography 3D printing can achieve better surface roughness and lower the grinding temperature.

Influence of random geometrical imperfection on loading capacity of scaffold based on stochastic numerical model

The existing data indicate that two-thirds of engineering accidents occur during construction among which engineering accidents caused by scaffold collapse account for a large proportion. Due to the complex mechanical behavior of connection and random nature of scaffold system caused by random geometrical imperfection, the reliability of scaffold system is lower than other kinds of building structures. However, the method considering the random geometrical imperfection is limited. To facilitate the analysis of random geometrical imperfection, the original numerical algorithm is proposed based on ANSYS Parametric Design Language. Through proposed method, two types of geometrical imperfections, i.e., the nodal location error and initial curvature can be automatically considered. The randomness in initial curvature includes random magnitude and random direction. The established numerical model is as close to reality as possible and the process of establishing stochastic numerical model can be automatically finished. The only work that needs to be done is to enter the dimensions of the scaffold. Except the propose of numerical algorithm, the objective of this study is to reveal the influence of geometrical imperfection on random distribution of loading capacity of scaffold system under different load conditions. The influence of random geometrical imperfection on probabilistic distribution of loading capacity is systematically investigated. The results indicated that there may be several buckling modes exist and the buckling mode occurred in actual condition is closely related to the random distribution of geometrical imperfection. The load factor of internal post (point 3) is 8 %–12 % larger than that of corner post. The load factor of side post is 4.7 %–7.2 % larger than that of corner post. The ultimate bending capacity Mu has little influence on the loading capacity of scaffold system when the initial bending stiffness ko is small enough.

Multi-objective optimization of buildings in urban scale for early stage planning and parametric design

Passive design of buildings in early design stage is essential for energy efficiency and sustainability. In this study, a streamlined tool for parametric study and passive design of buildings in urban scale considering thermal loads and natural lighting performance is presented, which markedly enhances the efficiency of early-stage urban planning. The tool is comprised of three sub-models, including (1) degree-month based annual building thermal load prediction model, (2) simplified climate modification model that takes into account the effects of building layout on solar heat gain and urban heat island, (3) multi-objective optimization algorithm NSGA-II, which optimizes both energy-saving and natural lighting performance. Model validation results show that this tool has an average error of 11.44% and 15.82% in simulating building thermal load compared with Dragonfly and CitySim, and has an average error of 9.9% in predicting average daylight factor compared with Radiance. Multiple optimization scenarios and sensitivity analysis in 10 typical climatic cities were conducted. It is found that in cold and hot climatic cities, it is more beneficial to set energy target as the optimization objective, meanwhile, establishing natural lighting as a constraint, rather than solely minimizing thermal loads. In contrast, the inherently lower thermal loads of buildings in milder climatic cities help to achieve both energy-saving and natural lighting goals, and it is also found that the increased thermal loss due to a higher window-to-wall ratio can be offset by employing thicker wall and roof insulation or by improving building layouts.