水田动力底盘逆向建模与质心验证——基于Geomagic Design X

针对目前农业机械仿真和优化模型精度不高的问题,提出了一种构建精确模型的逆向建模方法。应用光学扫描仪采集点云数据,基于Geomagic Design X处理点云数据并重构零部件模型,在SolidWorks中完成水田动力底盘的装配。以VP6D-CQ型水田动力底盘为例,将测得的实际质心位置与所建的模型质心位置进行比较,并对提出的逆向建模方法进行了试验验证以及误差分析。结果表明:总质量、x坐标、y坐标、z坐标的误差值分别为4.55%、3.62%、2.23%、4.81%,误差值均在5%内。此方法可构建准确的三维模型,为后续仿真优化数据精确性奠定了基础,与传统的研发相比较,可缩短农业机械研发周期、降低设计成本。

Towards data-efficient mechanical design of bicontinuous composites usinggenerative AI

The distribution of material phases is crucial to determine the composite’s mechanical property.While the full structure-mechanics relationship of highly ordered material distributions can be studied with finite number of cases,this relationship is difficult to be revealed for complex irregular distributions,preventing design of such material structures to meet certain mechanical requirements.The noticeable developments of artificial intelligence(AI)algorithms in material design enables to detect the hidden structure-mechanics correlations which is essential for designing composite of complex structures.It is intriguing how these tools can assist composite design.Here,we focus on the rapid generation of bicontinuous composite structures together with the stress distribution in loading.We find that generative AI,enabled through fine-tuned Low Rank Adaptation models,can be trained with a few inputs to generate both synthetic composite structures and the corresponding von Mises stress distribution.The results show that this technique is convenient in generating massive composites designs with useful mechanical information that dictate stiffness,fracture and robustness of the material with one model,and such has to be done by several different experimental or simulation tests.This research offers valuable insights for the improvement of composite design with the goal of expanding the design space and automatic screening of composite designs for improved mechanical functions.

Multi-Scale Design and Optimization of Composite Material Structure for Heavy-Duty Truck Protection Device

In this paper,to present a lightweight-developed front underrun protection device(FUPD)for heavy-duty trucks,plain weave carbon fiber reinforced plastic(CFRP)is used instead of the original high-strength steel.First,the mechanical and structural properties of plain carbon fiber composite anti-collision beams are comparatively analyzed from a multi-scale perspective.For studying the design capability of carbon fiber composite materials,we investigate the effects of TC-33 carbon fiber diameter(D),fiber yarn width(W)and height(H),and fiber yarn density(N)on the front underrun protective beam of carbon fiber compositematerials.Based on the investigation,a material-structure matching strategy suitable for the front underrun protective beam of heavy-duty trucks is proposed.Next,the composite material structure is optimized by applying size optimization and stack sequence optimization methods to obtain the higher performance carbon fiber composite front underrun protection beam of commercial vehicles.The results show that the fiber yarn height(H)has the greatest influence on the protective beam,and theH1matching scheme for the front underrun protective beamwith a carbon fiber composite structure exhibits superior performance.The proposed method achieves a weight reduction of 55.21% while still meeting regulatory requirements,which demonstrates its remarkable weight reduction effect.

Research on the design method for uniform wear of shield cutters in sand-pebble strata

During shield tunneling in highly abrasive formations such as sand–pebble strata,nonuniform wear of shield cutters is inevitable due to the different cutting distances.Frequent downtimes and cutter replacements have become major obstacles to long-distance shield driving in sand–pebble strata.Based on the cutter wear characteristics in sand–pebble strata in Beijing,a design methodology for the cutterhead and cutters was established in this study to achieve uniform wear of all cutters by the principle of frictional wear.The applicability of the design method was verified through three-dimensional simulations using the engineering discrete element method.The results show that uniform wear of all cutters on the cutterhead could be achieved by installing different numbers of cutters on each trajectory radius and designing a curved spoke with a certain arch height according to the shield diameter.Under the uniform wear scheme,the cutter wear coefficient is greatly reduced,and the largest shield driving distance is increased by approximately 47%over the engineering scheme.The research results indicate that the problem of nonuniform cutter wear in shield excavation could be overcome,thereby providing guiding significance for theoretical innovation and construction of long-distance shield excavation in highly abrasive strata.

Application of Digital Technology in Road and Bridge Design

With the development and progress of science and technology,road and bridge design has experienced rapid development,from the initial manual drawing design to the popularity of Computer-Aided Design(CAD),and then to today’s digital software design era.Early designers relied on hand-drawn paper design forms which was time-consuming and error-prone.Digital support for road and bridge design not only saves the design time but the design quality has also achieved a qualitative leap.This paper engages in the application of digital technology in road and bridge design,to provide technical reference for China’s road and bridge engineering design units,to promote the popularity of Civil3D and other advanced design software in the field of engineering design and development,ultimately contributing to the sustainable development of China’s road and bridge engineering.

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.

基于Geomagic Design X组合体的逆向建模

Geomagic Design X软件常用于STL面片的逆向建模,选取一典型组合体对其逆向建模,通过对组合体对齐、分割领域、创建面片草图、创建实体和扫掠完成实体建模,最后验证体偏差检测是否符合要求,为后续相似零件的逆向建模提供参考。

DADOS:A Cloud-based Data-driven Design Optimization System

This paper presents a cloud-based data-driven design optimization system,named DADOS,to help engineers and researchers improve a design or product easily and efficiently.DADOS has nearly 30 key algorithms,including the design of experiments,surrogate models,model validation and selection,prediction,optimization,and sensitivity analysis.Moreover,it also includes an exclusive ensemble surrogate modeling technique,the extended hybrid adaptive function,which can make use of the advantages of each surrogate and eliminate the effort of selecting the appropriate individual surrogate.To improve ease of use,DADOS provides a user-friendly graphical user interface and employed flow-based programming so that users can conduct design optimization just by dragging,dropping,and connecting algorithm blocks into a workflow instead of writing massive code.In addition,DADOS allows users to visualize the results to gain more insights into the design problems,allows multi-person collaborating on a project at the same time,and supports multi-disciplinary optimization.This paper also details the architecture and the user interface of DADOS.Two examples were employed to demonstrate how to use DADOS to conduct data-driven design optimization.Since DADOS is a cloud-based system,anyone can access DADOS at www.dados.com.cn using their web browser without the need for installation or powerful hardware.

A Custom Manipulator for Dental Implantation Through Model-Based Design

This paper presents a Model-Based Design(MBD)approach for the design and control of a customized manipulator intended for drilling and position-ing of dental implants accurately with minimal human intervention.While performing an intra-oral surgery for a prolonged duration within a limited oral cavity,the tremor of dentist's hand is inevitable.As a result,wielding the drilling tool and inserting the dental implants safely in accurate position and orientation is highly challenging even for experienced dentists.Therefore,we introduce a customized manipulator that is designed ergonomically by taking in to account the dental chair specifications and anthropomorphic data such that it can be readily mounted onto the existing dental chair.The manipulator can be used to drill holes for dental inserts and position them with improved accuracy and safety.Further-more,a thorough multi-body motion analysis of the manipulator was carried out by creating a virtual prototype of the manipulator and simulating its controlled movements in various scenarios.The overall design was prepared and validated in simulation using Solid works,MATLAB and Simulink through Model Based Design(MBD)approach.The motion simulation results indicate that the manipulator could be built as a prototype readily.

High-strength Ti-Al-V-Zr cast alloys designed using α and β cluster formulas

Ti-Al-V-Zr quaternary titanium alloys were designed followingα-{[Al-Ti12](AlTi2)}17-n+β-{[Al-Ti12Zr2](V3)}n,where n=1-7(the number ofβunits),on the basis of the dual-cluster formula of popular Ti-6Al-4V alloy.Such an alloying strategy aims at strengthening the alloy via Zr and V co-alloying in theβ-Ti unit,based on the originalβformula[Al-Ti14](V2Ti)of Ti-6Al-4V alloy.The microstructures of the as-cast alloys by copper-mold suction-casting change from pureα(n=1)toα+α’martensite(n=7).When n is 6,Ti-5.6Al-6.8V-8.1Zr alloy reaches the highest ultimate tensile strength of 1,293 MPa and yield strength of 1,097 MPa,at the expense of a low elongation of 2%,mainly due to the presence of a large amount of acicularα’martensite.Its specific strength far exceeds that of Ti-6Al-4V alloy by 35%.

A machine learning approach for accelerated design of magnesium alloys.Part B: Regression and property prediction

Machine learning(ML) models provide great opportunities to accelerate novel material development, offering a virtual alternative to laborious and resource-intensive empirical methods. In this work, the second of a two-part study, an ML approach is presented that offers accelerated digital design of Mg alloys. A systematic evaluation of four ML regression algorithms was explored to rationalise the complex relationships in Mg-alloy data and to capture the composition-processing-property patterns. Cross-validation and hold-out set validation techniques were utilised for unbiased estimation of model performance. Using atomic and thermodynamic properties of the alloys, feature augmentation was examined to define the most descriptive representation spaces for the alloy data. Additionally, a graphical user interface(GUI) webtool was developed to facilitate the use of the proposed models in predicting the mechanical properties of new Mg alloys. The results demonstrate that random forest regression model and neural network are robust models for predicting the ultimate tensile strength and ductility of Mg alloys, with accuracies of ~80% and 70% respectively. The developed models in this work are a step towards high-throughput screening of novel candidates for target mechanical properties and provide ML-guided alloy design.

A novel Ti-5.55Al-6.70Zr-1.50V-0.70Mo-3.41Nb-0.21Si alloy designed using cluster-plus-glue-atom model for laser additive manufacturing

A novel Ti-5.55Al-6.70Zr-1.50V-0.70Mo-3.41Nb-0.21Si alloy was designed using the cluster formula approach(cluster-plus-glue-atom model)and prepared by laser melting deposition(LMD).Its composition formula 12[Al-Ti_(12)](AlTi_(2))+5[Al_(0.8)Si_(0.2)-Ti_(12)Zr_(2)](V_(0.8)Mo_(0.2)Nb_(1)Ti)features an enhancedβ-Ti via co-alloying of Zr,V,Mo,Nb and Si.The experimental results show that the cluster formula ofαandβphases in the novel alloy are respectivelyα-[Al-Ti_(11.5)Zr_(0.5)](Al_(1)Ti_(2))andβ-[Al_(0.8)Si_(0.2)-Ti_(13.2)Zr_(0.8)](V_(1)Mo_(0.4)Nb_(1.6)),both containing Zr elements.The fitted composition via the α andβphase cluster formulas has little difference with the actual alloy composition,suggesting that the validity of cluster-plus-glue-atom model in the alloy composition design.After hot isostatic pressing(HIP),both the Ti-6Al-4V and the novel alloy by LMD are characterized by prior-βcolumnar grains,while the typical<100>texture disappears.Compared with Ti-6Al-4V,Ti-5.55Al-6.70Zr-1.50V-0.70Mo-3.41Nb-0.21Si alloy exhibits a combination of higher strength(1,056 MPa)and higher ductility(14%)at room temperature and higher strength(580 MPa)at 550℃ after HIP,and can potentially serves as LMD materials.

Uncertainty analysis for the calculation of marine environmental design parameters in the South China Sea

The calculation results of marine environmental design parameters obtained from different data sampling methods,model distributions,and parameter estimation methods often vary greatly.To better analyze the uncertainties in the calculation of marine environmental design parameters,a general model uncertainty assessment method is necessary.We proposed a new multivariate model uncertainty assessment method for the calculation of marine environmental design parameters.The method divides the overall model uncertainty into two categories:aleatory uncertainty and epistemic uncertainty.The aleatory uncertainty of the model is obtained by analyzing the influence of the number and the dispersion degree of samples on the information entropy of the model.The epistemic uncertainty of the model is calculated using the information entropy of the model itself and the prediction error.The advantages of this method are that it does not require many-year-observation data for the marine environmental elements,and the method can be used to analyze any specific factors that cause model uncertainty.Results show that by applying the method to the South China Sea,the aleatory uncertainty of the model increases with the number of samples and then stabilizes.A positive correlation was revealed between the dispersion of the samples and the aleatory uncertainty of the model.Both the distribution of the model and the parameter estimation results of the model have significant effects on the epistemic uncertainty of the model.When the goodness-of-fit of the model is relatively close,the best model can be selected according to the criterion of the lowest overall uncertainty of the models,which can both ensure a better model fit and avoid too much uncertainty in the model calculation results.The presented multivariate model uncertainty assessment method provides a criterion to measure the advantages and disadvantages of the marine environmental design parameter calculation model from the aspect of uncertainty,which is of great significance to analyze the uncertainties in the calculation of marine environmental design parameters and improve the accuracy of the calculation results.

Optimization of integrated geological-engineering design of volume fracturing with fan-shaped well pattern

According to the variable toe-to-heel well spacing, combined with the dislocation theory, discrete lattice method, and finite-element-method(FEM) based fluid-solid coupling, an integrated geological-engineering method of volume fracturing for fan-shaped well pattern is proposed considering the geomechanical modeling, induced stress calculation, hydraulic fracturing simulation, and post-frac productivity evaluation. Besides, we propose the differential fracturing design for the conventional productivity-area and the potential production area for fan-shaped horizontal wells. After the fracturing of the conventional production area for H1 fan-shaped well platform, the research shows that the maximum reduction of the horizontal principal stress difference in the potential productivity-area is 0.2 MPa, which cannot cause the stress reversal, but this reduction is still conducive to the lateral propagation of hydraulic fractures. According to the optimized fracturing design, in zone-Ⅰ of the potential production area, only Well 2 is fractured, with a cluster spacing of 30 m and an injection rate of 12 m^(3)/min per stage;in zone-Ⅱ, Well 2 is fractured before Well 3, with a cluster spacing of 30 m and an injection rate of 12 m^(3)/min per stage. The swept area of the pore pressure drop in the potential production area is small, showing that the reservoir is not well developed. The hydraulic fracturing in the toe area can be improved by, for example, properly densifying the fractures and adjusting the fracture distribution, in order to enhance the swept volume and increase the reservoir utilization.

Scavenging Microwave Wireless Power:A Unified Model,Rectenna Design Automation,and Cutting-Edge Techniques

While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas,few studies focus on the fundamental modeling and related design automation of receiver systems.This article reviews the development of MWPT and MWEH receivers,with a focus on rectenna design automation.A novel rectifier model capable of accurately modeling the rectification process under both high and low input power is presented.The model reveals the theoretical boundary of radio frequency-to-direct current(dc)power conversion efficiency and,most importantly,enables an automated system design.The automated rectenna design flow is sequential,with the minimal engagement of iterative optimization.It covers the design automation of every module(i.e.,rectifiers,matching circuits,antennae,and dc–dc converters).Scaling-up of the technique to large rectenna arrays is also possible,where the challenges in array partitioning and power combining are briefly discussed.In addition,several cutting-edge rectenna techniques for MWPT and MWEH are reviewed,including the dynamic range extension technique,the harmonics-based retro-directive technique,and the simultaneous wireless information and power transfer technique,which can be good complements to the presented automated design methodology.

Adaptive enhancement design of triply periodic minimal surface lattice structure based on non-uniform stress distribution

The Schwarz primitive triply periodic minimal surface(P-type TPMS)lattice structures are widely used.However,these lattice structures have weak load-bearing capacity compared with other cellular structures.In this paper,an adaptive enhancement design method based on the non-uniform stress distribution in structures with uniform thickness is proposed to design the P-type TPMS lattice structures with higher mechanical properties.Two types of structures are designed by adjusting the adaptive thickness distribution in the TPMS.One keeps the same relative density,and the other keeps the same of non-enhanced region thickness.Compared with the uniform lattice structure,the elastic modulus for the structure with the same relative density increases by more than 17%,and the yield strength increases by more than 10.2%.Three kinds of TPMS lattice structures are fabricated by laser powder bed fusion(L-PBF)with 316L stainless steel to verify the proposed enhanced design.The manufacture-induced geometric deviation between the as-design and as-printed models is measured by micro X-ray computed tomography(μ-CT)scans.The quasi-static compression experimental results of P-type TPMS lattice structures show that the reinforced structures have stronger elastic moduli,ultimate strengths,and energy absorption capabilities than the homogeneous P-TPMS lattice structure.

Model Design and Development of a Telescopic Palm Fruit Harvester

This research paper presents a comprehensive conceptual design approach for the development of a telescopic machine system, which is portable and will provide a safe method of harvesting palm fruits. For this machine system development, the material for each component of the machine system was first selected, the boom length, maximum boom angle, force and stroke length of each hydraulic cylinder, the hydraulic pump pressure, base weight, permissible weight of the cutting system and power required were then calculated in the design analysis. Furthermore, from the calculated parameters, the model of the system was created using SolidWorks engineering software, the model was developed and tested. The result shows that the cutting time of the system for one bunch of palm fruit was longer when compared to conventional systems. It was concluded that though the machine is maintenance friendly and portable, further improvements in its design are necessary so as to develop a system that will give desirable economic output at a shorter time.

The Study of Optimizing Reservoir Model Using Experimental Design in Stochastic Models

In response to the main problems in commonly used model selection methods,a method was proposed to apply the concept of experimental design to the optimization of uncertain reservoir models.Firstly,based on the actual situation of the oil field,the uncertain variables were determined that affect the geological reserves of the model and their possible range of variation,and experimental design was used to determine the modeling plan.Then,multiple geological models were established and reserves were calculated,and multiple regression was performed between uncertain variables and the corresponding geological reserves of the model.Finally,Monte Carlo simulation technology was applied to determine the parameters of the P10,P50,and P90 models for probabilistic reserves,and P10,P50,and P90 models were established.This method is not only more objective and time-saving in the application process,but also can determine the main geological variables that affect geological reserves,providing a new idea for evaluating the uncertainty of geological reserves.

Design and Characterization of an Aerosol Test Chamber for Emergency Response Patient Contamination Control Simulation and Research

Contaminated or infected patients present a risk of cross-contamination for emergency responders, attending medical personnel and medical facilities as they enter a treatment facility. The controlled conditions of an aerosol test chamber are required to examine factors of contamination, decontamination, and cross-contamination. This study presents the design, construction, and a method for characterizing an aerosol test chamber for a full-sized manikin on a standard North Atlantic Treaty Organization litter. The methodology combined air velocity measurements, aerosol particle counts and size distributions, and computational fluid dynamics modeling to describe the chamber’s performance in three dimensions. This detailed characterization facilitates future experimental design by predicting chamber performance for a variety of patient-focused research.

Design of N-11-Azaartemisinins Potentially Active against Plasmodium falciparum by Combined Molecular Electrostatic Potential, Ligand-Receptor Interaction and Models Built with Supervised Machine Learning Methods

N-11-azaartemisinins potentially active against Plasmodium falciparum are designed by combining molecular electrostatic potential (MEP), ligand-receptor interaction, and models built with supervised machine learning methods (PCA, HCA, KNN, SIMCA, and SDA). The optimization of molecular structures was performed using the B3LYP/6-31G* approach. MEP maps and ligand-receptor interactions were used to investigate key structural features required for biological activities and likely interactions between N-11-azaartemisinins and heme, respectively. The supervised machine learning methods allowed the separation of the investigated compounds into two classes: cha and cla, with the properties εLUMO+1 (one level above lowest unoccupied molecular orbital energy), d(C6-C5) (distance between C6 and C5 atoms in ligands), and TSA (total surface area) responsible for the classification. The insights extracted from the investigation developed and the chemical intuition enabled the design of sixteen new N-11-azaartemisinins (prediction set), moreover, models built with supervised machine learning methods were applied to this prediction set. The result of this application showed twelve new promising N-11-azaartemisinins for synthesis and biological evaluation.