A novel method of hydraulic valves design for additive manufacturing based on structural decomposition

Three-way spatial fluid channel (TSFC) is commonly used in spatial fluid channels of the high hydraulic integrated system. However, the mathematic model of TSFC pressure loss is not clear, and what TSFC structural parameters in a certain space can get the minimum pressure loss and weight is also vague. Therefore, TSFC pressure loss mathematic model and multi-objective optimization about pressure loss, axis path length, and mass are studied in this paper. First, the mathematic model of TSFC pressure loss is established based on the response surface methodology and pressure loss models of fluid dynamics. Then, the optimized mathematic model for the TSFC structural parameters is built by the multi-objective optimization design method to achieve low pressure loss, short axis path length, and lightweight. According to the simulation, the results of optimized structure model show that the mass has been reduced 5.68%, and the pressure loss has been reduced 70.75% compared with the original model. Besides, the optimized TSFC structure model is manufactured by additive manufacturing, and the experiment is carried out to measure TSFC pressure loss. It shows that the error of pressure loss between the mathematic model and the experiment is only 1.6%, which verifies the accuracy of mathematic model of the pressure loss. This research lays a foundation for the design and optimization of the spatial flow channel in highly integrated hydraulic systems.

Additive manufacturing (AM) and generative design tools are gaining popularity in reverse engineering and design optimization. Many industries, including aerospace and automotive, seek to reduce the mass of critical components while maintaining desired strength. The benefits of more efficient structural components include manufacturing cost savings across industries, increased fuel economy in transportation, and greater payload capacity in aerospace applications. This study utilized techniques such as 3D scanning, Fusion-based generative design simulations, and 3D printing to create a more efficient and equally strong component using advanced computer and manufacturing technologies. This study focused on an engine mount bracket for a Honda comfortable runabout vehicle (CRV), part number 11910-PPA-000, selected for generative design simulations and 3D printing as its dimensions were optimal for a commercially available desktop 3D printer and defined features ideal for 3D scanning and material testing. Once scanned, the stereolithography (STL) file was processed using Autodesk ReCap Photo to convert the triangular STL facets to quadrilateral facets before conversion to a meshed object in Fusion for further processing in the Design and Generative Design workspaces. The bolt and tapped holes were then isolated from the body of the mount bracket using the Fusion body splitting tool before post-processing to remove scanning defects from the inside face of the fixture points. The mounting bracket was then processed in the Fusion Generative Design workspace using acrylonitrile-butadiene-styrene (ABS) as the assigned material. The entire part was designated as the starting shape, with each bolt hole designated as preserved geometry, and established obstacle geometry to set the boundaries for the generative design. After assigning the part geometry, structural constraints and loads were applied to be consistent with the expected fixture points during testing, and the manufacturing type was designated for additive manufacturing. A model was then selected from 10 different generative design studies based on the mass saved and maximum Von Mises stresses. The chosen outcome had a mass reduction of 34%, from an original 131 grams to 86 grams when designed from ABS plastic. The maximum von Mises stress for the generative design was shown to be 9.8 MPa with a minimum factor of safety of 2. Three parts were printed out of ABS using 0°, 90°, and 45°/−45° raster orientations from the generative design. In addition, the legacy mount bracket was printed out of ABS using a 45°/−45° raster orientation from the generative design. The legacy part was tested on an Instron universal testing system as a benchmark for future testing of the generative design parts. The comparative study of a 3D scanned legacy part with generative design models demonstrated the feasibility of reverse engineering parts. This study also enabled advanced simulation tools to reduce the processing chain compared to traditional manufacturing and increase efficiency for critical parts across multiple industries.

Out-of-plane crashworthiness of bio-inspired hierarchical diamond honeycombs with variable cell wall thickness

Experiments are conducted to determine how the calculation of the parameters of cold pipe rolling, taking primary account of the metal propagation, affects the variation in pipe wall thickness.

Additive manufacturing (AM) is a “game-changing” digital fabrication technology that can fundamentally alter the way products are designed and manufactured. In nuclear engineering, the application of additive manufacturing can enable advanced reactor designs with better performance, lower cost, and quicker deployment. To exploit the maximum potential of additive manufacturing, design for additive manufacturing (DfAM) is needed, DfAM can leverage the complexity freedom offered by additive manufacturing technology to break traditional design constraints and achieve enhanced performance. Generative design, one of the key technologies in DfAM, is an iterative exploration method using AI-driven algorithms to generate a series of design solutions that meet specified constraints. In this work, a generative design platform for micro-reactors is developed based on DASSULT SIMULIA Isight. To simulate and analyze the multi-physics performance of the reactor design, various multi-physics simulation codes are integrated on this generative design platform, including RMC for neutron physics analysis, ANSYS Fluent for computational fluid dynamics analysis, and ANSYS Mechanical for structural mechanics analysis. A multi-objective optimization method is used to explore geometric parameters and fuel configurations to achieve better neutronics, thermal-fluidics, and structural mechanics performance. The generative design solution is a 4 MW helium-cooled nuclear reactor which includes 3D-printed silicon carbide (SiC) matrix embedded with tri-structural isotropic (TRISO) particle fuel. Helium at 3 MPa is chosen as the coolant, and the cross-shaped coolant channels are distributed within the matrix to remove the heat generated by fission. According to the multiphysics analysis, the reactor has a initial keff of 1.0571, power peaking factor FQ of 1.50, and operating lifetime of 1200 EFPD (Effective Full Power Days), with a maximum temperature of 1331 K and a peak thermal stress of 141.3 MPa. The generative design method and platform provide a systematic and efficient approach for the design of additively manufactured micro-reactors, and the generative design solution demonstrates the feasibility and effectiveness of the proposed method.

<div class="htmlview paragraph">Commercial Computational Fluid Dynamics (CFD) code ANSYS/Flotran has been used to simulate hydraulic oil flow inside valves. The fluid flow inside valve is treated as turbulent and adiabatic or iso-thermal. The CFD simulations presented in this paper have been carried out for the purpose of predicting hydraulic oil flow pressure drop inside hydraulic valves under certain operating conditions with the aim to minimize the pressure losses. The complete simulation procedure will be presented from parametric geometry creation with a 3-D solid CAD through final post-processing of results. Simulation results of different multiple-spool monoblock hydraulic valves are included. CFD simulation results are compared to experimental results. Some CFD model mesh sensitivity analysis result is also presented.</div>

Free vibration analysis of complete paraboloidal shells of revolution with variable thickness and solid paraboloids from a three-dimensional theory

Membrane stress equations for a catenary dome with a variation in wall thickness

Metal spinning is one of a number of flexible sheet forming processes which is a cost effective option for the production of parts with a very high strength to weight ratio. Although the wall thickness of the formed part in conventional spinning is generally considered to be nearly constant, a non uniform distribution of wall thickness is in fact observed. In this study, the wall thickness variation of a formed part made of Cr-Mn austenitic stainless steel was analysed. The thickness variation was measured using an optical 3D scanning method and the influence of mandrel speed, feed ratio and tool path profile (convex, concave and linear) on wall thickness variation was studied. A three-level full factorial design of the experiment and ANOVA (Analysis of Variance) were used. The results show that the maximal variation in wall thickness is observed in approximately half of the part wall height (thinning) and on the open end of the part (thickening). Feed ratio and roller path profile are statistically significant factors governing wall thickness variation. There was no obvious effect from the variation in mandrel speed on the thickness distribution.

Experimental investigation of wall thickness and hole shape variation effects on full-coverage film cooling performance for a gas turbine vane

The unique design freedom offered by additive manufacturing (AM) technologies enables engineers to develop more innovative products with relatively lower costs within a shorter period of processing time in comparison with conventional manufacturing methods. On the other hand, the unique capabilities of AM have created a platform for researchers to combine several engineering methods with the new manufacturing technique to grow industrial applications as well as resolve the existing issues with AM processes. Understanding the research values that AM offers academic environments, this paper performs a systematic survey on AM-related research topics in the fields of mechanical engineering and materials science that have attracted much attention from research teams over the last few years. These topics, namely process modelling in AM, innovative research in AM, generative design by AM, material characterisation in AM processes, and finally, design for additive manufacturing (DfAM), are notably investigated through this study.

Variable gauge rolling (VGR) is a new technology for producing the materials which have the advantage of lightweight due to optimized thickness according to load distribution. The new progresses in the theoretical research and application of VGR are reviewed in this paper. Two basic equations, VGR-f and VGR-s, were deduced. The former is a new differential equation of force equilibrium, and the latter is a new form of formula for the law of mass conservation. Both of them provide a new base for the development of VGR analysis. As the examples of VGR’s application, tailor rolled blank (TRB) and longitudinal profile (LP) plate are introduced. Now TRBs are only produced in Germany and China, and have been used in the automotive manufacturing to play an important role in lightweight design. LP plates have been used in shipbuilding and bridge construction, and promised a bright prospect in reducing construction weight. In addition, new technologies and applications of VGR emerge constantly. Tailor welded strips and tailor rolled strips with variable thickness across the width can be used for progressive die and roll forming. The 3D profiled blank can be obtained by two-step rolling process. Tailor tubes with the variable wall thickness are an efficient way to reduce the weight. The blank with tailored thickness and mechanical property is also under development. Above products based on the tailored ideas provide a new materials-warehouse for the designers to select so as to meet the needs of weight reducing and material saving.

3D modeling technology, as well as additive manufacturing, has changed the processes of industries, allowing the creation and production of complex and unique prototypes with increased speed and versatility. However, the effectiveness of additive manufacturing is primarily based on the capabilities of the 3D design software used to create these objects. The state of 3D modeling software in additive manufacturing currently has both advantages and disadvantages: existing tools have basic design support functionality, but they often lack the ability to optimize designs for increased efficiency and productivity. This inspires research into how to incorporate artificial intelligence into 3D modeling software to solve these problems and improve the additive manufacturing process. Using artificial intelligence techniques such as machine learning and generative design, the accuracy and efficiency of 3D models can be significantly improved, leading to improved manufacturing efficiency. However, integrating artificial intelligence into existing 3D modeling software faces challenges related to compatibility, data management, and user acceptance. With a discussion of this topic and a show demonstrating the successful implementation of AI in 3D modeling for additive manufacturing, the impact of AI-enhanced software on the industry is clear. This article aims to explore the current state of 3D modeling software in relation to additive manufacturing, discuss how AI can be used for optimization, and assess the implications and possible future steps of integrating AI into 3D modeling to improve efficiency in relation to additive manufacturing. production.

Determination of collapse loads in pipe bends with ovality and variable wall thickness under internal pressure and in-plane opening moment

Hollow shafts are widely used due to their high weight saving potential and only slight reduction of their bending and torsional stiffness compared to solid shafts. Additional weight savings can be achieved by a specific material allocation within the hollow shaft, which can be achieved by varying their wall thickness. The production of such hollow shafts by conventional forming processes and multiple forming stages appears quite costly today. Alternatively, incremental forming processes could be used, but those are very time-consuming. In order to overcome these disadvantages, this paper proposes a special cold forging process characterized by a locally adjustable forming zone, which allows the production of hollow shafts with variable wall thickness within one single press stroke. In previous numerical investigations, the potential of this cold forging process for the production of customized hollow shafts with predefined wall thickness locations or internal splines has already been demonstrated. However, experimental validation has not yet been carried out. In this paper, the first experimental results on hollow shafts produced with wall thickness changes along their longitudinal direction are presented. The experimental setup and the results of the tests carried out so far are described. Furthermore, the experimental results are compared with the numerical calculations of this new forming process.