3D-printed Steel Research Articles

Magnetic properties and structure of carbon steel samples manufactured by selective laser melting and subjected to fatigue tests

This study investigates the magnetic properties and structure of 09G2S steel samples fabricated using casting and selective laser melting methods. Fatigue bending tests with cantilever fixation were performed to analyze these properties. It was found that the fatigue curve for 3D-printed steel lies below that of cast steel with a similar chemical composition. Both the coercive force and residual magnetic induction are lower near the fracture site. The greater the number of cycles to failure, the smaller the difference in coercive force and residual magnetic induction in different parts of the sample. The nature of fatigue failure differs between cast and 3D-printed steel. The cast 09G2S steel sample exhibits a straight and homogeneous fatigue fracture without visible crack initiation sites. In contrast, the 3D-printed steel samples show heterogeneous fractures with localized zones of failure and tear-off ridges.

Enhancing thermal performance of heat exchanger by using different 4-lobed swirl tube arrangements

This study numerically and experimentally investigated the thermal performance of a 4-lobed swirl tube. A double-pipe heat exchanger was built using 3D-printed steel tubes with PD ratios ranging from 4, 6 to 8. In addition, a 3D-printed circular pipe was also manufactured to investigate the influence of the 3D-printing method. In the experimental results, the PD4 decaying swirl tube had the highest performance for all PD ratios. The effects of different pitch-to-diameter (PD) ratios and tube arrangements on the swirl pipe were also investigated during simulations. The results reveal that the tube with a smaller PD ratio and crossover arrangement has a larger thermal enhancement and pressure drop. However, in comparison, the decaying arrangement has a relatively higher overall performance since it has a lower pressure drop. The PD6 decaying tube arrangement is the highest, especially at higher Reynolds numbers. Moreover, by showing the streamline within the swirl tube, small-scale vortices are found within the swirl tube, especially in the crossover arrangement. These vortices are formed due to the swirl motion and can enhance mixing and the heat transfer rate. Based on these simulation results, a regular-spaced swirl tube arrangement is proposed and its thermal performance is evaluated. In the experimental results, the PD4 decaying swirl tube gave the highest overall performance from 1.12 to 1.09 across all configurations. In the numerical results, the regularly-spaced swirl tube can further improve the overall performance with moderate pressure drop. Type 2 PD4 has the highest performance value at 1.06.

Effect of steel fibre with different orientations on mechanical properties of 3D-printed steel-fibre reinforced concrete: Mesoscale finite element analysis

It is widely recognized that steel fibres exhibit directional distribution during the preparation of 3D-printed steel fibre reinforced concrete (SFRC). The degree of fibre orientation varies due to several factors, such as nozzle size and layer height. This variation in fibre orientation range may result in different mechanical performance exhibited by 3D-printed SFRC at hardened state. To explore the relationship between steel fibre orientation and the mechanical properties of 3D-printed SFRC at hardened state, this study firstly establishes three-dimensional mesoscale finite element models based on the distribution of fibres in 3D-printed SFRC. The steel fibre and matrix work together through a mechanism for fluid-structure interaction between models. Then, compares the simulation results with experimental data to verify the accuracy of the models. After that, different steel fibre distribution orientations were set, and parametric analysis was conducted for the compressive and tensile loading conditions to explore the effects of fibre orientation on the damage mode and strength of 3D-printed SFRC. The results indicate that 3D-printed SFRC exhibits different damage modes with varying steel fibre orientation ranges. Additionally, the strength of 3D-printed SFRC varies in steel fibre orientation range and exhibits anisotropic characteristics. This study provides a theoretical basis for improving and controlling the performance of 3D-printed SFRC in future engineering applications.

Comparing the Performance of Rolled Steel and 3D-Printed 316L Stainless Steel.

Three-dimensional printing is a non-conventional additive manufacturing process. It is different from the conventional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that conventional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, by affecting the structural strength and the parts' assembly capability. Therefore, this study compares the qualities of the warpage, weight, and surface roughness after milling and grinding processes for the same material (316L stainless steel) between rolled steel and 3D-printed steel. The experimental results show that 3D-printed parts are approximately 13% to 14% lighter than rolled steel. The surface roughness performance of 3D-printed steel is better than that of rolled steel for the same material after milling or grinding processing. The hardness of the 3D-printed steel is better than that of the rolled steel. This research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

ML-Enabled Piezoelectric-Driven Internal Defect Assessment in Metal Structures

With the growth of 3D printing in the production space, it is inevitable that quality assurance will be needed to keep final products within the constraints of requirements. Also, the variety of materials that can be used with 3D printing has increased over the years. Testing also must consider the process of manufacturing. This paper focuses its efforts on the finished product and not the process of manufacturing. Ultrasonic testing is a type of nondestructive testing. The experiments performed in this study aim to explore the usefulness of ultrasonic testing in materials that are 3D printed. The two materials used in this study are steel alloy metals and aluminum blocks of the same dimensions—120 mm × 40 mm × 15 mm. These materials represent common choices in additive manufacturing processes. The chosen alloys, such as Aluminum (6063T6) and grade-304 stainless steel, possess distinct properties crucial for validating the proposed testing method. Metal 3D-printed materials play a pivotal role in diverse industries, since ensuring their structural integrity is imperative for reliability and safety. Testing is crucial to identify and mitigate defects that could compromise the functionality and longevity of the final products, especially in applications with demanding performance requirements. An ultrasonic transducer is used to scan for subsurface defects within the samples and an oscilloscope is used to analyze the signals. Furthermore, several Machine Learning (ML) techniques are used to estimate the severity of the defects. The application of Machine Learning methods in the manufacturing industry has proven advantageous in terms of detecting defects due to its practicality and wide application. Due to their distinct benefits in processing image information, convolutional neural networks (CNNs) are the preferred method when working with picture data. In order to perform binary and multi-class classification, support vector machines that employ the alternative kernel function are a viable option for processing sensor signals and picture data. The study reveals that ultrasonic tests are viable for metallic materials. The primary objective of this work is to evaluate and validate the application of ultrasonic testing for the inspection of 3D-printed steel alloy metals and aluminum blocks. The novelty lies in the integration of Machine Learning techniques to estimate defect severity, offering a comprehensive and non-invasive approach to quality assessment in 3D-printed materials. The proposed method can successfully detect the presence of internal defects in objects, as well as estimate the location and severity of the defects.

Performance-based, AI-ML-assisted Generative EA Design with Bio-inspired Topological Optimisations of a 50m, 3D-printed Steel Bridge

Performance-based, AI-ML-assisted Generative EA Design with Bio-inspired Topological Optimisations of a 50m, 3D-printed Steel Bridge

A data-centric approach to generative modelling for 3D-printed steel.

The emergence of additive manufacture (AM) for metallic material enables components of near arbitrary complexity to be produced. This has potential to disrupt traditional engineering approaches. However, metallic AM components exhibit greater levels of variation in their geometric and mechanical properties compared to standard components, which is not yet well understood. This uncertainty poses a fundamental barrier to potential users of the material, since extensive post-manufacture testing is currently required to ensure safety standards are met. Taking an interdisciplinary approach that combines probabilistic mechanics and uncertainty quantification, we demonstrate that intrinsic variation in AM steel can be well described by a generative statistical model that enables the quality of a design to be predicted before manufacture. Specifically, the geometric variation in the material can be described by an anisotropic spatial random field with oscillatory covariance structure, and the mechanical behaviour by a stochastic anisotropic elasto-plastic material model. The fitted generative model is validated on a held-out experimental dataset and our results underscore the need to combine both statistical and physics-based modelling in the characterization of new AM steel products.

The investigation of dynamic properties of 3D-printed steel parts

Additive technologies are promising for manufacturing parts of metal navigation devices with complex shapes. Finite element analysis is used during the designing of such items. The modeling accuracy is determined by the correctness of the specified physical properties of materials. The properties of materials used in 3D printing significantly differ from the ones used in the traditional manufacturing. Researchers focus on such characteristics as Young’s modulus, Poisson’s ratio, hardness and strength. Meanwhile, some applications require dynamic properties. The paper presents the investigation and comparison of damping properties of three steel parts produced by different methods. The first part is manufactured by 3D printing with melting in the transverse direction, and the second part is done by melting in the longitudinal direction, while the third one is traditionally manufactured. The parts are shaft shaped with constant cross-section and have the same geometric dimensions. The TIRA TV 5220 / LS-120 stand is used. A piezoelectric accelerometer is installed at the loose end of the part. The tests are carried out in the frequency range from 15 to 3500 Hz and with an acceleration of 19.6 m/s2 (2 g). The accelerometer output is used to calculate the damping coefficient. The results are verified by comparison with the finite element modeling results. The damping coefficients of transverse and longitudinal 3D-printed parts are 0.022 and 0.006, respectively. The damping coefficient of the traditional manufactured part is 0.023. The difference of 3D-printed parts damping coefficients can be explained by the denser fusion of powder granules when printing one layer than between layers. In this case, a crystal structure with greater rigidity in the printing plane is formed and it limits the dissipation of vibration energy due to internal friction. Finite element modeling shows mismatch between the experimental and calculated values of the printed parts natural frequencies. Considering that the values of natural frequencies are largely determined by Young’s modulus, a parametric optimization of its value is carried out. It was found that the value of Young’s modulus does not correspond to the values determined during tensile tests for similar samples. Thus, 3D-printed parts have different vibration and static stiffness. This is not typical for metals and should be taken into account in simulations. The research results can be used in the simulation model development of steel 3D-printed parts and in the design of digital twins for navigation devices. It allows one to estimate vibration resistance of promising products at the early stages of their design and to optimize the construction minimizing stress.

A hierarchical Bayesian approach for calibration of stochastic material models

AbstractThis article recasts the traditional challenge of calibrating a material constitutive model into a hierarchical probabilistic framework. We consider a Bayesian framework where material parameters are assigned distributions, which are then updated given experimental data. Importantly, in true engineering setting, we are not interested in inferring the parameters for a single experiment, but rather inferring the model parameters over the population of possible experimental samples. In doing so, we seek to also capture the inherent variability of the material from coupon-to-coupon, as well as uncertainties around the repeatability of the test. In this article, we address this problem using a hierarchical Bayesian model. However, a vanilla computational approach is prohibitively expensive. Our strategy marginalizes over each individual experiment, decreasing the dimension of our inference problem to only the hyperparameter—those parameter describing the population statistics of the material model only. Importantly, this marginalization step, requires us to derive an approximate likelihood, for which, we exploit an emulator (built offline prior to sampling) and Bayesian quadrature, allowing us to capture the uncertainty in this numerical approximation. Importantly, our approach renders hierarchical Bayesian calibration of material models computational feasible. The approach is tested in two different examples. The first is a compression test of simple spring model using synthetic data; the second, a more complex example using real experiment data to fit a stochastic elastoplastic model for 3D-printed steel.

Failure analysis of 3D-printed steel gears

The basic principle of additive manufacturing technology is that the model can be manufactured directly via computer-aided design system. This technology is quite different from traditional methods and allows production to avoid wasting material.This study features 420 steel gears produced using both additive and conventional manufacturing. The gears were subjected to identical test processes and compared to one another. The effects of rotational speed, torque, production technique, and post-production surface treatment were investigated. The researchers performed wear loss, efficiency analysis, oil analysis, damage analysis, optical, and scanning microscope surface analysis. It was revealed that the density and hardness of the gears produced by additive manufacturing (Direct Metal Laser Sintering – DMLS) were quite close to those produced by conventional methods (hobbing machine); however, the surface properties were different. Therefore, the types of damage that occur under the same operating conditions differ. As a result, it was found that gears produced by additive manufacturing wear more, but the weight loss (which is a measure of wear) from wear was mostly caused by non-sintered powders. However, under the same operating conditions, it was found that production technique has little effect on efficiency. In some conditions, the performance of the gears produced by additive manufacturing (with a smoother tooth profile) was better from the computer-aided design. It was also seen that surface treatment after additive manufacturing has a preventive effect on gear wear and damage.

X-ray particle tracking velocimetry in liquid foam flow.

In this work, we introduce a novel approach to measure the flow velocity of liquid foam by tracking custom-tailored 3D-printed tracers in X-ray radiography. In contrast to optical observations of foam flow in flat cells, the measurement depth equals 100 mm in the X-ray beam direction. Light-weight tracers of millimetric size and tetrapod-inspired shape are additively manufactured from stainless steel powder by selective laser melting. Matching with the foam structure and bubble size, these tracers follow the foam flow. An X-ray beam passes through the radiotransparent foam channel and is detected by an X-ray image intensifier. The X-ray transmission images show the two-dimensional projections of the radiopaque tracers. Utilizing particle tracking velocimetry algorithms, the tracer trajectories are measured with both high spatial (0.2 mm) and temporal (25 fps) resolution. Fine and coarse liquid foam flow of different velocities are studied in a partly curved channel with rectangular cross section. The simultaneous time-resolved measurements of the tracers' translational motion and their intrinsic rotation reveal both the local velocity and vorticity of the foam flow. In the semi-circular curved channel section, the rigid-body-like flow pattern is investigated. Moreover, a relaxation of the foam structure in the transition zone between straight and curved section is observed.

The glass swing: a vector active structure made of glass struts and 3D-printed steel nodes

The majority of glass used in load-bearing structures is as planar elements. Some projects exist that use linear glass elements. This paper discusses in broad terms the design, engineering, and fabrication of a unique vector active glass structure consisting of glass bundles and partly printed steel connections. A structure was conceived that utilizes the glass bundles in a way that can be directly experienced by the users: a swing. To create a non-standard form for the swing, a structural optimization procedure was used. To realize the structure, a novel steel node was developed and produced using an additive manufacturing technique in steel. These novel applications have made the project innovation heavy, particularly considering the limited timeframe for its development and construction. Description is given of the several optimization techniques incorporated in the digital process, the assembly and testing of the glass bundles, and the manufacturing of the steel nodes by Wire and Arc Additive Manufacturing.

Metal 3D-printed catalytic jet and flame ionization detection for in situ trace carbon oxides analysis by gas chromatography.

A gas chromatographic approach for the determination and quantification of trace levels of carbon oxides in gas phase matrices for in situ or near-line/at-line analysis has been successfully developed. Catalytic conversion of the target compounds to methane via the methanation process was conducted inside a metal 3D-printed jet that also acted as a hydrogen burner for the flame ionization detector. Modifications made to a field transportable gas chromatograph enabled the leveraging of advantaged microfluidic-enhanced chromatography capability for improved chromatographic performance and serviceability. The compatibility with adsorption chromatography technology was demonstrated with in-house constructed columns. Sustained reliable conversion efficiencies of greater than 99% with respectable peak symmetries were attained at 400°C. Quantification of carbon monoxide and carbon dioxide at a parts-per-million level over a range from 0.2ppm to 5% v/v for both compounds with a respectable precision of less than 3% relative standard deviation for peak area (n=10) and a detection limit of 0.1ppm v/v was achieved. Linearity with correlation coefficients of R2 greater than 0.9995 and measured recoveries of >99% for spike tests were achieved. The 3D-printed steel jet was found to be reliable and resilient against potential contamination from the matrices owing to the in situ backflushing capability.

THE APPLICATION OF WELD-BASED ADDITIVE MANUFACTURING STEEL TO STRUCTURAL ENGINEERING

The present work aims at providing the first considerations upon the application of innovative manufacturing technology for civil engineering purposes. In particular, among the 3D printing processes currently available, Weld-Based Additive Manufacturing (WAM) results to be the most suitable technique for the realization of innovative structural forms in metal material. The great potential of taking the printing head "out of the box" allows for the construction of innovative shapes by adding layer upon layer of welded steel. In particular, the study is focused on the realization of the first 3D-printed steel footbridge by a Dutch company held in Amsterdam, called MX3D, and its Additive manufacturing process, which results in specific constraints and limitations to be taken into account for design purposes. First, the design issues are described, by considering the printing parameters to be adopted for the realization of large-dimensions structures, and then the implications in terms of specific geometrical and mechanical characteristics are studied. These first engineering evaluations are intended to pave the way towards the development of a ground-breaking technology for the fully-automated design and construction of novel 3D-printed building structures through innovative robotic manufacturing processes whose parameters are still not fully known

Gas Chromatography with In Situ Catalytic Hydrogenolysis and Flame Ionization Detection for the Direct Measurement of Formaldehyde and Acetaldehyde in Challenging Matrices.

A gas chromatographic strategy to advance the direct detection and quantification of volatile aliphatic aldehydes such as formaldehyde and acetaldehyde in gas phase matrices without the need for sample pretreatment or concentration has been successfully developed. The catalytic hydrogenolysis of aldehydes to alkanes is conducted in situ within the 3D-printed steel jet assembly of the flame ionization detector and without any additional hardware required. Reliable conversion efficiencies of greater than 90% with respectable peak symmetries for the analytes were attained at 400 °C. Quantification of formaldehyde and acetaldehyde at parts-per-million levels over a range of 0.5-300 ppm (v/v) for formaldehyde and 0.2-430 ppm (v/v) for acetaldehyde with a respectable precision of less than 5% RSD ( n = 10) was achieved. The total analysis time was less than 10 min. Linearity with a correlation coefficient ( R2) greater than 0.9997 and measured recoveries of >99% for spike tests under the specified conditions were achieved. The 3D-printed steel jet assembly was found to be reliable and resilient to matrices such as air, water, hydrocarbons, and aromatics. An additional benefit realized with this analytical strategy is that the slight restriction induced by the presence of the catalyst in the 3D-printed jet assembly enables backflush via the inlet split vent without the need for additional pressure control or intercolumn-connection devices. The utility of this technique was demonstrated with important aldehyde applications from various segments.

Rapid prototyping of force/pressure sensors using 3D- and inkjet-printing

This work reports on inkjet- and 3D-printed force/pressure sensing devices. The employed printing processes can enable cost- and resource-efficient, fast and flexible designs compared to solid-state technology which is used as a reference design. The pressure sensing devices are realized as either 3D-printed steel or 3D-printed ceramic diaphragms. Both designs thus withstand harsh environmental conditions and elevated temperatures. Additionally, the increased size guarantees less sensitivity to dirt or moisture due to the larger diameter of the diaphragms. The hardware used for the capacitive sensor read-out is based on a shunt measurement system and subsequent demodulation. This architecture enables long cabling, allowing for large parasitic capacitances, without significant loss of transferred signal power, due to the employed power matching to the transmission line. Physical analyses such as contact angle measurements, profilometer measurements, and focused ion beam analysis are done to characterize the resulting printed surfaces. Then, the response of both designs is evaluated by applying force on the diaphragms surface using a moveable load cell. The gathered results are also compared to finite element method simulations.

3D-printed steel reinforcement for digital concrete construction – Manufacture, mechanical properties and bond behaviour

Digital concrete construction has recently become the subject of very rapidly growing research activities all over the world. Various technologies involving 3D-printing with concrete have been developed, and the number of demonstration projects and practical applications has been increasing exponentially. Most of these approaches are focused on the placement of concrete, while the suggested solutions for incorporation of reinforcement are still rudimentary, and as such they lag behind the concepts for printing concrete. Since the use of (steel) reinforcement is mandatory in most structural applications, there is an urgent need to bring the technology of reinforcing 3D-printed structural elements forward. The article starts with a brief overview of the existing approaches in using reinforcement in digital concrete construction. Then the authors’ own research work is presented, namely a feasibility study on 3D-printing of steel reinforcement using gas-metal arc welding. A description of the newly developed 3D-printing process is followed by a demonstration of its feasibility in producing vertical steel reinforcement bars with and without extra ribs. The mechanical performance of the printed bars was investigated by means of uniaxial tension tests. The samples exhibited comparable mechanical properties to common steel reinforcement of the same diameter. The investigation of fracture surfaces confirmed a ductile mode of failure of the printed steel bars. Finally, the bond between printed steel bars and printable fine-grained concrete was tested by means of pull-out experiments. Here the overall performance could be rated as satisfactory, even though it could be improved by introducing extra ribs in the process of bar manufacturing.

Galvanic exchange platinization reveals laser-inscribed pattern in 3D-LAM-printed steel

Galvanic exchange involving dissolution of iron and the simultaneous growth of platinum onto 316 L stainless steel was investigated for specimens manufactured by 3D-printing, and the behavior was compared to conventional stainless steel. Novel phenomena associated with the 3D-printed steel, but not conventional steel, reacting in three distinct phases were observed: first, with low platinum loading, a bright etching pattern linked to the laser-manufacturing process is revealed at the steel surface; second, a nanostructured pore pattern with platinum nano-deposits forms; and third, a darker platinum film coating of typically 500-nm thickness forms and then peels off the steel surface with further platinum growth underneath. Unlike the conventional steel (and mainly due to residual porosity), 3D-printed steel supports well-adhered platinum films for potential application in electrocatalysis, as demonstrated for alkaline methanol oxidation.Graphical abstractᅟ

Effect of the Ultrasonic Nanocrystalline Surface Modification (UNSM) on Bulk and 3D-Printed AISI H13 Tool Steels

A comparative study of the microstructure, hardness, and tribological properties of two different AISI H13 tool steels—classified as the bulk with no heat treatment steel or the 3D-printed steel—was undertaken. Both samples were subjected to ultrasonic nanocrystalline surface modification (UNSM) to further enhance their mechanical properties and improve their tribological behavior. The objective of this study was to compare the mechanical properties and tribological behavior of these tool steels since steel can exhibit a wide variety of mechanical properties depending on different manufacturing processes. The surface hardness of the samples was measured using a micro-Vickers hardness tester. The hardness of the 3D-printed AISI H13 tool steel was found to be much higher than that of the bulk one. The surface morphology of the samples was characterized by electron backscattered diffraction (EBSD) in order to analyze the grain size and number of fractions with respect to the misorientation angle. The results revealed that the grain size of the 3D-printed AISI H13 tool steel was less than 0.5 μm, whereas that of the bulk tool steel was greater than 4 μm. The number of fractions of the bulk tool steel was about 0.5 μm at a low misorientation angle, and it decreased gradually with increasing misorientation angle. The low-angle grain boundary (LAGB) and high-angle grain boundary (HAGB) of the bulk sample were about 21% and 79%, respectively, and those of the 3D-printed sample were about 8% and 92%, respectively. Moreover, the friction and wear behavior of the UNSM-treated AISI H13 tool steel specimen was better than those of the untreated one. This study demonstrated the capability of 3D-printed AISI H13 tool steel to exhibit excellent mechanical and tribological properties for industrial applications.