Abstract The claim in additive manufacturing (AM) changes from simply producing prototypes as show objects to the fabrication of final parts and products in small volume batches. Thereby the focus is on freedom of material, dimensional accuracy and mechanical component properties. A novel extrusion-based AM technology has been developed focusing on these issues. The working principle is to form spheres from a thermoplastic polymer melt and build parts by single droplets. The material preprocessing is similar to the injection molding technology and enables a wide range of different thermoplastic polymers as build materials. With the droplet-based working principle high mechanical component properties and dimensional accuracy can be reached compared to similar processes. Further improvements to the process need a detailed knowledge of the physical effects during the build process. The temperature distribution during the manufacturing process determines at which temperature material is fused and how solidification takes place and shrinkage can occur or is suppressed. Thus, it has a significant influence on the mechanical properties and warpage effects of produced parts. In this work a thermal model is presented that describes the heat transfer during the build process. The necessary input data are the material properties and a print job description including the part geometry and building strategy. The basic idea is to simulate each single droplet deposition by applying a dynamic Finite Element Method. All relevant heat transfer effects are analyzed and represented in the model. The model was validated with measurements using a thermal imaging camera. Several measurements were performed during the build process and compared to the simulation results. A high accuracy could be reached with an average model error of about 4° Celsius and a maximal error of 10° Celsius.

Abstract In metal cutting processes the use of cutting fluids shows significant effects on workpiece surface quality by reducing thermomechanical loads on cutting tool and workpiece. Many efforts are made to model these thermomechanical processes, however without considering detailed heat transfer between cutting fluid, tool and workpiece. To account for heat transfer effects, a coupling approach is developed which combines CFD (Computational Fluid Dynamics) and FEM (Finite Element Method) chip formation simulation. Prior to the simulation, experimental investigations in orthogonal cutting in dry and wet cutting conditions with two different workpiece materials (AISI 1045 and DA 718) are conducted. To measure the tool temperature in dry as well as in wet cutting conditions, a two color pyrometer is placed inside a EDM drilled cutting tool hole. Besides tool temperature, the cutting force is recorded during the experiments and later used to calculate heat source terms for the CFD simulation. After the experiments, FEM chip formation simulations are performed and provide the chip forms for the CFD mesh generation. In general, CFD simulation and experiment are in reasonable agreement, as for each workpiece setup the measured temperature data is located between the simulation results from the two different tool geometries. Furthermore, numerical and experimental results both show a decrease of tool temperature in wet cutting conditions, however revealing a more significant cooling effect in a AISI 1045 workpiece setup. The results suggest that the placement of drilling holes has a major influence on the local tool temperature distribution, as the drilling hole equals a thermal resistance and hence leads to elevated temperatures at the tool front.

Abstract Friction stir welding (FSW) has been successfully applied to join dissimilar materials in engineering applications. Fundamental understanding on the underlying physical principles of the dissimilar FSW process is generally required to achieve strong and reliable joints. In this study, we aim to develop a theoretical and numerical model based on computational fluid dynamics (CFD) in order to analyze the in-process heat transfer and material flow during the dissimilar FSW of aluminum and steel. The model describes the coupling behavior between the material distribution, thermal-mechanical properties, interfacial friction, heat generation and transfer. To account for the different material behaviors in stirring zone, a VOF-based approach is adopted. In this paper, preliminary numerical simulation is conducted. Simulation results show that the current modeling approach has the capability to capture the material mixing during the dissimilar FSW of aluminum and steel. The predicted temperature field is shown to be asymmetrical, which is attributed to the different properties of aluminum and steel. The predicted thermal history agrees with the experimental measurements in the literature.

The paper studies how to control boundary slope of optimized parts in density-based topology optimization for additive manufacturing (AM). Boundary slope of a part affects the amount of support structure required during its fabrication by additive processes. Boundary slope also has direct relation with the resulting surface roughness from the AM processes, which in turn affects the heat transfer efficiency. By constraining the minimal boundary slope, support structures can be eliminated or reduced for AM, and thus material and post-processing costs are reduced; by constraining the maximal boundary slope, high surface roughness can be attained, and thus the heat transfer efficiency is increased. In this paper, the boundary slope is controlled through a constraint between the density gradient and the given build direction. This allows us to explicitly control the boundary slope through density gradient in the density-based topology optimization approach. We control the boundary slope through a single global constraint. Numerical examples on heat conduction problem, and coupled 2D and 3D thermoelastic problems demonstrate the effectiveness and efficiency of the proposed formulation in controlling boundary slopes for additive manufacturing.

Direct metal deposition (DMD) is a major additive manufacturing (AM) process, which employs high energy beams as the heat source to melt and deposit metals in layerwise fashion so that complex structural components can be directly obtained. Similar to other metal AM processes, DMD is a complicated thermo-mechanical process, characterized by fast scan rates, large thermal gradients, rapid material phase transformations, and cyclic non-uniform temperature changes. Accurate and efficient computation of the thermal field during the DMD process is essential for understanding the fundamental microstructure evolution and developing the optimization strategy. In this paper, we aim to develop an open-source and fast computation tool for analyzing the heat transfer during the DMD process, which is based on the finite volume formulation and the quiet element method and allows development of customized functionalities at the source level. A computing tool is developed in MATLAB for fast prediction of the temperature field during metal additive manufacturing, and compared against the regular finite element analysis using a commercial software. The preliminary results show that for a system of 14400 cells, deposition of a single path takes 174 s using the commercial software, and 15.8s to 81s depending on the setting of convergence criterion using the in-house code. This represents a time reduction ranged from 90.9% to 53.4%, and the overall error is around 12.1%.

Powder bed metal additive manufacturing (AM) utilizes a high-energy heat source scanning at the surface of a powder layer in a pre-defined area to be melted and solidified to fabricate parts layer by layer. It is known that powder bed metal AM is primarily a thermal process and further, heat conduction is the dominant heat transfer mode in the process. Hence, understanding the powder bed thermal conductivity is crucial to process temperature predictions, because powder thermal conductivity could be substantially different from its solid counterpart. On the other hand, measuring the powder thermal conductivity is a challenging task. The objective of this study is to investigate the powder thermal conductivity using a method that combines a thermal diffusivity measurement technique and a numerical heat transfer model. In the experimental aspect, disk-shaped samples, with powder inside, made by a laser powder bed fusion (LPBF) system, are measured using a laser flash system to obtain the thermal diffusivity and the normalized temperature history during testing. In parallel, a finite element model is developed to simulate the transient heat transfer of the laser flash process. The numerical model was first validated using reference material testing. Then, the model is extended to incorporate powder enclosed in an LPBF sample with thermal properties to be determined using an inverse method to approximate the simulation results to the thermal data from the experiments. In order to include the powder particles’ contribution in the measurement, an improved model geometry, which improves the contact condition between powder particles and the sample solid shell, has been tested. A multi-point optimization inverse heat transfer method is used to calculate the powder thermal conductivity. From this study, the thermal conductivity of a nickel alloy 625 powder in powder bed conditions is estimated to be 1.01 W/m·K at 500 °C.

Cellular structures are broadly applicable to lightweight design and multifunctional applications. Especially, with unprecedented fabrication freedom provided by additive manufacturing (AM), design and optimization of nonuniform cellular structures have recently attracted great research interests. Topology optimization is one of the most powerful tools to obtain the optimized material distribution, and much research have been conducted to optimize cellular structures with the help of this optimization technique. In general, the optimized cellular structure is generated based on a predefined ground structure, and thickness of each strut is then decided based on the optimization result. However, many existing studies did not consider the constraints of AM processes, such as some generated struts may be too thin to be manufactured. Besides, only load support structure was considered in these studies. Other applications, such as heat dissipation or energy absorption, were rarely researched. In this paper, a novel cellular structure design method, which considered both functionality and manufacturability, is proposed. Different from other methods, wall thickness of the structure was set as a constant. To get the optimized material distribution, variable cell sizes were applied. Because of uniform wall thickness, the smaller the unit cell is, the higher its volume fraction will be. By mapping small unit cells to high density area and large cell to low density area, the final optimized cellular structure can be generated. In addition, because smaller unit cells have higher surface-to-volume ratio, this method can also be applied to solve heat transfer problem. Two examples, minimum compliance design of a cantilever beam and maximum heat dissipation efficiency design of a CPU heat sink, were conducted to validate the proposed method.

Modern computer technology enables people to simulate additive manufacturing (AM) process at high fidelity, which has proven to be an effective way to analyze, predict, and design the AM processes. In this paper, a new method is proposed to simulate the melting process of metal powder based AM. The physics is described using partial differential equations for heat transfer and Laminar flow. The level set methods are employed to track the motion of free surface between liquid and solid phases. The issues, including free surface evolution, phase changes, and velocity field calculation are investigated. The convergence problem is examined in order to improve the efficiency of solving this multiphysics problem.

As an emerging and effective nano-manufacturing technology, the directional freezing based 3D printing can form 3-Dimensional (3D) nano-structures with complex shapes and superior functionalities, and thus has received ever increasing publicity in the past years. One of the key challenges in this process is the proper heat management, since the heat induced melting and solidification process significantly affects the functional integrity and structural integrity of the 3D printed nano-structures. To address this challenge, this paper proposes a novel path planning modeling and optimization framework to intelligently control the internal and external heat transfer process and ultimately optimize both the macro- and micro-structure of the printed part. Specifically, a heuristic tool path planning model was formulated and optimized based on thermal analysis process. The simulation results demonstrate that the tool path planning highly affects the spatial and temporal temperature distribution of the being printed part and the optimized tool path planning can effectively improve the uniformity of the temperature distribution which will consequently enhance the performance of the fabricated nano-structures.

Fused-coating based metal additive manufacturing (FCAM) is a newly established direct metal forming process. This method is characterized by deposition metal materials in a crucible and under the driving pressure the molten metal is extruded out from a special designed nozzle. Hence, dense metal parts with different kind of materials can be built on the moving substrate layer by layer. It provides a method to fabricate metal components with lower costs, clean and cheap materials compared with other AM processes. To study the feasibility of this new AM methodology, an experimental system with a molten metal stream generator, a fused-coating nozzle, a process monitor unit, an inert atmosphere protection unit and a temperature measurement unit has been established. In order to determine the proper parameters in the building process, a metal fused-coating heat transfer model analysis and experimental study is performed by using Sn63-37Pb alloy in building three-dimensional components. The process parameters that may affect fabrication are molten and substrate temperature, layer thickness, the substrate-speed, the temperature of substrate, the distance between the nozzle and substrate and the pressure. Microscopy images were used to investigate the metallurgical bonding between layers. The influence of different parameters on the layer thickness and width was studied quantitatively. At last, the optimal parameter was used to fabricate complex metal parts to demonstrate the feasibility of this new technology compared with other AM methods.

The lack of robust testing systems to generate uniform elevated temperatures on specimens in material tests is hindering the advancement of small specimen testing technology (SSTT). The purpose of this study is to develop a novel hybrid heating method combining coil heating and electric-resistance specimen heating to uniformly heat micro specimens in material tests. In a hybrid heating process, two heating coils are used to heat the local temperatures on the specimen ends, and electric current is conducted through the specimen to generate Joule heat and compensate the heat transfer effects of natural convection and radiation around the specimen center area. In this way, a highly uniform temperature distribution can be generated on the specimen between the heating coils. In this study, Thermal-Electrical and Transient Thermal FEA simulations are applied to analyze the temperature distributions and preheating times on the micro specimens under coil heating, electric-resistance specimen heating, and hybrid heating respectively. According to the simulation results, it can be concluded that hybrid heating method can provide the ability to generate highly uniform elevated temperature conditions on different micro tubular specimens with short preheating times.

This paper presented a novel 3D printing technique to fabricate graphene aerogel based on directional freezing. Thermal property of the graphene ink is one of key factors in this process which affects the material integrity and morphology as well as process efficiency and reliability. The major objective of this paper is to develop a heat transfer model to efficiently and reliably predict the temperature evolution of the printed materials and the waiting time between the layers for any input geometry. The simulation results show that the input geometry significantly affects the temperature evolution and waiting time. The proposed technique can not only improve the process efficiency and reliability, it can also serve as a flexible tool to predict and control the microstructure of the printed graphene aerogels.

The development of micro and nanoscale additive manufacturing methods in metals and ceramics is important for many applications in the aerospace, medical device, and electronics industries. Unfortunately, most commercially available metal additive manufacturing tools have feature-size resolutions of greater than 100 μm, which is too large to precisely control the microstructure of the parts they produce. A few research-grade metal additive manufacturing tools do exist, but their build rate is generally too slow for commercial applications. Therefore, this paper presents a new microscale selective laser sintering (μ-SLS) that can be used to improve the minimum feature-size resolution of metal additively manufactured parts by up to two orders of magnitude, while still maintaining the throughput of traditional additive manufacturing processes. In order to achieve this goal, several innovative design features like the use of (1) ultra-fast lasers, (2) a micro-mirror based optical system, (3) nanoscale powders, and (4) a precision spreader mechanism, have been implemented. The micro-SLS system is capable of achieving build rates of approximately 1 cm 3 /hr while achieving a feature-size resolution of approximately 1 μm. This paper will also present new molecular scale models that have been developed for the micro-SLS to quantify and certify the micro-SLS build process. Modeling of the micro-SLS process is challenging, because most macroscale models of the SLS process contain assumptions that are no longer valid when the size of the particles that are being sintered is smaller than the wavelength of the laser being used to sinter them. Therefore, in modeling the micro-SLS process we must account for the wave nature of light and can no longer rely on the ray tracing models commonly used to model the SLS process. Also, heat transfer in the micro-SLS process is dominated by near-field radiation due to the diffraction of the light off the nanoparticles in the powder bed and the ultrafast lasers that are used in the micro-SLS system. This means that the assumptions of heat transfer by conduction and far-field radiation in the macroscale SLS systems are no longer valid for the micro-SLS system. Finally, the agglomeration of nanoparticles in the powder bed must be accurately modeled in order to precisely predict the formation of defects in the final parts produced. Overall, the goal of this modeling effort is to be able to predict the quality of a part produced using any given processing conditions, in order to produce parts that are “born certified” and do not need to be tested post fabrication.

In this study a heat transfer model of machining of Ti-6Al-4V under the application of atomization-based cutting fluid spray coolant is developed to predict the temperature of the cutting tool. Owing to high tool temperature involved in machining of Ti-6Al-4V, the model considers film boiling as the major heat transfer phenomenon. In addition, the design parameters of the spray for effective cooling during machining are derived based on droplet-surface interaction model. Machining experiments are conducted and the temperatures are recorded using the inserted thermocouple technique. The experimental data are compared with the model predictions. The temperature field obtained is comparable to the experimental results, confirming that the model predicts tool temperature during machining with ACF spray cooling satisfactorily.

Temperature field in metal cutting process is one of the most important phenomena in machining process. Temperature rise in machining directly or indirectly determines other cutting parameters such as tool life, tool wear, thermal deformation, surface quality and mechanics of chip formation. The variation in temperature of a cutting tool in end milling is more complicated than any other machining operation especially in high speed machining. It is therefore very important to investigate the temperature distribution on the cutting tool–work piece interface in end milling operation. The determination of the temperature field is carried out by the analysis of heat transfer in metal cutting zone. Most studies previously carried out on the temperature distribution model analysis were based on analytical model and with the used of conventional machining that is continuous cutting in nature. The limitations discovered in the models and validated experiments include the oversimplified assumptions which affect the accuracy of the models. In metal cutting process, thermo-mechanical coupling is required and to carry out any temperature field determination successfully, there is need to address the issue of various forces acting during cutting and the frictional effect on the tool-work piece interface. Most previous studies on the temperature field either neglected the effect of friction or assumed it to be constant. The friction model at the tool-work interface and tool-chip interface in metal cutting play a vital role in influencing the modelling process and the accuracy of predicted cutting forces, stress, and temperature distribution. In this work, mechanistic model was adopted to establish the cutting forces and also a new coefficient of friction was also established. This can be used to simulate the cutting process in order to enhance the machining quality especially surface finish and monitor the wear of tool.

For the accurate simulation about the heat transfer between the flowing oil coolant and ball screw structure, a heat-fluid-solid interaction transient FE (finite element) modeling method of precision ball screw unit is presented in this paper. This FE modeling method allows a supply power prediction of the oil coolant for precision ball screw unit. Then based on predictions, influencing tendencies from oil cooling strategy (oil supply temperature and volume flow rate) onto the time-varying supply powers of oil coolant are investigated. The research results demonstrate that: Firstly, the supply power of oil coolant has the increasing tendency with the time increase. Besides, the steady scale of oil supply power is in proportion to the oil supply volume flow rate, and in inverse proportion to the oil supply temperature. Finally, the maximum steady supply cooling power brings the guidance for the capacity selection of recirculation cooler for the precision ball screw unit.

Ice thermal storage system is a novel technology used in HVAC&R systems for improving energy efficiency of manufacturing facilities. In this paper, the investigation of ice formation in a typical ice thermal storage system was conducted to study the factorial effect of the new structure of thin layer ring placed in a rectangular cavity filled with water on solidification process. Numerical method was used for the computational solutions of fluid flow domain. The performance of the thin layer ring was successfully demonstrated by achieving an increased ice generation area and shortening the time period of ice formation for a typical ice thermal storage system. More detailed research on material, thickness and arrangement of the ring has been comparatively conducted for heat transfer enhancement. The parameters of thin layer ring from three perspectives have been investigated statistically with nine combinations of model are carried out by combining different levels of each factor via Taguchi Method. The results show the contribution ratio of each factor of thin layer ring on improving energy efficiency of ice thermal storage system.

Ti-6AL-4V is widely used in the industry for the high strength-to-weight ratio at elevated temperature, its excellent resistance to fracture and corrosion, and biological properties. However, Ti-6AL-4V is hard to manufacture for its reactive chemical properties and low thermal conductivity that causes high temperature on the tool surface. Prediction of the tool temperature distribution from different manufacturing ways, up and down milling, has great significance in predicting tool wear pattern (cutting speed, feed/tooth, and axial depth of cut) in corner milling on temperature of the tool rake face. The tool material used is general carbide and Johnson-Cook plastic model is utilized to model the behavior of the workpiece Ti-6AL-4V. A separate Abaqus heat transfer model is used to analyze the heat transfer process after the tooth disengages the workpiece and before it engages the workpiece again to predict change of temperature distribution during this cooling process. The comparison of the up milling and down milling on the tool temperature is conducted.

This paper presents a μ – EDM melt-pool model to predict workpiece (anode) material removal from a single discharge μ – EDM process. To model the melt-pool heat transfer and fluid flow equations are solved in the domain containing dielectric and workpiece material. A level set method is used to identify solid and liquid fractions of the workpiece material when the material is molten by μ – EDM plasma heat flux. The plasma heat flux, plasma pressure and the radius of the plasma bubble have been estimated by a μ – EDM plasma model and serve as inputs to the melt-pool model to predict the volume of material removed from the surface of the workpiece. Experiments are carried out to study the effect of inter-electrode voltage and gap distance on the crater size. For inter-electrode voltage in the range of 100 – 150 V and gap distance of 0.5 – 2 μm, the model predicts crater diameter in the range of 150 – 165 μm and maximum crater depth of 25 – 35 μm for discharge duration of 5 μs. The crater sizes for most of experimental craters at higher gap distances show good agreement with the simulated crater shapes. However, at lower gaps, the model over-predicts the crater size.

Extensive experimental work has shown that pulsed laser micro polishing (PLμP) is effective for polishing micro metallic parts. However, the process physics have not been fully understood yet, especially with respect to the melt pool flow. A reliable physical model can be of significant assistance in understanding the fluid flow in the melt pool and its effect on PLμP. In this paper, a two-dimensional axisymmetric transient model that couples heat transfer and fluid flow is described that was constructed using the finite element method. The model not only provided the solutions to the temperature and velocity fields but also predicted the surface profile evolution on a free deformable surface. The simulated melt depth and resolidified surface profiles matched those obtained from optical images of PLμPed sample cross-sections. The model was also used to study the effect of laser pulse duration on the melt pool flow. The study suggests that longer pulses produce more significant fluid flows. The cut-off pulse duration below which minimal fluid flows should be expected was estimated to be 0.66 μs for Ti6Al4V, which also matched well with the experimental results. It is evident that the coupled model offers reliable predictions and thus can be extended for a more complex parametric study to provide further insights for PLμP.