Search NASA⌕ Search

SEARCH · Search NASA

Results for “large scale extrusion deposition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

Development of Large Scale Extrusion Deposition for Structural Applications

Large Scale Extrusion Deposition (LSED) is an evolving additive manufacturing (AM) technology that research, such as that taking place at Oak Ridge National Laboratory (ORNL) and companies like Local Motors, are continuing to utilize and develop new applications. A major LSED application of interest has been molds and tooling as it allows for much shorter production time and lower cost. However, interest has been expanding into using LSED for more structural applications due to more frequent use of high performing polymer composites as feedstock. The use of LSED for structural applications is of particular interest to Local Motors as it is currently being used to create commercially viable, energy efficient electric vehicles. LSED offers a unique opportunity when compared to traditional manufacturing methods as it can significantly reduce the number of components necessary, while decreasing embodied energy and carbon emissions. Even with these benefits however, it is important that LSED is properly understood from a structural aspect as this field has not been as heavily researched as tooling. To ensure a high level of safety and repeatability is an essential responsibility of a manufacturer whose products are structural in nature. As such it is important to understand the materials and LSED process to make structural objects that the manufacturer can be confident in. The main goals of this project were to: develop and investigate materials that are of interest for structural LSED applications, further develop and understand the current machines used in LSED and develop simulations tools of LSED and the mechanical properties of the created structure. Material development focused on composite materials that have high mechanical properties and are stable in a variety of environments. The materials were tested to determine their as printed mechanical and thermal properties as these are necessary for simulations. Once the materials were investigated thoroughly, it allowed for simulations to be performed to compare to experimental data with simulations. Materials were also vetted to determine candidates for multi-material printing. The machine development focused around the areas of process monitoring, non-destructive evaluation, and quality control. Finally, the goal of the simulations was to develop a realistic model of printed structures, including in-process simulation and dynamic simulation. The routes to get to some of these goals and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. This project resulted in many valuable results such as the development of an nondestructive evaluation (NDE) technique for interlayer defects, proof of simulation for warpage in simple parts, the development and utilization of a profilometer to monitor a print for defects or inconsistencies, thorough investigation of a material used commercially for structural LSED applications and valuable experimental data on the applicability and advantages of multi-material crush structures versus their neat counterparts by creation and testing of samples.

36 MATERIALS SCIENCE↗

Characterizing The Internal Morphology of Transition Regions in Large-Scale Extrusion Deposition Additive Manufacturing

A dual-hopper feed system that was developed for the Big Area Additive Manufacturing (BAAM) system allows for transitioning between different materials while maintaining continuous deposition. This technique creates a step-change in material feedstock by switching the pellet feeding system to alternate which hopper is currently supplying material, allowing for multi-material construction. The step-change in feedstock material produces a transition region that is characterized by a compositional gradient and blended internal morphology. Initial cross-sectional imaging of the transition region revealed a non-homogenous blend of materials with distinct domains of each material, likely due to incomplete mixing within the screw. This study used a carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) and an unfilled ABS to characterize the internal structure and to correlate it to mechanical performance by tracking microhardness across cross-sections of the transition region.

Brackett, James↗

Online thermal profile prediction for large format additive manufacturing: A hybrid CNN-LSTM based approach

Large format additive manufacturing (LFAM) is an advanced 3D printing technique that efficiently fabricates large-scale components through a layer-by-layer extrusion and deposition process. Accurate surface layer temperature monitoring is essential to prevent manufacturing failures and ensure final product quality. Traditional physics-based offline approaches for simulating thermal behavior are often inefficient and complex, posing challenges on real-time, in-situ monitoring. Here, to address this, we propose a data-driven hybrid CNN-LSTM model to predict sequential thermal images of arbitrary length using real-time infrared thermal imaging. In this approach, a Convolutional Neural Networks (CNN) is trained offline to capture spatial features, reduce dimensional complexity, and enhance time efficiency, while a stacked Long Short-Term Memory (LSTM) is applied online to capture temporal information for improved prediction of future thermal behavior in subsequent printing layers. Model performance is evaluated using MSE, SSIM, and PSNR metrics and is benchmarked against stacked LSTM and convolutional LSTM models, demonstrating superior accuracy and applicability. Additionally, to mitigate noise from moving extruders and gantry backgrounds in thermal images, a fine-tuned semantic segmentation model is implemented offline to extract printing geometry, enabling precise temperature tracking along the tool path for further thermal analysis. The frameworks developed in this study significantly advance temperature monitoring, thermal analysis, and in-situ manufacturing control for LFAM, bridging the gap between theoretical modeling and practical application.

Geometry extraction↗

Large-scale reactive thermoset printing: Complex interactions between temperature evolution, viscosity, and cure shrinkage

Thermoset composites are strong candidates for large-scale material extrusion additive manufacturing (AM). However, uncured thermoset composites become unstable as print height increases. Here, chemical initiation of vinyl ester immediately before deposition was used to suppress collapse and enable large-scale thermoset printing. Structural stability was assessed by printing thin walls at various layer times and monitoring thermal gradients with an infrared camera. Stable printing was observed at a layer time of 4.50 min, approximately half the gel time of the material (8 min). Self-weight collapse occurred at short layer time (0.68 min), whereas warpage occurred at long layer time (6.50 min). Here, a new behavior was discovered at intermediate layer time (2.25 min) where the heat generated by the reaction causes new, un-gelled layers to flow. Forced convection eliminates this behavior, stabilizing the 2.25-min layer time print. These findings motivated development of a less exothermic material system, which was used to print a large-scale mold and demonstrate the value of this understanding. By presenting these challenges of large-scale reactive thermoset AM for the first time, this work motivates focused studies of the complex interplay between rheological, thermal, and chemical behaviors to improve the feasibility of large-scale thermoset AM. Tensile properties of the printed material were also measured. Longitudinal and transverse elastic moduli are 3.79 and 2.95 GPa, respectively, and corresponding tensile strengths are 36.11 and 18.83 MPa. The glass transition temperature is 93.13 °C.

36 MATERIALS SCIENCE↗

Material Characterization for Large Scale Additive Manufacturing (AM)

The objective of this project was to enable prediction of residual stresses and warpage for extrusion deposition additive manufacturing (EDAM) fabricated carbon fiber thermoplastic matrix parts with three different materials systems produced by Techmer. The materials selected include Polyphenylene sulfide reinforced with 50% by weight of carbon fiber (CF-PPS), Polyethersulfone reinforced with 25% by weight of carbon fiber (CF-PESU), Polysulfone reinforced with 25% by weight of carbon fiber (CF-PSU). ADDITIVE3D © , a physics-based simulation workflow for EDAM, provided the simulation capabilities required for this project. Simulation predictions were validated against measurements carried out during and after the printing process carried out in the CAMRI and LSAM systems . Predictions for temperature, degree of crystallinity and deformation were carried out for the three material systems and two different geometries. Predictions for temperature were correlated very well with the experimental measurements for the two geometries printed using the three-material systems. The crystallinity level was verified for CF-PPS. The predictions for part deformation were in good agreement with the experimental measurements. In the best-case, predictions were within 8% of the maximum displacement observed in the 3-direction whereas predictions were within 14% for the worst-case. The adoption of this technology in commercial large-scale EDAM production processes would dramatically reduce the costs associated with producing articles by that process. Many thousands of dollars in materials, energy, and machine time could be saved by utilizing this simulation technology to develop articles rather than iterative printings to arrive at the optimal or correct design. The avoidance of a single failed print has the possibility of saving tens of thousands of dollars involved in the cost of material, machine and operators’ time.

36 MATERIALS SCIENCE↗

Controlling substrate temperature with infrared heating to improve mechanical properties of large-scale printed parts

Additively manufactured parts made with polymer extrusion techniques can be 50-75% weaker in the z-direction (across layers) than in the x- and y-directions. This has been attributed to poor mobility of polymer chains and a low degree of entanglement across a cold deposition interface. This is particularly a challenge when printing large-scale parts, such as with the Big Area Additive Manufacturing (BAAM) system, because layer times can exceed several minutes. The current work presents a method for controlling the temperature of the substrate material on the BAAM just prior to deposition using infrared heating lamps. Additionally, long layer times were simulated by actively cooling the material following deposition of each layer. The effect of substrate temperature on the z-direction mechanical properties of 20% carbon fiber reinforced acrylonitrile butadiene styrene (ABS) was measured for an initial temperature ranging from 50 °C to 150 °C and a preheated temperature ranging from 150 °C to 220 °C. Infrared preheating proved to be very effective when applied to substrates that had cooled considerably, almost doubling the tensile strength and increasing the fracture toughness by a factor of 7x.

36 MATERIALS SCIENCE↗

Anisotropic thermal behavior of extrusion-based large scale additively manufactured carbon-fiber reinforced thermoplastic structures

Large format additive manufacturing (AM) enables rapid manufacturing of large parts and structures with minimum waste in material and energy. Extrusion-based AM deposition processes provide parts with highly anisotropic thermal properties, which are not typically reflected in textbook values for these materials. In order to develop accurate models that describe the directionally dependent thermal behavior of these materials in processing and service, accurate measurements of specific heat capacity and thermal conductivity are required. Here, this work characterizes, documents, and analyzes the effect of the anisotropic nature of the extrusion-based deposition process on the specific heat capacity and thermal conductivity of the resulting AM products. All measurements were made over a temperature range of 20–180°C using the transient plane source technique, also referred to as the hot disk technique. Three of the most commonly used large format AM feedstock materials that utilize carbon fiber reinforcement were examined in this work: acrylonitrile butadiene styrene, polyphenylene sulfide and polyphenylsulfone. Finally, these findings can serve as a thermal design/process guideline for future large format AM applications.

36 MATERIALS SCIENCE↗

Large-scale additive manufacturing tooling for extrusion-compression molds

Carbon fiber reinforced polymer composites (CFPC) have been used in additive manufacturing (AM) due to both the high-strength-to-weight and superior-stiffness-to-weight ratios. CF AM is being considered for tooling applications. In AM, CFPCs are usually aligned along the deposition direction; however, it results in anisotropic thermal properties which affect the heat transfer and warpage of the final part. In this study, three male molds with different infill patterns were produced via the material extrusion additive manufacturing (EDF-AM) process. These include (a) 0°: infill pattern along the printing direction; (b) 90°: infill pattern perpendicular to the printing direction; and (c) 0°/90°: alternate layers along and perpendicular directions. The effect of the infill pattern on thermal conductivity was analyzed and observed that 0° infill (surface temperature: 79.2°C) had the highest conductivity; and 90° infill (surface temperature: 66.4°C) had the least.

36 MATERIALS SCIENCE↗

Effect of Internal Structure on Warpage in a Large-Scale Additive Manufacturing Process With Bio-Derived Composites

Extrusion-based large-format additive manufacturing (LFAM) often results in unintended deformation and failures due to thermal residual stress between layers. This LFAM involves a hot molten polymer deposited on a previously deposited and cooled layer, generating a temperature mismatch between the layers. The temperature discrepancy causes a thermal contraction mismatch, generating thermal residual stress. Due to the residual stress, printed structures experience warpage and delamination Therefore, understanding the heat distribution behavior is essential to preventing undesired deformation and failures. The goal of this study is to investigate the effect of infill patterns on heat distribution and deformation in an LFAM system. Wood fiber-reinforced polylactic acid was used as a sustainable and low-cost reinforcement material. A numerical model was developed to predict the temperature and deformation field with thermo-mechanical properties, which were measured by a dynamic mechanical analysis and a thermal expansion test. Simulations were performed on a box geometry with three different infill patterns. The simulation model was verified with temperature data gathered from an infrared camera. The results show good agreement between predicted and measured temperature profiles. The developed simulation model was applied to a roof tray with different infill patterns for a case study. We found that the different thermal mass distributions resulting from the various infill patterns affected the heat distribution and deformation. These findings contribute to a better understanding of the thermal and mechanical behavior of LFAM.

Jo, Eonyeon↗

High-performance molded composites using additively manufactured preforms with controlled fiber and pore morphology

Here, large-scale multimaterial preforms produced by additive manufacturing (AM) underwent compression molding (CM) to produce high-performance thermoplastic composites reinforced with short carbon fibers. AM and CM techniques were integrated to control the fiber orientation (microstructure) and to reduce void content for the improved mechanical performance of the composite. The new integrated manufacturing technique is termed “additive manufacturing-compression molding” (AM-CM). For the present study, the most common materials were used for large-scale printing, i.e., acrylonitrile butadiene styrene (ABS), carbon fiber (CF)–filled ABS (CF/ABS) and glass fiber (GF)–filled ABS (GF/ABS). Three different manufacturing processes; (a) AM (b) extrusion compression molding (ECM), and (c) AM-CM were used to prepare four different panel configurations: (1) neat ABS, (2) CF/ABS, (3) overmold (CF/ABS over neat ABS), and (4) sandwich (neat ABS between two CF/ABS layers). The mechanical properties (tensile and flexural strength and modulus, and Izod impact energy) of samples prepared via all three manufacturing processes were compared. X-ray microcomputer tomography was employed to evaluate the fiber orientation distribution and the volumetric porosity content. The preform maintained high fiber alignment (≈ 82% of fibers within the range of 0–20° in the deposition direction), and the volumetric porosity was reduced by 50% from 3.79% to 1.91% after compression. The alignment of long pores along the deposition direction was also observed. The mechanical properties are discussed with correlation to the fiber alignment and void content in the samples. CF/ABS samples prepared by AM-CM showed significant improvement of 11.15%, 35.27%, 28.6%, and 74.3% in the tensile strength, tensile modulus, flexural strength, and flexural modulus, respectively, when compared with samples prepared by ECM. Unique aspects of this study are the demonstration of large-scale multimaterial AM and the use of multimaterials as preforms to make high-performance composites.

36 MATERIALS SCIENCE↗

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Today, large-scale additive manufacturing with plastics and composite materials requires continuous monitoring by experienced staff to prevent, detect and correct anomalous events affecting the performance of the printed part. We address the complexity of this demanding task by designing a camera-based anomaly detection system utilizing probabilistic principal component analysis (PPCA). This is a machine learning technique is trained with thermal images collected during normal operation of the large-scale printer (Cincinnati BAAM). This technique is advantageous for practical applications as there is no need to artificially introduce anomalous conditions into model training. During deployment, we challenge this model by introducing deliberate variations of the extruder speed. We reduce extrusion speed to a lower level, between 70 and 95% of the nominal value to collected test images. Our results show that images are easily identified as anomalous for extruder speeds at or below 85% of the nominal speed, meaning that an anomalous reduction of the material deposition rate can be detected within seconds of its onset. We show that our results are robust to (a) camera-to-camera variability and (b) print-to-print variability.

Pike, John [ORNL]↗

Reducing warpage in a hybrid large-scale additive manufacturing and compression molding process

In recent years, a hybrid manufacturing process, developed by combining extrusion-based large-scale additive manufacturing (AM) and compression molding (CM) techniques, has shown promising outcomes for producing structurally functional parts. The process can be used with both short fiber-reinforced composites and neat polymers and hence, even multi-material parts can be manufactured easily. This process offers the advantages of structural enhancement by having a desired fiber orientation using a large-scale AM process, as well as rapid manufacturing capability using a CM process. In the large-scale AM process, the alignment of fibers in the deposition direction enables significant improvement in the mechanical properties of the manufactured parts. However, the anisotropy resulting from the directional arrangement of fibers also introduces challenges related to warpage in the produced parts. This study aims to identify the causes of warpage and propose strategies to mitigate it. The research involves the use of preforms manufactured through the large-scale AM, which are then combined with the neat resin for CM manufacturing. A finite element-based numerical simulation model is developed, employing a sequentially coupled thermomechanical approach. Through a parametric study using the simulation models, optimization of printing direction and preform geometry is performed to minimize warpage. This contributes to the advancement and wider adoption of AM/CM hybrid manufacturing to produce structurally functional parts.

Jo, Eonyeon↗

Additive Manufacturing of Dissolvable Mandrels

ORNL collaborated with Mitsubishi Chemical America to investigate different grades of vinyl alcohol co-polymers as a potential feedstock material for large-scale material extrusion additive manufacturing (AM). Dissolvable polymers and can find potential applications in AM tooling for complex, hollow, and trapped composite structures without the need for specialized molds and tools. This CRADA Phase I work involved analysis of three different developmental grades of vinyl alcohol co-polymers for thermal and rheological properties, followed by print trials on the Big Area Additive Manufacturing (BAAM) system using these materials. Finally, printed part properties, including mechanical and thermal performance, as well as dissolvability were evaluated. The properties and performance evaluated in this phase of the project have provided guidelines to further develop these vinyl alcohol co-polymers to enable large-scale printing at high deposition rates and obtain parts that satisfy high temperature molds and dies requirements.

36 MATERIALS SCIENCE↗

Co-Extrusion (CoEx) for Cost Reduction of Advanced High-Energy-and-Power Battery Electrode Manufacturing

Co-Extrusion (CoEx) is a deposition technology developed at PARC that uses engineered fluidic channels to cause multiple streams of dissimilar fluids to impart shape to one another. Here, we describe the use of CoEx to produce structured cathode electrode films to improve electrochemical performance of thick electrode films. CoEx enables us to create structured electrode films that have periodic regions of enhanced ionic conductivity, enabling higher utilization of thicker cathode films at high discharge rates. While increasing electrode thickness is a known method for increasing energy density of battery electrodes, this increase in energy density typically also results in reduced power density. This project, a collaboration between the Palo Alto Research Center, Oak Ridge National Laboratories, and Ford Motor Company, seeks to first validate the benefits of CoEx at the coin cell level, before performing the necessary R&D effort to scale production up to large (10+ Ah) pouch cells that will show increased energy density without a reduction in power density. We used conventional battery materials (commercially available NMC, PVDF, carbon black, and graphite) to produce structured electrodes via CoEx and compared them to thick and thin conventionally produced (unstructured) battery electrodes. CoEx electrodes show improved high rate performance compared to unstructured electrodes, resulting in higher energy density pouch cells compared to the baseline electrode of 7 and 11% in volumetric and gravimetric energy density, respectively. These electrodes also showed substantially improved electrochemical performance at high discharge rates compared to thick conventional electrodes.

25 ENERGY STORAGE↗

Structural stability of thin overhanging walls during material extrusion additive manufacturing of thermoset-based ink

Recent developments have enabled material extrusion additive manufacturing of thermoset-based composite inks on the large scale. In addition, printing out-of-plane components is of broad interest to the polymer material extrusion community. Here, we address some of the challenges associated with both large-scale and out-of-plane thermoset material extrusion additive manufacturing by studying the height at which thin overhanging walls collapse. Walls at a range of overhang angles were printed until they collapsed. An optical camera captured the profile of each wall throughout the print, allowing the collapse height to be identified and the geometric fidelity to the programmed angle to be evaluated. Using previously measured rheological properties, predictive models were generated to approximate the collapse height and profile of the deflected walls. First, an analytical model was created to predict the height at which the walls would yield. The analytical model assumes the walls exhibit a perfectly linear profile; however, experiments proved this assumption to be false. Therefore, a finite element simulation was developed to account for the elastic deflection that occurs during printing. The finite element simulation predicts both the yield height and the deflected profile after the deposition of each layer. For the properties of the thermoset ink used here, the yield height predicted by the analytical model and finite element simulation are virtually identical. These predictions match experimental data reasonably well, but minor errors are observed. Accounting for the fully plastic moment appears to explain the small mismatch between experimental data and predictions. Additionally, the finite element simulation provides an excellent prediction of the deflected profile before the wall begins to collapse. Finally, by demonstrating that the collapse height and deflected profile of thin overhanging walls can be predicted, this work illustrates how the soft viscoelastic properties of thermoset-based composite inks limit the scale of a key feature required to print some nonplanar components. It also provides a basis to tailor in-process curing systems to suppress deflection and collapse of thin overhanging walls.

36 MATERIALS SCIENCE↗

UHT-CAMANCHE: Ultra-High Temperature Ceramic Additively Manufactured Compact Heat Exchangers

The conceptual basis for this project is the convergence of advanced ultra-high temperature ceramic materials and additive manufacturing technologies to produce compact ceramic heat exchangers with complex internal flow path geometries. Task areas were broadly divided into materials and manufacturing development, heat exchanger design, component testing, and techno-economic analysis. Technical challenges included the design and commissioning of new test facilities, improving feature resolution and deposition rate of ceramic additive manufacturing techniques, establishing process-structure-property relationships in additively manufactured ultra-high temperature ceramics, and assessing high temperature materials compatibility in CO 2 environments. The primary candidate material evaluated in this work is a composite comprising zirconium diboride (ZrB2) with 30 vol. % silicon carbide (SiC) which was selected based on its desirable combination of high temperature mechanical properties, high thermal and electrical conductivities, and oxidation resistance. High solids loaded ZrB2-SiC pastes suitable for extrusion-based additive manufacturing were developed for the first time as part of this work. Materials compatibility studies indicate this material oxidizes in CO 2 to form a protective borosilicate scale which transforms to pure silica above 1000°C. Parts made by additive manufacturing displayed enlarged grain sizes produced by pressureless sintering as compared to hot-press sintering. Increases in microstructural coarseness have outsized effect on oxidation performance up to 1400°C due to incomplete oxidation of coarse large diameter SiC particles resulting in lower amounts of silica that apparently inhibit protective scale formation. Additive manufacturing as a forming technique did not appear to significantly affect thermal conductivity, hardness, or elastic modulus, though flexural strength was reduced by half or more as compared to traditionally hot-pressed materials. This effect was attributed to the presence of strength-limiting flaws (ca. 40 microns in size) originating from extrudate inhomogeneities that could potentially be eliminated with further process improvements. Attempts to attain economies of scale for production of multi-kilowatt scale heat exchangers by ceramic additive manufacturing proved difficult. Lack of automation and a modest extrusion rate while retaining fine feature resolution made the overall process labor intensive and limited experimental throughput. A number of full-scale components were taken through post-process heat treatments including drying, binder burnout, and sintering; however, none survived without significant flaws or cracks. Therefore, no operational data from a newly installed heat exchanger test loop were able to be obtained during the performance period. Continued research and development is recommended to improve economic feasibility of ceramic additive manufacturing by standardizing the use of advanced sensors, artificial intelligence, and automation tools to reduce associated labor costs and accelerate production rates. The materials and manufacturing techniques demonstrated in this work are likely to find applications in defense and energy applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal images collected during large-scale 3D printing with Ingersoll MasterPrint

This data set contains images produced to test the performance of anomaly and fault detection methods in the context of additive manufacturing. Two print jobs were executed using the Ingersoll MasterPrint with the Model 30 Strangpresse extruder. The material used was Techmer compounded polylactic acid (PLA) with wood flour as a filler (80/20 PLA/WF by weight). The first print job consists of the 3D printing of a hexagonal cylinder with a two-bead wall. This print was sliced at a gantry velocity of 3000 millimeter per minute, and an extruder screw speed of 68.14 rotations per minute. This are considered the normal operating conditions. A second hexagonal cylinder was printed using a reduced extruder screw speed, 15% lower than under normal operating conditions. The images were collected with a Teledyne FLIR Lepton 3.5 infra-red camera, a small form factor radiometric long-wave infrared camera with a spectral range of 8 µm to 14 µm. Sensor resolution was 160x120 pixels, with a pixel size of 12 µm, a temperature range of -10 - 450°C, and an accuracy of +/- 10°C in its low gain configuration. Images in this data set were collected with cameras oriented at the printer nozzle. The nozzle camera setup consisted of two cameras located 12.5cm from the nozzle center. These were mounted directly to the print head, so that the camera positions relative to the print direction would remain constant as it rotated around its C-axis to follow the print path. One camera was placed ahead of the nozzle to capture the previous layer immediately before being covered by the new layer of material, while the second camera was placed behind the nozzle and captured the freshly extruded bead. Images are collecting during each phase of the print: (a) idle (i.e., no material deposited), (b) extrusion (i.e., to prime the extruder), and (c) printing (deposition of material to manufacture the hexagonal cylinder).

36 MATERIALS SCIENCE↗