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DOE OSTI2024

PyTorch Implementation of Log-Additive Convolutional Neural Networks

This code is a collection of python code that defines, trains, and tests Log-Additive Convolutional Neural Networks. The model components and training routine are based on the PyTorch python library. The code implements the Log-Additive Convolutional Neural Networks as described in Pagendam et al. 2023. In addition to the Log-Additive Convolutional Neural Networks, this library also defines the Log-Normal Density loss function as described in Pagendam et al. 2023. Code from this paper is not publicly available, so the Pytorch implementation of this type of model is unique to this library.

Callis, Skylar↗

DOE OSTI2023

Development and evaluation of a skeletal mechanism for EHN additized gasoline mixtures in large Eddy simulations of HCCI combustion

Advanced Low Temperature Combustion modes, such as the Sandia proposed Additive-Mixing Fuel Injection (AMFI), can unlock significant potential to boost fuel conversion efficiency and ultimately improve the energy conversion of internal combustion engines. This is a novel improved combustion process that is enabled by supplying small (<5%) variable amounts of autoignition improver to the fuel to enhance the engine operation and control. Common, diesel-fuel ignition-quality enhancing additive, 2-ethylexyl nitrate (EHN), is doped into gasoline to enable Sandia LTGC + AMFI combustion. This manuscript focuses on the development of a reduced sub-mechanism for EHN chemical kinetics at engine relevant conditions that is implemented into a skeletal mechanism for chemical kinetic studies of gasoline surrogate fuels. The mechanism validation utilized zero-dimensional numerical simulations and comparison to shock tube ignition-delay data of pure and EHN-doped n-heptane. Additional validation is presented with Homogeneous Charge Compression-Ignition (HCCI) engine data of pure and EHN-doped research-grade E10 gasoline. Then, the mechanism was deployed in a 3-D computational fluid dynamics (CFD) using Large Eddy Simulations (LES) to model the HCCI engine experiments of 0.4% vol EHN additized E10 gasoline at several equivalence ratios. Simulations showed a very good performance of the mechanism, and the model accurately reproduced (a) the ignition point, (b) combustion phasing, (c) combustion duration, and (d) the peak of the heat release rates of the engine experiments. The results show that EHN promotes Low-Temperature Heat Release, ultimately driving the gasoline to autoignite at thermodynamic conditions where the fuel would not otherwise ignite. Overall, this work demonstrates a viable reduced chemical-kinetic mechanism for EHN and shows that it can be combined with a skeletal gasoline mechanism for CFD-LES analysis of well-mixed LTGC that matches well with experimental results. The CFD-LES analysis also shows the spatial distribution of EHN-fuel interactions that control the autoignition throughout the combustion chamber.

Guleria, Gaurav↗

DOE OSTI2025

In situ Visible Light and Thermal Imaging Data from a Laser Powder Bed Fusion Additive Manufacturing Process Co-Registered to X-ray Computed Tomography and Fatigue Data

This dataset is comprised of in situ sensing data collected during a laser-based powder bed fusion additive manufacturing process, as well as rasterized scan path information, post-build X-ray computed tomography (XCT), and fatigue test results. A total of 64 cylinders, approximately 15 mm in diameter and 102 mm tall, were printed out of stainless steel 316H on a Colibrium Additive Concept Laser M2 Series 5 machine. Parameters known to produce dense material were used to construct 56 of these cylinders, while the remaining 8 cylinders were printed with relatively high energy density parameters prone to producing keyhole pores. In addition, two spatter generation blocks were constructed upstream of the 64 cylinders such that ejecta produced during the melting of the spatter generators were stochastically seeded onto the 64 cylinders. Based on previous experiments, these spatter particles were theorized to produce stochastic lack-of-fusion pores. During the construction of the build, high-resolution images of reflected light in the visible spectrum were captured both before and after recoating for each print layer. Additionally, temporally integrated thermal imaging in the near infrared spectrum produced integrated sum and max images on a layerwise basis. The multimodal in situ data has been co-registered to the build plate coordinate system, allowing for identification of process anomalies (e.g., spatter particles) apparent in the two sensors. Following construction of the build, the cylinders were subjected to XCT to identify internal flaws, and the resulting data have also been registered to the build plate coordinate system. Finally, 60 of the 64 cylinders were machined into fatigue coupons conforming to ASTM E466 and subsequently subjected to either high- or -low-cycle fatigue testing. The results of the fatigue tests have also been included in the dataset, and the XCT data corresponded to the approximate location of the gauge sections of the machine fatigue specimen geometry.

42 ENGINEERING↗

DOE OSTI2021

Effect of additives on carbon dioxide uptake and compressive strength of dry-cast concrete

The main thrust of the work reported herein is to study the effect of chemical additives to make beneficial use of carbon dioxide in enhancing the compressive strength of dry-cast concrete. The additives used in this investigation were calcium and magnesium oxides and silicates, nickel oxide, sodium hydroxide, sodium bicarbonate and strontium chloride. The experimental results showed that both the carbonation reactions and the compressive strength of dry-cast concrete mixtures were improved when using chemical additives. Experimental investigations for optimisation were also undertaken with selected additives to further increase the carbon dioxide uptake and improve the compressive strength. The best results were obtained when using calcium silicate in combination with calcium oxide. The early-age compressive strength of specimens made from the optimised mixture increased from 9·82 MPa to 13·32 MPa, and the specimens’ carbon dioxide uptake increased from 8·76% to 10·62% of cement weight.

Construction & Building Technology↗

DOE OSTI2016

Ionic Liquids as Multi-Functional Lubricant Additives to Enhance Engine Efficiency (final report NFE-12-03876)

This ORNL-Shell CRADA developed and investigated ionic liquids (ILs) as multifunctional additives for next-generation low-viscosity engine oils. Several groups of oil-miscible ILs were successfully designed and synthesized with high thermal stability, non-corrosiveness, excellent wettability, and most importantly effective anti-scuffing/anti-wear and friction reduction characteristics. Synergistic effects between the common anti-wear additive zinc dialkyldithiophosphate (ZDDP) and a particular group of ILs were discovered with > 30% friction reduction and 70% wear reduction compared with using ZDDP or IL alone. The IL+ZDDP tribofilm distinguishes itself from the IL or ZDDP tribofilms with substantially higher contents of metal phosphates but less metal oxides and sulfur compounds. Notably, it was revealed that the actual concentrations of functional elements on the droplet surface of the oil containing IL+ZDDP are one order magnitude higher than their nominal values. Such significantly increased concentrations of anti-wear agents are presumably expected for the oilsolid interface and believed to be responsible for the superior lubricating performance. A prototype SAE 0W-16 engine oil using a synergistic IL+ZDDP pair as the anti-wear additive has been formulated based on the compatibility between the IL and other additives. Sequence VIE full-scale engine dynamometer tests demonstrated fuel economy improvement (FEI) for this prototype oil and revealed the individual contributions from the lower oil viscosity and reduced boundary friction. The impact of IL and IL+ZDDP on exhaust emission catalyst was investigated using an accelerated small engine aging test and results were benchmarked against ZDDP.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2016

Assessment of Gasoline Additive Containing Ditert-butoxypropanol

The Fuels, Engines, and Emissions Research Center completed analysis and testing of the CPS Powershot gasoline additive under the auspices of the Department of Energy’s Technical Assistance for US Small Businesses in Vehicle Technologies. Gas chromatography-mass spectrometry (GC-MS) was used to quantify the makeup of the additive, finding a predominance of 2,3-Ditert-Butoxypropanol, also known as Glyceryl Di-Tert-Butyl Ether (GTBE). Blends of the additive at 2 and 4 volume percent were subjected to a number of standard ASTM tests, including Research Octane Number, Motor Octane Number, distillation, and vapor pressure. Results show a high boiling range and low vapor pressure for the additive, and a very modest octane boosting effect in gasoline with and without ethanol.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

CRADA/NFE-15-05761 Report: Additive Manufacturing of Isotropic NdFeB Bonded Permanent Magnets

The technical objective of this technical collaboration phase I proposal is to fabricate net shape isotropic NdFeB bonded magnets utilizing additive manufacturing technologies at the ORNL MDF. The goal is to form complex shapes of thermoplastic and/or thermoset bonded magnets without expensive tooling and with minimal wasted material. Two additive manufacturing methods; the binder jet process; and big area additive manufacturing (BAAM) were used. Binder jetting produced magnets with the measured density of the magnet of 3.47 g/cm 3 , close to 46% relative to the NdFeB single crystal density of 7.6 g/cm 3 were demonstrated. Magnetic measurements indicate that there is no degradation in the magnetic properties. In addition, BAAM was used to fabricate isotropic near-net-shape NdFeB bonded magnets with magnetic and mechanical properties comparable or better than those of traditional injection molded magnets. The starting polymer magnet composite pellets consist of 65 vol% isotropic NdFeB powder and 35 vol% polyamide (Nylon-12). The density of the final BAAM magnet product reached 4.8 g/cm 3 , and the room temperature magnetic properties are: Intrinsic coercivity Hci = 8.65 kOe, Remanence Br = 5.07 kG, and energy product (BH) max = 5.47 MGOe (43.50 kJ/m 3 ). This study provides a new pathway for preparing near-net shape bonded magnets for various magnetic applications.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Bio-reinforced composite development for additive manufacturing: Nanocellulose-PLA

Additive manufacturing (AM) is transitioning from being only a prototyping method towards becoming a manufacturing technique for the quick production of parts with complex geometries. For the complete realization of this transition, the mechanical properties of the printed parts have to meet the requirements of actual load-bearing structural components. Integration of a reinforcing second phase into a polymer is a viable approach for the improvement of resins mechanical performance. Addition of carbon fibers into acrylonitrile-butadiene-styrene (ABS) has already been shown to improve its mechanical properties compared to the neat ABS resin (both additively manufactured), and led to the manufacture of world s first 3D-printed car. However, both ABS resin and carbon fibers are petroleum-based products, and there is a continuous search for alternative, bio-sourced, renewable materials as a feedstock for manufacturing. Towards this direction, we have investigated the potential of cellulose nanofibril-reinforced polylactic acid (PLA) resin systems as an alternative. CNF-PLA composite systems with up to 40 wt% CNF loadings were prepared via compression molding technique and tested. Significant improvements in both tensile strength (80%) and elastic modulus (128%) were observed. Filaments prepared from the same compositions were also successfully 3D-printed into tensile testing specimens with up to 30% CNF concentrations, and showed similar improvements in mechanical performance. Although CNFs were not individually dispersed in PLA matrix, they were observed to be well blended with the polymer based on SEM micrographs. In summary, preparation and 3D-printing of a 100% bio-based feedstock material with the mechanical properties comparable to the carbon fiber-ABS system was successfully demonstrated that it can open up new window of opportunities in the additive manufacturing industry. Acknowledgement Research sponsored by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office, under contract DE-AC05-00OR22725 with UT-Battelle, LLC.

09 BIOMASS FUELS↗

DOE OSTI2018

Wire Arc Additive Manufacturing

Project highlight. This project designs and implements a new additive manufacturing capability at Savannah River National Laboratory. Wire Arc Additive Manufacturing is an Advanced Manufacturing technology that enables materials and energy savings by producing materials that are in near net shapes to minimize material losses compared to conventional forging and machining techniques. Wire arc additive manufacturing is an evolving technology that can be used to fabricate large components with significantly less materials waste than conventional processing. This project includes an engineering model, an aspect that is largely overlooked in the Additive Manufacturing modeling work where the emphasis has been on mechanistic and microscopic modeling, to estimate the residual stresses and distortions. The Abaqus Weld Interface software coupled with user subroutines in Fortran enable the local cooling rates to be estimated to provide a coarse scale model for the secondary dendrite arm spacing, a parameter useful to estimate mechanical properties.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Utility of Big Area Additive Manufacturing for Part Production for Low-Head Hydropower (CRADA NFE-18-07280 Final Report)

ORNL worked with Cadens, LLC, to explore the use of additive manufacturing (AM) to produce low-cost parts for low-head hydropower systems. Cadens develops design optimization software that leverages the flexible, low-cost, high-strength benefits of AM and composite materials. Cadens also operates a micro-hydro lab to test AM components in controlled environments. Until now, Cadens’ tests have been limited to components of a size that they can cost-effectively manufacture using local commercial systems. This project provided an opportunity for Cadens to scale up their modular AM hydropower parts using the capabilities of Big Area Additive Manufacturing (BAAM). This project was a success and resulted in the design and fabrication of several end-use parts of a hydropower system, using a Big Area Additive Manufacturing (BAAM) system. The fabricated parts include a draft tube, thimble, runner housing mold, PVC end fitting and two PVC pipe supports. In addition, a runner system was fabricated using fused deposition modeling on a 3D Platform Workbench 400 Series System.

13 HYDRO ENERGY↗

DOE OSTI2020

Feedstock Modification for Enhanced Additive Alloys

This project investigated the use of Y 2 O 3 nanoparticles to enhance IN625 feedstock for metal additive manufacturing. The oxide nanoparticles are adhered to the outer surface of the pre-alloyed IN625 powder feedstock, and serve to form an oxide dispersion strengthened (ODS) material in situ during processing. The conventional and enhanced feedstocks were processed using a laser powder bed fusion additive manufacturing (AM) system. The properties of the AM materials were characterized at elevated temperatures and compared to conventional wrought material. The addition of the Y 2 O 3 nanoparticles improved the yield strength, stress rupture, and corrosion properties of the AM material, and compared more favorably with conventional wrought IN625. This research will enable future adoption of additively manufactured ODS-IN625 components with superior properties to current printed IN625 material.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Development of a Multi-physics Model to Optimize Continuous Liquid Interface Production (CLIP) for Additive Manufacturing (Carbon3D HPC4Mfg Final Report)

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗

DOE OSTI2023

Analysis of Pitting Corrosion on Wrought and Additively Manufactured 316L Stainless Steel in Atmospheric Environments

Additive manufacturing of metal components enables rapid fabrication of complex geometries. However, metal additive manufacturing also introduces new morphological and microstructural characteristics which might be detrimental to component performance. Here we report the pitting corrosion properties of wrought and additively manufactured 316L stainless steel after atmospheric exposure to coastal environments and laboratory-created environments. Qualitative visualization in combination with quantitative analysis of resulting pits provided an in-depth understanding of pitting differences between wrought and additively manufactured 316L stainless steel and between coastal and laboratory-based exposure. Optical and scanning electron microscopy were utilized for visualization, while white light interferometry measured pits across approximately 5mm x 5mm areas on each sample. Post-processing of the interferometry data enables quantification of pitting attack for each sample in terms of both pit depth and pit volume. The pitting analysis introduced herein offers a new technique to compare pitting attack between different manufacturing processes and materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Wire Arc Additive Manufacturing of Lightweight High Pressure Die Casting Tooling

Oak Ridge National Laboratory (ORNL) and Mercury Marine partnered to develop and test methods for additively manufactured tooling for aluminum die casting applications under CRADA agreement NFE- 20-08193. Tooling is the largest capital expense for high production casting projects. The lead time for tooling is often measured in months with a typical project taking 9-12 months to realize Production Part Approval Process (PPAP) ready die cast samples. This project demonstrated the technical viability of rapidly produced steel components for high pressure die casting tooling via Wire Arc Additive Manufacturing (WAAM). A 410 stainless steel tool was redesigned and optimized with conformal cooling channels and additively manufactured. The finished tool was tested and used to produce over 4000 parts, which well surpassed expectations. A secondary objective was to evaluate the durability of multi-material additively manufactured (AM) components with conformal cooling. A large multi-material tool (H13 and 410SSNiMo) was manufactured using the same methods showing potential reductions in used material and cost. However, the H13 section sustained material cracking. Further analysis showed that the potential cause was the CTE mismatch of the two materials at higher temperatures. It is also suggested that the material mix can be used if the steel processing temperature does not exceed 600 ˚C. This project has shown high potential for using the WAAM technology for creating AM parts for aluminum dies casting. However, the multi-material approach requires extended study and tests.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Process–Property–Performance Mapping of Additively Manufactured 316H Stainless Steel Components

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development of advanced materials and components fabricated via additive manufacturing, and is using laser powder bed fusion (LPBF) of 316H stainless steel as an initial case study. In the previous fiscal year, miniature high-throughput specimens were printed on multiple LPBF systems to provide initial processing windows to minimize porosity and limit epitaxial grain growth during prints. This fiscal year, scaled builds were completed on three different LPBF systems at ORNL: a GE Concept Laser M2, a Renishaw AM400, and an EOS M290. Builds on the Concept Laser were conducted on multiple powder lots and processing parameter ranges to provide microstructure effects on time-independent and time-dependent mechanical properties. Builds on the Renishaw were produced using Oak Ridge National Laboratory (ORNL)-optimized printing parameters and Argonne National Laboratory (ANL)-optimized printing parameters to compare outcomes of parallel process optimization efforts at different national laboratories on the same LPBF system. Similarly, the build completed on the EOS M290 replicated the processing parameters of builds completed at Los Alamos National Laboratory (LANL). Optical microscopy and electron backscatter diffraction characterization was completed on all builds. In addition to the general round robin characterization, this work-package generated time-independent data, including tensile and fracture toughness test data on scaled Concept Laser builds as a function of processing parameters and post-build heat treatment. This analysis is complimentary to work in parallel work packages aiming to establish heat treatment and processing effects on time-dependent properties. It was found that although the stress-relief heat treatment provides the highest strength at lower-temperatures, tensile strength begins to converge at higher temperatures regardless of heat treatment condition. In addition, the more rigorous solution annealing and hot-isostatic pressing post-build heat treatments result in higher fracture toughness than the stress-relieved condition. The root-causes of the lower fracture toughness of the stress-relieved LPBF 316H material was informed via a stress-relief optimization study on a scaled concept laser print, where it was found that although dislocation recovery was largely complete after only a couple hours at 650°C, the extended hold of the current 24h heat treatment employed on scaled builds likely caused increased carbide volume fractions along the LPBF 316H grain boundaries, thereby deteriorating crack propagation resistance. This trend was seen to become more deleterious with additional increases of stress-relief temperature to 750°C or 850°C. These results have helped inform a new optimal stress-relief annealing condition for LPBF 316H for future campaign testing (650°C for 2h).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Process–Property–Performance Mapping of Additively Manufactured 316H Stainless Steel Components

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Novel Manufacturing Process of Lightweight Automotive Seats (Integration of Additive Manufacturing and Reinforced Polymer Composite)

Lightweight automotive seats offer multiple benefits to original equipment manufacturers in terms of cost savings from various aspects, including less material usage, more integrated processes, and compliance with Corporate Average Fuel Economy Standards. Original equipment manufacturers have been focusing on innovative ways to produce light weight automotive seats. The commercially available automotive seats are currently made of multiple metal components combined through welding and fasteners. The use of additive manufacturing and composite structures is particularly useful for light weighting the automotive components. Additive manufacturing (AM) offers multiple advantages over traditional manufacturing processes such as freedom of design thereby enabling complex structural geometries, mass customization and waste minimization, and control over the fiber alignment through deposition in a predetermined pattern. Combining metal inserts with polymer composites through a novel manufacturing process allows design of lightweight and high-performance materials for automotive components. However, fabricating these metal polymer composite structures through traditional manufacturing processes limits their mechanical properties due to limited design freedom, lack of control over fiber orientation in composite parts, and poor interfacial bonding between the constituent materials. It is essential to develop a novel manufacturing process to enable high throughput production of lightweight automotive seats using metal and polymer composites. As such it is important to design the automotive seat suitable for manufacturing via this process and perform mechanical characterization on various subcomponents of the seat to ensure that the design and performance requirements provided by the auto manufacturer are met. The aim of this project is to develop a novel manufacturing technique to produce lightweight automotive seat by combining AM with conventional manufacturing processes. The car seat back panel will be designed via topology optimization and numerical simulations to minimize the overall weight while ensuring it meets all the performance requirements. The optimization of the seat back structure will be based on computational stress analysis to maximize the stiffness and minimize the weight. Materials currently used by Ford Motor Company will be adopted for a few subcomponents while the in-house composite materials will be used for the rest of the seat back. The composite and metallic materials will be tested to determine their mechanical properties as these are necessary for simulations. A novel manufacturing process will be developed to integrate AM metal inserts with discontinuous reinforced composite through large scale additive manufacturing and compression overmolding processes. The developed manufacturing technique will be used to fabricated various subcomponents suitable for the seat back design and mechanically tested to determine their properties. The manufacturing of the lightweight seat back design through this process involves integrated AM metal inserts with the composite structure for recliner connection. The manufacturing of the entire seat back which is lightweight through the novel manufacturing process will be discussed. The performance of the designed seat back will be investigated through numerical simulations and shown to meet all the requirements provided by the auto manufacturer. The final goal of developing a novel manufacturing process for lightweight automotive seats is met through design optimization of seat back, manufacturing of subcomponents, mechanical characterization, and validation through numerical simulations. The routes to achieve the final goal of the project and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. The project resulted in the development of a novel manufacturing process to integrate metal inserts with tailored polymer composite preforms through overmolding. Leveraging this proven manufacturing process, a lightweight seat back was designed through topology optimization and numerical simulations. The designed seat back uses AM metal inserts and compression overmolding of tailored polymer composite preforms obtained via large scale additive manufacturing. The metal polymer composite structures fabricated through this process exhibited enhancement in stiffness and improved ductility upon testing. Overall, the project provided an alternative design and manufacturing technique for automotive seat back that enables weight saving while meeting the safety and performance requirements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗