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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Predictive Engineering Tools for Injection-molded Long-Carbon-Fiber Thermoplastic Composites - FY 2014 Third Quarterly Report

This report describes the technical progresses made during the third quarter of FY 2014: 1) Autodesk introduced the options for fiber inlet condition to the 3D solver. These options are already available in the mid-plane/dual domain solver. 2) Autodesk improved the accuracy of 3D fiber orientation calculation around the gate. 3) Autodesk received consultant services from Prof. C.L. Tucker at the University of Illinois on the implementation of the reduced order model for fiber length, and discussed with Prof. Tucker the methods to reduce memory usage. 4) PlastiComp delivered to PNNL center-gated and edge-fan-gated 20-wt% to 30-wt% LCF/PP and LCF/PA66 (7”x7”x1/8”) plaques molded by the in-line direct injection molding (D-LFT) process. 5) PlastiComp molded ASTM tensile, flexural and impact bars under the same D-LFT processing conditions used for plaques for Certification of Assessment and ascertaining the resultant mechanical properties. 6) Purdue developed a new polishing routine, utilizing the automated polishing machine, to reduce fiber damage during surface preparation. 7) Purdue used a marker-based watershed segmentation routine, in conjunction with a hysteresis thresholding technique, for fiber segmentation during fiber orientation measurement. 8) Purdue validated Purdue’s fiber orientation measurement method using the previous fiber orientation data obtained from the Leeds machine and manually measured data by the University of Illinois. 9) PNNL conducted ASMI mid-plane analyses for a 30wt% LCF/PP plaque and compared the predicted fiber orientations with the measured data provided by Purdue University at the selected locations on this plaque. 10) PNNL put together the DOE 2014 Annual Merit Review (AMR) presentation with the team and presented it at the AMR meetings on June 17, 2014. 11) PNNL built ASMI dual domain models for the Toyota complex part and commenced mold filling analyses of the complex part with different wall thicknesses in order to support part molding. 12) Toyota and Magna discussed with PNNL on tool modification for molding the complex part. Toyota sent the CAD files of the complex part to PNNL to build ASMI models of the part for mold filling analysis to provide guidance to tooling and part molding.

Injection molding, long-fiber thermoplastic, carbo↗
DOE OSTI2015

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites - FY 2015 First Quarterly Report

During the first quarter of FY 2015, the following technical progress has been made toward project milestones: 1) Autodesk delivered a new research version of ASMI to PNNL. This version includes the improved 3D fiber orientation solver, and the reduced order model (ROM) for fiber length distribution using the proper orthogonal decomposition (POD) implemented in the mid-plane, dual-domain and 3D solvers. 2) Autodesk coordinated a conference paper with PNNL reporting ASMI mid-plane fiber orientation predictions compared with the measured data for two PlastiComp plaques. This paper was accepted for presentation at the 2015 Society for Plastics Engineers (SPE) ANTEC conference. 3) The University of Illinois (Prof. Tucker) assisted team members from Purdue with fiber orientation measurement techniques, including interpretation of off-axis cross sections. 4) The University of Illinois assisted Autodesk team members with software implementation of the POD approach for fiber length modeling, and with fiber orientation modeling. 5) The University of Illinois co-authored in the SPE ANTEC paper, participated with the team in discussions of plaque data and model results, and participated in the definition of go/no-go experiments and data. 6) Purdue University (Purdue) conducted fiber orientation measurements for 3 PlastiComp plaques: fast-fill 30wt% LCF/PP center-gated, fast-fill 50wt% LCF/PA66 edge-gated and fast-fill 50wt% LCF/PA66 center-gated plaques, and delivered the fiber orientation data for these plaques at the selected locations (named A, B, and C) to PNNL. However, the data for the fast-fill 50wt% LCF/PA66 edge-gated plaque exhibited unusual variations and could not be used for the model validation. Purdue will re-measure fiber orientation for this plaque. 7) Based on discussions with the University of Illinois Purdue explained the ambiguity in the measurements of the fiber orientation components. 8) PNNL discussed with team members to establish a go/no-go decision plan for the project and submitted the established plan to DOE. 9) PNNL performed ASMI mid-plane analyses for the fast-fill center-gated 30wt% LCF/PP and 50wt% LCF/PA66 plaques and compared the predicted fiber orientations with the measured data provided by Purdue at Locations A, B, and C on these plaques. 10) Based on discussions with the University of Illinois and Autodesk, PNNL proposed a procedure to adjust fiber orientation data for Location A of the center-gated plaques so that the data can be expressed and interpreted in the flow/cross-flow direction coordinate system. 11) PNNL tested the new ASMI version received from Autodesk, examined and discussed 3D fiber orientation predictions for PlastiComp plaques. 12) PlastiComp, Inc. (PlastiComp), Toyota Research Institute North America (Toyota) and Magna Exteriors and Interiors Corp. (Magna) participated in discussions with team members on the go/no-go plan and the issues related to fiber length measurements. Toyota continued the discussion with Magna on tool modification for molding the complex part in order to achieve the target fiber length in the part.

42 ENGINEERING↗
DOE OSTI2015

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites - Second FY 2015 Quarterly Report

During the second quarter of FY 2015, the following technical progress has been made toward project milestones: 1) Autodesk reviewed 3D fiber orientation distribution (FOD) comparisons and provided support on improving accuracy. 2) Autodesk reviewed fiber length distribution (FLD) data comparisons and provided suggestions, assisted PNNL in FOD and FLD parameter settings optimization, and advised PNNL on appropriate through thickness thermal conductivity for improved frozen layer effect on FOD predictions. Autodesk also participated in project review meetings including preparations and discussions towards passing the go/no-go decision point. 3) Autodesk implemented an improved FOD inlet profile specification method through the part thickness for 3D meshes and provided an updated ASMI research version to PNNL. 4) The University of Illinois (Prof. C.L. Tucker) provided Autodesk with ideas to improve fiber orientation modeling 5) Purdue University re-measured fiber orientation for the fast-fill 50wt% LCF/PA66 edge-gated plaque, and delivered the fiber orientation data for this plaque at the selected locations (named A, B, and C, Figure 1) to PNNL. Purdue also re-measured fiber orientation for locations A on the fast-fill 30wt% LCF/PP and 50wt% LCF/PA66 center-gated plaques, which exhibited anomalous fiber orientation behavior. 6) Purdue University conducted fiber length measurements and delivered the length data to PNNL for the purge materials (slow-fill 30wt% LCF/PP and 30wt% LCF/PA66 purge materials) and PlastiComp plaques selected on the go/no-go list for fiber length model validation (i.e., slow-fill edge-gated 30wt% LCF/PP and 30wt% LCF/PA66 plaques, Locations A, B, and C). 7) PNNL developed a method to recover intact carbon fibers from LCF/PA66 materials. Isolated fibers were shipped to Purdue for length distribution analysis. 8) PNNL completed ASMI mid-plane analyses for all the PlastiComp plaques defined on the go/no-go list for fiber orientation (FO) model validation and compared the predicted fiber orientations with the measured data provided by Purdue at Locations A, B, and C on these plaques. The 15% accuracy criterion based on evaluation of tensile and bending stiffness was used to assess the accuracy in fiber orientation predictions. 9) PNNL completed ASMI mid-plane analyses for all the PlastiComp plaques defined on the go/no-go list for fiber length distribution (FLD) model validation and compared the predicted length distributions with the measured data provided by Purdue at Locations A, B, and C on these plaques. The 15% accuracy criterion based on evaluation of tensile and bending stiffness was used to assess the accuracy in fiber orientation predictions. 10) PNNL tested the new ASMI version received from Autodesk in March 2015, examined and discussed 3D fiber orientation predictions for PlastiComp plaques. 11) PlastiComp, Inc. (PlastiComp), Toyota Research Institute North America (Toyota) and Magna Exteriors and Interiors Corporation (Magna) participated in discussions with team members on the go/no-go plan. Toyota continued the discussion with Magna on tool modification for molding the complex part in order to achieve the target fiber length in the part.

42 ENGINEERING↗
DOE OSTI2015

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites (FY 2015 Third Quarterly Report)

During the third quarter of FY 2015, the following technical progress has been made toward project milestones: 1) Magna oversaw the tool build and prepared the molding plan for the complex part of Phase II. 2) PlastiComp hosted a visit by Magna and Toyota on April 23rd to finalize the molding scope and schedule. The plan for molding trials including selection of molding parameters for both LFT and D-LFT for the U-shape complex part was established. 3) Toyota shipped the U-shape complex part tool to Magna on May 28th, 2015. 4) Plasticomp provided 30wt% LCF/PP and 30wt% LCF/PA66 compounded pellets to Magna for molding the complex part. 5) Magna performed preliminary molding trials on June 2nd, 2015 to validate wall thickness, fill profile, tool temperature and shot size requirements for the complex part. 6) Magna performed the first complex part run on June 16th and 17th, 2015 at Magna’s Composite Centre of Excellence in Concord, ON, Canada. Dale Roland of Plasticomp, and Umesh Gandhi of Toyota also attended the molding. 7) Magna discussed and finalized the plan with PNNL and the team for cutting samples from molded parts at selected locations for fiber orientation and length measurements. 8) Magna provided the computer-aided design (CAD) files of the complex parts with and without ribs to PNNL and Autodesk to build the corresponding ASMI models for injection molding simulations. Magna also provided the actual parameters used. 9) Plasticomp’s provided knowledge and experience of molding LCF materials essential to the successful molding of the parts including optimization of fill speed, tool temperatures, and plasticizing conditions for the 30wt% LCF/PP and 30wt% LCF/PA66 materials in both rib and non-rib versions. 10) Magna molded additional parts for evaluation of mechanical property testing including torsional stiffness on June 29th and 30th, 2015 at Magna’s Composite Center of Excellence. 11) Toyota began preparation for the torsion test of the specimens. Preparation of a computer-aided engineering (CAE) model to predict the performance is in progress. 12) Autodesk fixed an error in the implementation of the proper orthogonal decomposition (POD) calculation of fiber length that had caused the ASMI solution to crash and provided an updated build of ASMI containing the fix. 13)Autodesk reviewed and provided feedback for the complex part molding and measurement locations. 14) Autodesk provided support to set up the workflow for ASMI-ABAQUS® analysis, and provided a fix and workaround for a bug in the ASMI-ABAQUS® output command. 15) Autodesk helped build ASMI analysis models for the complex parts with and without ribs. 16) Autodesk worked on improving the orientation prediction accuracy in the shearing layer for 3D meshes based on comparison to measured data of the plaque moldings. 17) PNNL installed a new ASMI version received from Autodesk and performed comparative analyses to assess mid-plane versus 3D fiber length predictions using the full fiber length model and the reduced-order model (ROM) using POD. 18) PNNL presented the project scope, accomplishments, significant results and future plans to DOE and the USCAR Materials Tech Team on June 3rd, 2015. 19) PNNL discussed the cutting of samples from molded parts and finalized a plan with Magna and the team suggesting the sample size, locations and number of samples per location. 20) PNNL and Autodesk built ASMI models for the complex parts with and without ribs, and preliminary analyses of the part with ribs were conducted using the actual molding parameters received from Magna. 21) PNNL worked on a procedure to extract fiber orientation and length results from a 3D ASMI analysis to a 3D ABAQUS model. This procedure is essential to import ASMI fiber orientation and length to a 3D ABAQUS model of the part allowing future part structural analysis for weight reduction study.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites - FY 2016 First Quarterly Report

During the first quarter of FY 2016, the following technical progress has been made toward project milestones: 1) Virginia Tech completed fiber orientation (FO) measurements for the samples taken at Locations A, B, C and D (Figure 1) from the 30wt% LCF/PP and 30wt% LCF/PA66 ribbed and non-ribbed complex parts using Virginia Tech’s established procedure. Virginia Tech delivered to PNNL all the measured fiber orientation data for validating ASMI fiber orientation predictions. 2)Virginia Tech performed fiber length distribution (FLD) measurements for the samples taken at Locations A, B, C and D from these complex parts using Virginia Tech’s established procedure. Virginia also re-assessed previous data and measured fiber length distributions in the corresponding nozzle purging materials and delivered to PNNL all the measured length data for validating ASMI fiber length predictions. 3)Based on measured fiber orientation data, Autodesk identified the parameters of the anisotropic rotary diffusion reduced strain closure (ARD-RSC) model [1] and provided PNNL with the values of these parameters that were used in ASMI analyses of the complex parts. 4) Magna provided Virginia Tech with additional samples cut out from the 30wt% LCF/PP and 30wt% LCF/PA66 ribbed parts (Figure 1) for fiber length and orientation measurements. 5) In discussion with Autodesk, PNNL performed 3D ASMI analyses of the 30wt% LCF/PP and 30wt% LCF/PA66 ribbed and non-ribbed complex parts to predict fiber orientations and length distributions in these parts. The issues observed through the analyses regarding fiber orientation distributions profiles and abnormal length distributions were reported to Autodesk. Autodesk is working to resolve these issues. 6) PNNL completed 3D ASMI analyses of the complex parts and compared predicted fiber orientation results at Locations A, B, and C on the non-ribbed parts, and at Locations A, B, C and D on the ribbed parts with the corresponding measured data. PNNL also evaluated the within-15%-agreement criterion using the principal tensile and flexural moduli computed based on predicted vs. measured fiber orientation results. 7) PNNL developed and discussed with Toyota, Magna and PlastiComp a method to perform weight and cost reduction for making the 30wt% LCF/PA66 ribbed part through comparative three-point bending simulations of this part and of similar parts in steel.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites - FY 2014 Fourth Quarterly Report

During the last quarter of FY 2014, the following technical progress has been made toward project milestones: 1) Autodesk, Inc. (Autodesk) has implemented a new fiber length distribution (FLD) model based on an unbreakable length assumption with Reduced Order Modeling (ROM) by the Proper Orthogonal Decomposition (POD) approach in the mid-plane, dual-domain and 3D solvers. 2) Autodesk improved the ASMI 3D solver for fiber orientation prediction using the anisotropic rotary diffusion (ARD) – reduced strain closure (RSC) model. 3) Autodesk received consultant services from Prof. C.L. Tucker at the University of Illinois on numerical simulation of fiber orientation and fiber length. 4) PlastiComp, Inc. (PlastiComp) suggested to Purdue University a procedure for fiber separation using an inert-gas atmosphere in the burn-off furnace. 5) Purdue University (Purdue) hosted a face-to-face project review meeting at Purdue University on August 6-7, 2014. 6) Purdue conducted fiber orientation measurements for 3 PlastiComp plaques: fast-fill 30wt% LCF/PP edged-gated, slow-fill 50wt% LCF/PP edge-gated, and slow-fill 50wt% LCF/PP center-gated plaques, and delivered the orientation data for these plaques at the selected locations (named A, B, and C) to PNNL. 7) PNNL conducted ASMI mid-plane analyses for the above PlastiComp plaques and compared the predicted fiber orientations with the measured data provided by Purdue at Locations A, B, and C on these plaques. 8) PNNL planned the project review meeting (August 6-7, 2014) with Purdue. 9) PNNL performed ASMI analyses for the Toyota complex parts with and without ribs, having different wall thicknesses, and using the PlastiComp 50wt% LCF/PP, 50wt% LCF/PA66, 30wt% LCF/PP, and 30wt% LCF/PA66 materials to provide guidance for tool design and modifications needed for molding these parts. 10) Magna Exteriors and Interiors Corp. (Magna) molded plaques from the 50% LCF/PP and 50% LCF/PA66 materials received from Plasticomp in order to extract machine purgings (purge materials) from Magna’s 200-Ton Injection Molding machine targeted to mold the complex part. 11) Toyota and Magna discussed with PNNL tool modification for molding the complex part.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

High Energy Dynamic Impact Testing of APC AS4/PEKK-FC and TC1225 LMPAEK T700G Thermoplastic Composite Materials

High energy dynamic impact tests were conducted on Solvay APC AS4D/PEKK-FC and Toray TC1225 LMPAEK T700Gthermoplastic composite laminates. The primary objective was to provide data for evaluation of computational composite impact models. Empirical results indicate an approximately 50% increase in penetration threshold velocity and over 100% increase in penetration energy threshold for the TC1225 LMPAEK T700Gcomposite compared to the APC AS4D/PEKK-FC composite. The velocity required to produce NDE-detectable delamination in the TC1225 LMPAEK T700Gcomposite was roughly twice that for the APC AS4D/PEKK-FC composite. Comparison of the normalized energy absorption showed similar results for the APC AS4D/PEKK-FC system compared to a previously studied IM7/8552 composite material. The TC1225 LMPAEK T700Gsystem absorbed approximately twice that of the other two systems when normalized by areal weight.

Impact↗
DOE OSTI2023

Effect of Molecular Weight on the Morphology of a Polymer Semiconductor–Thermoplastic Elastomer Blend

Abstract Polymer semiconductors (PSCs) are essential active materials in mechanically stretchable electronic devices. However, many exhibit low fracture strain due to their rigid chain conformation and the presence of large crystalline domains. Here, a PSC/elastomer blend, poly[((2,6‐bis(thiophen‐2‐yl)‐3,7‐bis(9‐octylnonadecyl)thieno[3,2‐b]thieno[2′,3′:4,5]thieno[2,3‐d]thiophene)‐5,5′‐diyl)(2,5‐bis(8‐octyloctadecyl)‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4‐dione)‐5,5′‐diyl]] (P2TDPP2TFT4) and polystyrene‐ block ‐poly(ethylene‐ran‐butylene)‐ block ‐polystyrene (SEBS) are systematically investigated. Specifically, the effects of molecular weight of both SEBS and P2TDPP2TFT4 on the resulting blend morphology, mechanical, and electrical properties are explored. In addition to commonly used techniques, atomic force microscopy‐based nanomechanical images are used to provide additional insights into the blend film morphology. Opposing trends in SEBS‐induced aggregation are observed for the different P2TDPP2TFT4 molecular weights upon increasing the SEBS molecular weight from 87 to 276 kDa. Furthermore, these trends are seen in device performance trends for both molecular weights of P2TDPP2TFT4. SEBS molecular weight also has a substantial influence on the mesoscale phase separation. Strain at fracture increases dramatically upon blending, reaching a maximum value of 640% ± 20% in the blended films measured with film‐on‐water method. These results highlight the importance of molecular weight for electronic devices. In addition, this study provides valuable insights into appropriate polymer selections for stretchable semiconducting thin films that simultaneously possess excellent mechanical and electrical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Thermoplasticity and strain localization in transversely isotropic materials based on anisotropic critical state plasticity

Geomaterials including soils and rocks are inherently anisotropic and sensitive to temperature changes caused by various internal and external processes. They are also susceptible to strain localization in the form of shear bands when subjected to critical loads. In this paper, we present a thermo-plastic framework for modeling coupled thermo-mechanical response and for predicting the inception of a shear band in a transversely isotropic material using the general framework of critical state plasticity and the specific framework of an anisotropic modified Cam-Clay model. The formulation incorporates anisotropy in both elastic and plastic responses under the assumption of infinitesimal deformation. The model is first calibrated using experimental data from triaxial tests to demonstrate its capability in capturing anisotropy in the mechanical response. Subsequently, stress-point simulations of strain localization are carried out under two different conditions, namely, isothermal localization and adiabatic localization. The adiabatic formulation investigates the effect of temperature on localization via thermo-mechanical coupling. Numerical simulations are presented to demonstrate the important role of anisotropy, hardening, and thermal softening on strain localization inception and orientation.

36 MATERIALS SCIENCE↗