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At least 1,063 records · Page 59

Structural, dielectric and magnetic studies of (x) Ni{sub 0.7}Co{sub 0.1}Cu{sub 0.2}Fe{sub 2}O{sub 4} + (1-x) BaTiO{sub 3} magnetoelectric composites

The Magneto-electric composites (x) Ni{sub 0.7}Co{sub 0.1}Cu{sub 0.2}Fe{sub 2}O{sub 4} + (1-x) BaTiO{sub 3} (x=10%, 20% and 30%) were synthesized by sintering mixtures of highly ferroelectric BaTiO{sub 3} (BT) and highly magneto-strictive component Ni{sub 0.7}Co{sub 0.1}Cu{sub 0.2}Fe{sub 2}O{sub 4} (NCCF). The presences of constituent phases in magneto-electric composites were probed by X-ray diffraction (XRD) studies. The peaks observed in the XRD spectrum indicated spinel cubic structure for NCCF ferrite phase and tetragonal perovskite structure for BT and, both spinel and pervoskite structures for synthesized ME composites. Surface morphology of the samples has been investigated using Field Emission Scanning Electron Microscope (FESEM). Frequency and composition dependent dielectric properties of synthesized composites were measured from 100 Hz to 1 MHz at room temperature using Hioki LCR Hi-TESTER. The dielectric dispersion is observed at lower frequencies for the synthesized ME composites. The hysteresis behavior was studied to understand the magnetic ordering in the synthesized composites using a Vibrating Sample Magnetometer (VSM). It is observed that the values of saturation magnetization increases along with the ferrite content.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A study of the oriented composites with the conductive segregated structure obtained via solid-phase processing of the UHMWPE reactor powder mixed with the carbon nanofillers

Electrically conductive oriented polymer nano-composites of different compositions, based on the reactor powder of ultra-high-molecular-weight polyethylene (UHMWPE) with a special morphology, filled with particles of nanostructured graphite (NG), multi-walled carbon nanotubes (MWCNTs), and electrically conductive carbon black (CB), were investigated. Polymer composites were obtained via compaction of the mechanical mixture of the polymer and filler powder, followed by uniaxial deformation of the material under homogeneous shear (HS) conditions (all of the processing stages were conducted at room temperature). Resulted composites possess a high tensile strength, high level of the electrical conductivity and low percolation threshold, owing it to the formation of the segregated conductive structure, The influence of the type of nanosized carbon filler, degree of the deformation under HS condition, temperature and etc. on the electrical conductivity and mechanical properties of strengthened conductive composites oriented under homogeneous shear conditions was investigated. Changes in the electrical conductivity of oriented composite materials during reversible “tension–shrinkage” cycles along the orientation axis direction were studied. A theoretical approach, describing the process of transformation of the conductive system as a response on polymer phase deformation and volume change, was proposed, based on the data received from the analysis of the conductivity behavior during the uniaxial deformation and thermal treatment of composites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Preparation of fine powdered composite for latent heat storage

Application of latent heat storage building envelope systems using phase-change materials represents an attractive method of storing thermal energy and has the advantages of high-energy storage density and the isothermal nature of the storage process. This study deals with a preparation of a new type of powdered phase change composite material for thermal energy storage. The idea of a composite is based upon the impregnation of a natural silicate material by a reasonably priced commercially produced pure phase change material and forming the homogenous composite powdered structure. For the preparation of the composite, vacuum impregnation method is used. The particle size distribution accessed by the laser diffraction apparatus proves that incorporation of the organic phase change material into the structure of inorganic siliceous pozzolana does not lead to the clustering of the particles. The compatibility of the prepared composite is characterized by the Fourier transformation infrared analysis (FTIR). Performed DSC analysis shows potential of the developed composite for thermal energy storage that can be easily incorporated into the cement-based matrix of building materials. Based on the obtained results, application of the developed phase change composite can be considered with a great promise.

36 MATERIALS SCIENCE↗

Experimental and statistical study on the effect of process parameters on the quality of continuous fiber composites made via additive manufacturing

Ongoing research in additive manufacturing towards structural and industrial application has led to the use of commingled roving as a manufacturing feedstock for printing high fiber volume fraction composites. The prospects of using this technology for high performance applications necessitates the need for a comprehensive experimental investigation into the effects of processing parameters on the quality of an additively manufactured composite printed from commingled roving feedstock. Here, in this work, transverse flexure and void fraction matrix pyrolysis testing are both performed to evaluate composite quality. The transverse flexure test is a testing approach that evaluates the quality of the interfacial fiber-matrix bond while the void fraction test estimates the void content in the printed composite. A full observational study consisting of 27 different test combinations is done to investigate the effects of three different process parameters namely, temperature, pressure, and print speed across three different levels. Composite samples were made from commingled roving of E-glass and amorphous PET using an in-house built continuous fiber composite digital manufacturing system. Least squares regression analysis is performed to study the main, interaction and quadratic effects of process parameters. A statistical regression model having an R2 adjusted value of 80.1% is generated from the transverse flexure study, which is used to explain main and interaction effects and also predict performance. Response surface plots are also generated and are used to optimize process parameters which can subsequently be of help in scaling up composite manufacturing. Results show that all three process parameters are highly statistically significant at the 0.01 level of significance. Pressure * Temperature and Pressure * Printspeed are significant interaction terms. Pressure plays a weightier role when print speed is increased or temperature is decreased as it closes more voids that would ordinarily have been introduced because of drop in polymer melt viscosity. Micrographic analysis is also performed.

36 MATERIALS SCIENCE↗

Radiation Tolerance and Mechanical Properties of Nanostructured Amorphous-Ceramic/Metal Composites

The objective of this work was to use a radically non-traditional approach to design amorphous-ceramic/metal composites for service in extreme irradiation environments. The project was built on a strong integration among four research teams for materials synthesis and characterization, ion irradiation, mechanical evaluation, and atomic scale modeling. Rather than try to prevent microstructure changes in polycrystalline aggregates, the research team worked to evolve composite systems where one of the constituents is intentionally synthesized in a non-crystalline or “amorphous” state. Because amorphous materials possess no translational symmetry, such alloys do not contain conventional crystal defects such as vacancies, interstitials, or dislocations. These materials offer the possibility of eliminating the root cause responsible for radiation damage in polycrystalline solids - namely the production of point defects and clusters thereof in collision cascades - and could serve as the basis for developing a new class of structural materials with unprecedented resistance to radiation. The amorphous alloys were used to develop advanced amorphous-ceramic/metal composites with greatly improved radiation tolerance and stability above 500oC, and improved mechanical performance by combining the good properties of amorphous materials (high strength and elastic limit) with those of crystalline materials (high toughness, strain hardening). The ceramic component of the composite consisted of a high crystallization temperature and radiation tolerant amorphous alloy composed of Si-O-C, silicon oxycarbide, while the metal layer was Fe and Fe(Cr), chosen to serve as model materials for steel. A prime hypothesis that drove this work is that the composite interface, together with the composite constituents, would provide significantly enhanced radiation tolerance, similar to or superior to those observed in metallic nanolayered structures, in a more engineering relevant material system. As our experimental data and modeling show, we have successfully developed a new class of ceramic/metal composites that can be adapted for engineering applications, thus significantly impacting improved materials performance for advanced nuclear reactors.

36 MATERIALS SCIENCE↗

Smart Composite Pressure Vessels (SCPV) with Integrated Health Monitoring

The U.S. Department of Energy (DOE) is promoting and developing more energy efficient and environmentally friendly technologies that will enable America to use less petroleum. Hydrogen fuel cells – which directly convert the chemical energy in hydrogen to electricity with only water and heat as byproducts – are a very attractive solution that can enable this to happen. To date, DOE's efforts have culminated in commercial demonstration of on-board vehicular hydrogen storage systems that can allow for a driving range of greater than 300 miles. This requires storing 5 Kgs of hydrogen onboard a light vehicle. In order to store this quantity of hydrogen, the hydrogen gas needs to be stored in a composite overwrapped pressure vessel (COPV) at a very high internal pressure. The objective of the program was to demonstrate continuous and predictable health-monitoring of composite pressure vessels. A higher confidence in the operational safety of the vessels will lead to reduced burst factor of safety imposed by regulatory standards and hence will help reduce the structural wall thickness that drives the cost of the vessel. Highly optimized Type III (metal lined) and Type IV (polymer lined) COPVs that are manufactured using filament winding process have been designed and qualified for the above mentioned application. However, the main structural component of the COPVs is carbon fiber and the high cost of carbon fiber composite in a pressure vessel is a primary challenge in reducing the cost of gaseous hydrogen storage. Continuous and remote monitoring of structural health of the COPVs as well as optimization of the strength translation of carbon fibers have the potential to allow for reduced factor of safety, thereby reduced amount of carbon and associated cost of the vessel. In the current program, the project team including Steelhead Composites (SHC), University of Tennessee, Knoxville (UTK), Teijin Carbon America, Oak Ridge National Laboratory (ORNL) and LUNA designed, fabricated, and tested smart composite pressure vessels with integrated sensors. Iterative loops of design and testing using coupons, subscale STEB vessels and full size vessels proved that a new generation of high performance carbon fiber can be used for efficient design of Type 3 vessels for H2 storage. Novel analysis techniques were developed to predict the initiation and propagation of interlaminar damage inside the composite shell due to impact damage, a real threat in practical operation. Such an analysis scheme is typically not used in tank design but is an essential tool for health monitoring of composite vessels. Remote sensing of the key signatures of the tank’s operating parameters such as pressure, acceleration and humidity was demonstrated using a unique device that can wirelessly transmit and stream the data to a remote server. Fiber optic sensors were successfully integrated during fabrication of the tanks. These sensors provide a wealth of information regarding the structural health of the vessel when it is subsequently pressurized or subjected to impact damage. Excellent correlation was demonstrated between the fiber optic sensor and mechanical strain gage data, and between the measurements and analytical predictions.

08 HYDROGEN↗

Self-healable Copolymer Composites for Extended Service H 2 Dispensing Hoses

In this project, we designed, synthesized and fabricated using X-winder technologies precommercialized novel, self-healingable commodity copolymer fiber-reinforced composites to extend the H 2 hose service life beyond the current target of 1000 fills. These studies demonstrated that these composites are able to withstand over 25,000 damage-repair cycles, which was the main objective of the proposed project, in the temperature range of -40 to +80 °C under variable pressures. When micro-cracks are formed after about 1,000 cycles/fueling per hose in the inner composite layer, these micro-cracks self-heal, thus extending the lifetime of a prototype inner layer of the hose. These composites were tested by exposure to H 2 fuel and demonstrated the ability to recover from mechanical damage. Thermomechanical testing combined with analysis of the stress and strain fields across the cross-section of the inner layer composite hoses also identified the ring-like stresses on the edge of inner layers arising from changes of the fiber winding angle directions from +45° to -45°. The developed novel concept that self-healing commodity copolymers can be used in the development of prototype composites for the extended service of H 2 dispensing hoses will have major implications for other energy-related technologies, where the extended service life in harsh environments is expected. In this project, we optimized, validated, and demonstrated novel copolymer fiber-reinforced composites for H 2 dispensing hose applications, which can be utilized in future manufacturing using commodity materials. The estimated cost of materials (exluding labor) is in the range of < $1.0/ft.

08 HYDROGEN↗

Compression Response of Silicone-Based Composites with Integrated Multifunctional Fillers

Polydimethylsiloxane (PDMS) is known for its exceptional mechanical properties, chemical stability, and flexibility. Recent advancements have focused on developing functional PDMS composites by integrating various functional fillers, including polymers, ceramics, and metals, for advanced applications such as electronics, medical devices, and aerospace. Consequently, there is a growing need to investigate PDMS composites to achieve higher filler loadings offering enhanced mechanical performance. This study addresses this need by utilizing the high molecular weight (MW) PDMS resin we have developed, offering its high elongation capacity of up to >6500%. We incorporated boron (B), hollow glass microballoons (HGMs), and tungsten-coated hollow glass microballoons (WHGMs) into the developed high MW PDMS. The resulting composites demonstrated excellent elastic properties and significant compression resilience (35–80%) and elastic modulus (1.28–10.15 MPa) at high filler loadings (~60 vol.%). Specifically, B/PDMS composites achieved up to 67.6 vol.% of B, HGM/PDMS composites held up to 68.6 vol.% of HGM, and WHGM/PDMS composites incorporated up to 54.0 vol.% of WHGM. These findings highlight the potential of high MW PDMS for developing high-performance PDMS composites suitable for advanced applications such as aerospace, automotive, and medical devices.

36 MATERIALS SCIENCE↗

Composites for Exploration Upper Stage

The Composites for Exploration Upper Stage (CEUS) was a 3-year, level III project within the Technology Demonstration Missions program of the NASA Space Technology Mission Directorate. Studies have shown that composites provide important programmatic enhancements, including reduced weight to increase capability and accelerated expansion of exploration and science mission objectives. The CEUS project was focused on technologies that best advanced innovation, infusion, and broad applications for the inclusion of composites on future large human-rated launch vehicles and spacecraft. The benefits included near- and far-term opportunities for infusion (NASA, industry/commercial, Department of Defense), demonstrated critical technologies and technically implementable evolvable innovations, and sustained Agency experience. The initial scope of the project was to advance technologies for large composite structures applicable to the Space Launch System (SLS) Exploration Upper Stage (EUS) by focusing on the affordability and technical performance of the EUS forward and aft skirts. The project was tasked to develop and demonstrate critical composite technologies with a focus on full-scale materials, design, manufacturing, and test using NASA in-house capabilities. This would have demonstrated a major advancement in confidence and matured the large-scale composite technology to a Technology Readiness Level 6. This project would, therefore, have bridged the gap for providing composite application to SLS upgrades, enabling future exploration missions.

composites↗

A Design Methodology for Optimizing and Integrating Composite Materials in Gear Structures

The application of composite materials to gear structures is complex because of the gear shape, the need for precise dimensional tolerances, and the complex dynamic load condition. Methods are presented in this work to design and optimize an integrated composite hub-web structure that can be used as part of a hybrid composite-steel gear. The composite hub-web structure is a planar structure with a large decrease in thickness from the hub to the rim. Methods for design and optimization of this variable-thickness structure are presented along with a method for forming braided prepreg material to conform to the shape of this structure. A layered approach is presented that integrates cut plies or filler materials for thickness buildup with continuous-fiber layers for the primary load path. An additional gear design concept is presented that has an axially extended continuous-fiber composite structure that can be combined with the planar structure. A proposed optimization methodology is introduced where an optimized design is output for each type of optimization simulation. Through this process, composite knowledge can be incorporated in the optimization, and more control is given over the design during the process. The methods in this study provide a tool for designing and optimizing composite structures for gears and other high-power-density applications.

optimization↗

NDE Methods and Capabilities Handbook - Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. Techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delaminations, voids, Automated Fiber Placement (AFP) defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability to the NDE community of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members is discussed.

Nondestructive Evaluation↗

NDE Methods and Capabilities Handbook - Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. Techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delaminations, voids, Automated Fiber Placement (AFP) defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency and limitations. This paper describes key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability to the NDE community of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members is discussed.

nondestructive evaluation↗

Tunable Piezoelectricity of Multifunctional Boron Nitride Nanotube/Poly(dimethylsiloxane) Stretchable Composites

Boron nitride nanotubes (BNNT) uniformly dispersed in stretchable materials, such as poly(dimethylsiloxane) (PDMS), could create the next generation of composites with augmented mechanical, thermal, and piezoelectric characteristics. This work reports tunable piezoelectricity of multifunctional BNNT/PDMS stretchable composites prepared via co-solvent blending with tetrahydrofuran (THF) to disperse BNNTs in PDMS while avoiding sonication or functionalization. The resultant stretchable BNNT/PDMS composites demonstrate augmented Young’s modulus (200% increase at 9 wt% BNNT) and thermal conductivity (120% increase at 9 wt% BNNT) without losing stretchability. Further-more, BNNT/PDMS composites demonstrate piezoelectric responses that are linearly proportional to BNNT wt%, achieving a piezoelectric constant (|d33|) of 18 pmV−1 at 9 wt% BNNT without poling, which is competitive with commercial piezoelectric polymers. Uniquely, BNNT/PDMS accommodates tensile strains up to 60% without plastic deformation by aligning BNNTs, which enhances the composites’ piezoelectric response approximately five times. Finally, the combined stretchable and piezoelectric nature of the composite was exploited to produce a vibration sensor sensitive to low-frequency (≈1 kHz) excitation. This is the first demonstration of multifunctional, stretchable BNNT/PDMS composites with enhanced mechanical strength and thermal conductivity and furthermore tunable piezoelectric response by varying BNNT wt% and applied strain, permitting applications in soft actuators and vibration sensors.

Boron Nitride Nanotubes, Polydimethylsiloxane, Pie↗

Micromechanics-based Modeling of Laminated SiC/SiC Ceramic Matrix Composites

The behavior and response of ceramic matrix composites (CMCs), in particular silicon carbide fiber reinforced silicon carbide matrix (SiC/SiC), is affected by many factors such as variation of fiber volume fraction, residual stresses resulting from processing of the composites at high temperature, random microstructures, and the presence of matrix flaws (e.g., voids, pores, cracks etc.) as well as general material nonlinearity and heterogeneity that occurs randomly in a composite. Residual stresses arising from the phase change of constituents are evaluated in this paper and it is shown that they do influence composite strength and need to be properly accounted for. Additionally, the microstructures (location of fiber centers, coating thickness etc.) of advanced CMCs are usually disordered (or random) and fiber diameter and strength typically have a distribution. They rarely resemble the ordered fiber packing (square, rectangular, or hexagonal) that is generally assumed in micromechanics-based models with periodic boundary conditions for computational expediency. These issues raise the question of how should one model such systems effectively? Can an ordered hexagonal packed repeating unit cell (RUC) accurately represent the random microstructure behavior? How many fibers need to be included to enable accurate representation? Clearly, the number of fibers within an RUC must be limited to insure a balance between accuracy and efficiency. NASA’s in-house micromechanics-based code MAC/GMC provides a framework to analyze such RUCs for the overall composite behavior and the FEAMAC computer code provides linkage of MAC/GMC to the commercial FEA code, ABAQUS. The appropriate level of discretization of the RUC as well as the analysis method employed, i.e., Generalized Method of Cells (GMC) or High Fidelity Generalized Method of Cells (HFGMC), is investigated in this paper in the context of a unidirectional as well as a cross-ply laminated CMC. Results including effective composite properties, proportional limit stress (an important design parameter) and fatigue are shown utilizing both GMC as well as HFGMC. Finally, a few multiscale analyses are performed on smooth bar test coupons as well as test coupons with features such as open-hole and double notches using FEAMAC. Best practices and guidance are provided to take these phenomena into account and keep a proper balance between fidelity (accuracy) and efficiency. Following these guidelines can account for important physics of the problem and provide significant advantages when performing large multiscale composite structural analyses.

Ceramic Matrix Composites↗

Structural Sizing of a Composite Transonic Truss-Braced Wing

Accurate finite element modeling (FEM) is a vital part of the modern aircraft design process. As aircraft become increasingly complex, the time-consuming nature of detailed FEM approaches comes at a significant cost to program timeline and budget. In an effort produce modeling efforts that are sufficiently accurate and minimally costly, a proposed FEM approach and optimization scheme for a composite aircraft is explored, including a discussion of the manufacturing constraints of a highly tailored composite panel design. A high-fidelity structural model of a transonic truss-braced wing (TTBW) is generated, and the components are sized by structural optimization to satisfy buckling and strength constraints while subjected to critical maneuver loads. The structural modeling approaches and sizing of a TTBW are discussed, including details for FEM approaches, verification of an approximated FEM approach, a sizing optimization using the optimization software LS-OPT, and a manufacturing trial of integrally stiffened composite panels conducted to explore the validity of highly tailored composites as a design consideration. The results of study discussed herein indicate that the proposed FEM approach is suitable for modeling composite-construction aircraft and for use in sizing optimization. Further efforts regarding integrally stiffened composite panels will indicate the suitability of this method for the integration of highly tailored composite panels into the design and optimization process, given the manufacturability of such panels as shown here.

Finite Element↗

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗