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At least 361 records · Page 20

Terahertz Tools Advance Imaging for Security, Industry

Picometrix, a wholly owned subsidiary of Advanced Photonix Inc. (API), of Ann Arbor, Michigan, invented the world s first commercial terahertz system. The company improved the portability and capabilities of their systems through Small Business Innovation Research (SBIR) agreements with Langley Research Center to provide terahertz imaging capabilities for inspecting the space shuttle external tanks and orbiters. Now API s systems make use of the unique imaging capacity of terahertz radiation on manufacturing floors, for thickness measurements of coatings, pharmaceutical tablet production, and even art conservation.

Source record↗

External Payload Carrier (XPC) A Suborbital Research Platform

This slide presentation details the concept of an External Payload Carrier (XPC), that can fly on ann unused Solid Rocket Booster (SRB) location on the Atlas V rocket to suborbital environment. The XPC can be used anytime there is sufficient excess lift capability available. The dimensions and possible uses of the XPC are reviewed. The completed Phase 1 study reviewed 57 variations, and arrived at three viable configurations, identified design baselines, subsystems and preliminary testing requirements. Phase II effort is planned to produce the preliminary design (i.e., PDR level), Systems Requirements Document (SRD), identify flight candidates, develop schedule and funding profiles, and identify the risk-reduction activities.

Schallhorn, Paul↗

Preface: International Reference Ionosphere - Progress in Ionospheric Modelling

The international reference ionosphere (lRI) is the internationally recommended empirical model for the specification of ionospheric parameters supported by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) and recognized by the International Standardization Organization (ISO). IRI is being continually improved by a team of international experts as new data become available and better models are being developed. This issue chronicles the latest phase of model updates as reported during two IRI-related meetings. The first was a special session during the Scientific Assembly of the Committee of Space Research (COSPAR) in Montreal, Canada in July 2008 and the second was an IRI Task Force Activity at the US Air Force Academy in Colorado Springs in May 2009. This work led to several improvements and additions of the model which will be included in the next version, IRI-201O. The issue is divided into three sections focusing on the improvements made in the topside ionosphere, the F-peak, and the lower ionosphere, respectively. This issue would not have been possible without the reviewing efforts of many individuals. Each paper was reviewed by two referees. We thankfully acknowledge the contribution to this issue made by the following reviewers: Jacob Adeniyi, David Altadill, Eduardo Araujo, Feza Arikan, Dieter Bilitza, Jilijana Cander, Bela Fejer, Tamara Gulyaeva, Manuel Hermindez-Pajares, Ivan Kutiev, John MacDougal, Leo McNamara, Bruno Nava, Olivier Obrou, Elijah Oyeyemi, Vadym Paznukhov, Bodo Reinisch, John Retterer, Phil Richards, Gary Sales, J.H. Sastri, Ludger Scherliess, Iwona Stanislavska, Stamir Stankov, Shin-Yi Su, Manlian Zhang, Y ongliang Zhang, and Irina Zakharenkova. We are grateful to Peggy Ann Shea for her final review and guidance as the editor-in-chief for special issues of Advances in Space Research. We thank the authors for their timely submission and their quick response to the reviewer comments and humbly apologize for any delays in the editing process.

Bilitza Dieter↗

Thin Films Protect Electronics from Heat and Radiation

While Anne St. Clair worked on high performance polyimides at Langley Research Center, she noticed that some of the films were nearly colorless. The polyimides became known as LaRC-CP1 and LaRC-CP2, and were licensed by NeXolve Corporation, based in Huntsville, Alabama. Today, NeXolve provides polyimide film products to commercial customers for spacecraft, telescopes, and circuit boards.

Source record↗

Micro-Accelerometers Monitor Equipment Health

Glenn Research Center awarded SBIR funding to Ann Arbor, Michigan-based Evigia Systems to develop a miniaturized accelerometer to account for gravitational effects in space experiments. The company has gone on to implement the technology in its suite of prognostic sensors, which are used to monitor the integrity of industrial machinery. As a result, five employees have been hired.

Source record↗

Sound Modeling Simplifies Vehicle Noise Management

Under two SBIR contracts with Langley Research Center, Ann Arbor, Michigan-based Comet Technology Corporation developed Comet EnFlow, a software program capable of predicting both high- and low-frequency noise and vibration behavior in plane fuselages and other structures. The company now markets the software to airplane, automobile, and ship manufacturers, and Langley has found an unexpected use for it in leak detection on the International Space Station.

Source record↗

Aeroelastic Airworthiness Assesment of the Adaptive Compliant Trailing Edge Flaps

The Adaptive Compliant Trailing Edge (ACTE) demonstrator is a joint task under the National Aeronautics and Space Administration Environmentally Responsible Aviation Project in partnership with the Air Force Research Laboratory and FlexSys, Inc. (Ann Arbor, Michigan). The project goal is to develop advanced technologies that enable environmentally friendly aircraft, such as adaptive compliant technologies. The ACTE demonstrator flight-test program encompassed replacing the Fowler flaps on the SubsoniC Aircraft Testbed, a modified Gulfstream III (Gulfstream Aerospace, Savannah, Georgia) aircraft, with control surfaces developed by FlexSys. The control surfaces developed by FlexSys are a pair of uniquely-designed unconventional flaps to be used as lifting surfaces during flight-testing to validate their structural effectiveness. The unconventional flaps required a multidisciplinary airworthiness assessment to prove they could withstand the prescribed flight envelope. Several challenges were posed due to the large deflections experienced by the structure, requiring non-linear analysis methods. The aeroelastic assessment necessitated both conventional and extensive testing and analysis methods. A series of ground vibration tests (GVTs) were conducted to provide modal characteristics to validate and update finite element models (FEMs) used for the flutter analyses for a subset of the various flight configurations. Numerous FEMs were developed using data from FlexSys and the ground tests. The flap FEMs were then attached to the aircraft model to generate a combined FEM that could be analyzed for aeroelastic instabilities. The aeroelastic analysis results showed the combined system of aircraft and flaps were predicted to have the required flutter margin to successfully demonstrate the adaptive compliant technology. This paper documents the details of the aeroelastic airworthiness assessment described, including the ground testing and analyses, and subsequent flight-testing performed on the unconventional ACTE flaps.

aeroelasticity↗

Aeroelastic Response of the Adaptive Compliant Trailing Edge Transtition Section

The Adaptive Compliant Trailing Edge demonstrator was a joint task under the Environmentally Responsible Aviation Project in partnership with the Air Force Research Laboratory and FlexSys, Inc. (Ann Arbor, Michigan), chartered by the National Aeronautics and Space Administration to develop advanced technologies that enable environmentally friendly aircraft, such as continuous mold-line technologies. The Adaptive Compliant Trailing Edge demonstrator encompassed replacing the Fowler flaps on the SubsoniC Aircraft Testbed, a Gulfstream III (Gulfstream Aerospace, Savannah, Georgia) aircraft, with control surfaces developed by FlexSys, Inc., a pair of uniquely-designed, unconventional flaps to be used as lifting surfaces during flight-testing to substantiate their structural effectiveness. The unconventional flaps consisted of a main flap section and two transition sections, inboard and outboard, which demonstrated the continuous mold-line technology. Unique characteristics of the transition sections provided a challenge to the airworthiness assessment for this part of the structure. A series of build-up tests and analyses were conducted to ensure the data required to support the airworthiness assessment were acquired and applied accurately. The transition sections were analyzed both as individual components and as part of the flight-test article assembly. Instrumentation was installed in the transition sections based on the analysis to best capture the in-flight aeroelastic response. Flight-testing was conducted and flight data were acquired to validate the analyses. This paper documents the details of the aeroelastic assessment and in-flight response of the transition sections of the unconventional Adaptive Compliant Trailing Edge flaps.

ground vibration test↗

Evaluation of Load Analysis Methods for NASAs GIII Adaptive Compliant Trailing Edge Project

The Air Force Research Laboratory (AFRL), NASA Armstrong Flight Research Center (AFRC), and FlexSys Inc. (Ann Arbor, Michigan) have collaborated to flight test the Adaptive Compliant Trailing Edge (ACTE) flaps. These flaps were installed on a Gulfstream Aerospace Corporation (GAC) GIII aircraft and tested at AFRC at various deflection angles over a range of flight conditions. External aerodynamic and inertial load analyses were conducted with the intention to ensure that the change in wing loads due to the deployed ACTE flap did not overload the existing baseline GIII wing box structure. The objective of this paper was to substantiate the analysis tools used for predicting wing loads at AFRC. Computational fluid dynamics (CFD) models and distributed mass inertial models were developed for predicting the loads on the wing. The analysis tools included TRANAIR (full potential) and CMARC (panel) models. Aerodynamic pressure data from the analysis codes were validated against static pressure port data collected in-flight. Combined results from the CFD predictions and the inertial load analysis were used to predict the normal force, bending moment, and torque loads on the wing. Wing loads obtained from calibrated strain gages installed on the wing were used for substantiation of the load prediction tools. The load predictions exhibited good agreement compared to the flight load results obtained from calibrated strain gage measurements.

Aerodynamic Loads↗

Status, Emerging Ideas and Future Directions of Turbulence Modeling Research in Aeronautics

In July 2017, a three-day Turbulence Modeling Symposium sponsored by the University of Michigan and NASA was held in Ann Arbor, Michigan. This meeting brought together nearly 90 experts from academia, government and industry, with good international participation, to discuss the state of the art in turbulence modeling, emerging ideas, and to wrestle with questions surrounding its future. Emphasis was placed on turbulence modeling in a predictive context in complex problems, rather than on turbulence theory or descriptive modeling. This report summarizes many of the questions, discussions, and conclusions from the symposium, and suggests immediate next steps.

Duraisamy, Karthik↗

Kinetic Damage from Meteorites

Ballistic (kinetic energy) damage from falling meteorites has been recorded in two cases: the 1954 Sylacuga, Alabama meteorite of 4 kilogram mass which indirectly hit Ann Hodges and the 1992 Mbale meteorite fall where a 4 gram-sized meteorite struck a young boy. Neither event was fatal. Structures damaged by meteorites are much more common and include mail boxes (Figure 1) and cars (Figure2). Figure 3 shows that meteorite fragments of order 0.1 kilograms may cause serious human injury/fatality. Halliday et al (1985) estimated a human is struck once per decade by a meteorite (most likely gram-sized) while more than a dozen structures should be impacted annually by meteorite fragments.

Cooke, W.↗

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to find optimal designs for an interdigitated flushwall injector suitable for scramjet applications at hypervelocity conditions. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. A Latin hypercube sampling design-of-experiments method was used to select design points for RAS. A methodology was developed that automated building geometries and generating grids for each design. The ensuing RAS analysis generated the performance database from which the two objective functions of interest were computed using a one-dimensional performance utility. The data were fitted using four surrogate models: an artificial neural network (ANN) model, a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model obtained an optimal solution set that predicted high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts are required in order to lower the errors and perform more accurate surrogate-based optimization. sed optimization.

Shenoy, Rajiv R.↗

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗

Data-Driven Turbulence Modeling: Summary and Outcomes of the 2022 NASA Symposium

A three-day symposium sponsored by NASA was held in July 2022 in Suffolk, Virginia on the subject of Turbulence Modeling: Roadblocks, and the Potential for Machine Learning. This meeting brought together over 80 experts from academia, government, and industry to discuss critical issues for Reynolds-averaged Navier-Stokes (RANS) turbulence and transition models, as well as to evaluate the results from a collaborative testing challenge based on data-driven methods and machine learning (ML) technology. The symposium represents a continuation of an earlier symposium sponsored by the University of Michigan and NASA, held in Ann Arbor, MI in 2017. The 2022 symposium included a wide variety of talks on the subjects of RANS and ML, five invited talks, and three panel discussions. This talk summarizes the main outcomes of the symposium, and includes suggested recommendations and future directions.

machine learning↗

Comparing Low-Cost Sensors with Ground-Based and Airborne In-Situ and Column Observations of NO2 and HCHO during the FRAPPE Field Campaign in Colorado, USA

Even in the presence of more reliable air quality tools, low-cost sensors have the benefit of recording data on highly localized spatial and temporal scales, allowing for multiple measurements within a single satellite pixel and on pixel boundaries. However, they are less accurate than their regulatory-grade counterparts, requiring regular co-locations with accepted instruments to ensure their validity. Thus, the addition of low-cost sensors to a field campaign – where reference-grade air quality instruments are abundant – not only provides ample opportunities for low-cost sensor co-location and calibration, but also allows the low-cost instruments to be used for sub-pixel validation, covering more surface area than the regulatory instruments alone with a network of sensors. During the summer of 2014, our low-cost sensor network was deployed during the Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ) campaign conducted to sample the composition of air at and above ground level in northeastern Colorado, USA. The low-cost sensor platform included a suite of gas-phase sensors, notably NO2 and two generalized volatile organic compound (VOC) sensors, which were leveraged together to quantify speciated hydrocarbons such as formaldehyde. These key pollutants were chosen for their impacts on human health and climate change, as well as their inclusion on the TEMPO satellite launching this year. Airborne campaign measurements included slant column optical observations of formaldehyde (HCHO), nitrogen dioxide (NO2), and ozone (O3). Myriad additional in-situ instruments described chemical composition up to approximately 5 km above surface level. Ground-based instrumentation included both stationary and mobile regulatory-grade instruments, which were used for sensor calibration. Machine learning techniques such as artificial neural networks (ANNs) were used to match the low-cost signals to that of the reference-grade instruments. Here, we compare calibrated low-cost sensor data collected at ground level in a variety of locations along Colorado’s Front Range to various data sources from the FRAPPÉ campaign to better understand how well airborne and regulatory ground-based measurements can be extrapolated to other locations. Further, as the slant column measurements act as satellite simulators, we explore how low-cost instruments can be used for satellite validation purposes. Comparisons among these different data types also have important implications in data fusion.

Kristen Okorn↗

Trace Elemental Abundances in Calcium-Aluminum-Rich Inclusions in CV Chondrites

Introduction: Calcium-aluminum-rich inclusions (CAIs), are the first formed solids that define the age of the Solar System [1,2]. CAIs are thought to have condensed from nebular gas [3,4] within the first <1 Ma of Solar System formation [5,6]. CAIs have experienced numerous early Solar System processes including condensation, evaporation, melting, recrystallization, and aqueous alteration [e.g., 7]. The chemical, mineralogical, and textural diversity among CAIs results from a range of chemical and physical processes recorded during nebular and parent body epoch. This study aims to explore the mineralogical, textural, and chemical compositions of CAIs including the trace elemental abundances in CAI phases to determine the early Solar System processes recorded in them. Samples and Analytical Methods: We analyzed one CAI each from CV3 chondrites Northwest Africa (NWA) 5508 designated as ‘Saguaro’, and Northwest Africa (NWA) 12772 designated as ‘Hoopoe’. Back-scatter electron (BSE) images were collected using a Phenom XL scanning electron microscope (SEM) at the Lunar and Planetary Institute (LPI) and the JEOL JXA-8530F electron probe microanalyzer (EPMA) at Johnson Space Center (JSC)-NASA. Additionally, energy dispersive X-ray spectrometry (EDS) elemental maps of select areas for these samples were collected using a 15.0kV beam energy and a 40µA emission current. Using the EPMA, wavelength-dispersive X-ray spectroscopy (WDS) quantitative data were collected. In-situ trace element measurements for both CAIs were determined at JSC-NASA using a Photon Machines 193nm laser ablation system and a Thermo-Scientific Element-XR inductively coupled plasma mass spectrometer (ICP-MS). Analyses consisted of 30s ablations at 10Hz, spot sizes of 20-25µm, and a fluence of 6.0 J/cm2 for anorthite and melilite, and a 3.5 J/cm2 fluence for all other phases. NIST612 was used to correct for instrument drift, while BHVO-2g was used as a primary calibration standard. BCR-2g and in-house mineral standards were regularly measured as unknowns to ensure accuracy. Results: Saguaro is a coarse-grained CAI, ~11 x 6 mm in dimensions. Saguaro contains spinel, Al-rich pyroxene, anorthite, Mg-rich melilite, and minor perovskite in its interior and is therefore classified as a Type B CAI. Individual melilite grains shows normal compositional zoning with an Ak content ranging from ~24 to 54 with no apparent trend from the core to the edge of the CAI. The spinel appears euhedral and occurs both as clusters and as spinel palisades [8]. Two rim sequences surround most of the sample: the inner rim being a Wark-Lovering (WL) rim (~10-35 µm) containing pyroxene, spinel, and melilite (or anorthite), and the outer rim is a finer-grained, thicker (~100 µm), accretionary rim (Fig. 1). The mineral phases in Saguaro record an overall flat REE pattern with an average negative Eu anomaly in pyroxene, and an average positive Eu anomaly in anorthite and melilite respectively. Anorthite, melilite, and pyroxene have a minor depletion in Tm (Fig. 2). The Hoopoe CAI is a compact, coarse-grained ~6 × 4 mm in size. The major mineralogy includes hibonite, spinel, melilite, anorthite, and perovskite. Therefore, it is classified as a compact transitional type A and B. (?)zoning was observed in some hibonites. Individual melilite grains show both reverse and normal zoning, where the Ak content ranges from ~6- to 28. Melilite shows two distinct textures. One texture consisted of smooth melilite that appeared homogenous, while the second appeared to consist of many fine fractures. The spinel also often appears clustered. The WL-rim sequence surrounding Hoopoe is ~25 µm thick and composed of spinel, perovskite, hibonite, and melilite/anorthite. It is then partially surrounded by an outer accretionary rim (~75µm). Like before, refractory metal nuggets appeared concentrated near the WL rims. Other metal assemblages rich in Fe and Ni were also observed. All major mineral phases in Hoopoe display relatively flat REE patterns, except for varying Eu and Tm between phases (Fig. 2). There is a prominent negative Eu anomaly in perovskite and an average positive Eu anomaly in spinel, anorthite, and hibonite respectively (Fig. 2, 3). The mixed phases along the rim of the CAI also display a negative Eu anomaly, and all phases the CAI were depleted in Pb. Discussion: The CV3 CAIs analyzed in this study were classified based on their mineralogy and textures into Type A versus Type B CAIs [10]. Hibonite appears to be pseudomorphically replacing the spinel, (i.e., is hibonite in composition, but appears in the shape of spinel). Spinel palisades. The presence of spinel palisades present in Saguaro are consistent with the melting and recrystallization experienced by this CAI. Trace elemental analyses. Saguaro and Hoopoe display similar trace element patterns to each other, with both appearing generally flat, with anomalies in Eu, and Tm. Melilite and anorthite display positive Eu anomalies in both CAIs, in addition to the hibonite in Hoopoe (Fig. 2). The phases that are depleted in Eu are pyroxene and perovskite in both Saguaro and Hoopoe, respectively (Fig. 3). Given that Eu is volatile in reducing environments [11], this could possibly indicate reducing conditions at the time anorthite and melilite crystallized, with the gas they formed from containing Eu. As these CAIs continued to form, this gas as a result would become depleted in Eu. This also could be supported by the propensity of anorthite and melilite to take up Eu from its surroundings and incorporate it into their structure [12]. In addition, analyzing the assemblage of the phases in the Saguaro, melilite and anorthite (Eu enriched) often surround the pyroxene (Eu depleted) as they are crystallized. This intergrowth of phases and the proximity of the phases would support that the Eu is being incorporated into some phases, preventing it from incorporating into other. Trace elemental analyses of the CAI rims will be evaluated in more detail, as they are complicated by the transient signal being composed of a mixture of mineral phases. Broadly, however, the patterns in the rims of both CAIs are comparable to each other, and for Hoopoe, to the mixed phase patterns in the core (Fig. 3). Other studies have found that CAI rims can be depleted in Ce and Yb [13], however we did not observe these anomalies in the two CAIs discussed here. Given their similarity, the trace elemental analyses of the mixed interior (i.e. core) and rim phases could be interpreted as forming from similar, if not the same, reservoirs. The REE abundance between the rim and core of Hoopoe are also similar, indicating they may have formed from a gas of the same or similar composition. Acknowledgments: We thank the ASU Center for Meteorite Studies for loaning the samples used in this work and Tabb Prissel for his assistance with the analysis. Mouti Al-Hashimi thanks Sam Crossley and Cyrena Goodrich for their help with the LPI SEM training. This work was supported by the LPI Summer Intern Program in Planetary Science and the LPI Cooperative Agreement. References: [1] Connelly J.N. (2012) Science, 338, 651-655. [2] MacPherson G. J. (2014) Treatise on Geochem., 2, 139-179. [3] Grossman L. (1972) GCA, 36, 597-619. [4] Ebel, D.S. (2006) Meteorites and the Early Solar System II (D. S. Lauretta & H. Y. McSween, Eds.) 253-277. [5] MacPherson G. J. (2012) Earth Planet. Sci. Lett., 331-332, 43-54. [6] MacPherson G.J. (2017) GCA, 201, 65-82. [7] Krot A.N. (1995) Meteoritics & Planet. Sci., 30, 748-775. [8] Wark and Lovering (1982) GCA, 46, 2595-2607. [9] Palme H. and Jones A. (2003) Treatise on Geochemistry (H. D. Holland and K. K. Turekian Eds.), 1, 41-61. [10] Grossman L. (1980) Ann. Rev. Earth Planet. Sci., 8, 559-608. [11] Floss C. et al. (1996) GCA, 60, 1975-1997. [12] Mason B. and Martin P. M. (1974) Earth Planet. Sci. Lett., 22, 141-144. [13] Wark B. and Boynton W. V. (2001) Meteoritics & Planet. Sci., 36, 1135-1166.

X Mouti↗

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↗