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The design and application of advanced composites is discussed with emphasis on aerospace, aircraft, automotive, marine, and industrial applications. Failure modes in advanced composites are also discussed.
Assembly of dissimilar metals can be achieved by different methods, for example, casting, welding, and additive manufacturing (AM). However, undesired phases formed in liquid-phase assembling processes due to solute segregation during solidification diminish mechanical and other properties of the processed parts. In the present work, an open-source software named MaterialsMap, has been developed based on the CALculation of Phase Diagrams (CALPHAD) approach. The primary objective of MaterialsMap is to facilitate the design of an optimal composition pathway for assembling dissimilar alloys with liquid-phases based on the formation of desired and undesired phases along the pathway. In MaterialsMap, equilibrium thermodynamic calculations are used to predict equilibrium phases formed at slow cooling rate, while Scheil-Gulliver simulations are employed to predict non-equilibrium phases formed during rapid cooling. Additionally, by combining these two simulations, MaterialsMap offers a thorough guide for understanding phase formation in various manufacturing processes, assisting users in making informed decisions during material selection and production. As a demonstration of this approach, a compositional pathway was designed from pure Al to pure Cu through Ag using MaterialsMap. The design was experimentally verified using resistance spot welding (RSW).
The Structural Engineering Division at the NASA Johnson Space Center (JSC) has begun work on lightweight, multi‐functional pressurized composite structures. The first candidate vehicle for technology development is the Multi‐Mission Space Exploration Vehicle (MMSEV) cabin, known as the Gen 2B cabin, which has been built at JSC by the Robotics Division. Of the habitable MMSEV vehicle prototypes designed to date, this is the first one specifically analyzed and tested to hold internal pressure and the only one made out of composite materials. This design uses a laminate base with zoned reinforcement and external stringers, intended to demonstrate certain capabilities, and to prepare for the next cabin design, which will be a composite sandwich panel construction with multi‐functional capabilities. As part of this advanced development process, a number of new technologies were used to assist in the design and manufacturing process. One of the methods, new to JSC, was to build the Gen 2B cabin with Out of Autoclave technology to permit the creation of larger parts with fewer joints. An 8‐ply pre‐preg layup was constructed to form the cabin body. Prior to lay‐up, a design optimization software called FiberSIM was used to create each ply pattern. This software is integrated with Pro/Engineer to allow for customized draping of each fabric ply over the complex tool surface. Slits and darts are made in the software model to create an optimal design that maintains proper fiber placement and orientation. The flat pattern of each ply is then exported and sent to an automated cutting table where the patterns are cut out of graphite material. Additionally, to assist in lay‐up, a laser projection system (LPT) is used to project outlines of each ply directly onto the tool face for accurate fiber placement and ply build‐up. Finally, as part of the OoA process, a large oven was procured to post‐cure each part. After manufacturing complete, the cabin underwent modal and pressure testing (currently in progress at date of writing) and will go on to be outfitted and used for further ops usage.
Mineral-polymer composites found in nature exhibit exceptional structural properties essential to their function, and transferring these attributes to the synthetic design of functional materials holds promise across various sectors. Biomimetic fabrication of nanocomposites introduces new pathways for advanced material design and explores biomineralization strategies. This study presents a novel approach for producing single platelet nanocomposites composed of CaCO 3 and biomimetic peptoid (N-substituted glycines) polymers, akin to the bricks found in the brick-and-mortar structure of nacre, the inner layer of certain mollusc shells. The significant aspect of the proposed strategy is the use of organic peptoid nanosheets as the scaffolds for brick formation, along with their controlled mineralization in solution. Here, we employ the B28 peptoid nanosheet as a scaffold, which readily forms free-floating zwitterionic bilayers in aqueous solution. The peptoid nanosheets were mineralized under consistent initial conditions (σ calcite = 1.2, pH 9.00), with variations in mixing conditions and supersaturation profiles over time aimed at controlling the final product. Nanosheets were mineralized in both feedback control experiments, where supersaturation was continuously replenished by titrant addition and in batch experiments without a feedback loop. Complete coverage of the nanosheet surface by amorphous calcium carbonate was achieved under specific conditions with feedback control mineralization, whereas vaterite was the primary CaCO 3 phase observed after batch experiments. Thermodynamic calculations suggest that time-dependent supersaturation profiles as well as the spatial distribution of supersaturation are effective controls for tuning the mineralization extent and product. We anticipate that the control strategies outlined in this work can serve as a foundation for the advanced and scalable fabrication of nanocomposites as building blocks for nacre-mimetic and functional materials.
High entropy alloys (HEAs) are an important material class in the development of next-generation structural materials, but the astronomically large composition space cannot be efficiently explored by experiments or first-principles calculations. Machine learning (ML) methods might address this challenge, but ML of HEAs has been hindered by the scarcity of HEA property data. In this work, the EMTO-CPA method was used to generate a large HEA dataset (spanning a composition space of 14 elements) containing 7086 cubic HEA structures with structural properties, 1911 of which have the complete elastic tensor calculated. The elastic property dataset was used to train a ML model with the Deep Sets architecture. The Deep Sets model has better predictive performance and generalizability compared to other ML models. Association rule mining was applied to the model predictions to describe the compositional dependence of HEA elastic properties and to demonstrate the potential for data-driven alloy design.
Risk and cost trade-offs have been simulated using a probabilistic method. The probabilistic method accounts for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. The probability density function of first buckling load for a set of uncertain variables is computed. The probabilistic sensitivity factors of uncertain variables to the first buckling load is calculated. The reliability-based cost for a composite fuselage panel is defined and minimized with respect to requisite design parameters. The optimization is achieved by solving a system of nonlinear algebraic equations whose coefficients are functions of probabilistic sensitivity factors. With optimum design parameters such as the mean and coefficient of variation (representing range of scatter) of uncertain variables, the most efficient and economical manufacturing procedure can be selected. In this paper, optimum values of the requisite design parameters for a predetermined cost due to failure occurrence are computationally determined. The results for the fuselage panel analysis show that the higher the cost due to failure occurrence, the smaller the optimum coefficient of variation of fiber modulus (design parameter) in longitudinal direction.
Abstract Al alloys often suffer from low mechanical strength and lack high-temperature microstructural and mechanical robustness. A series of binary and ternary nanocrystalline (NC) Al transition metal alloys with supersaturated solid solution and columnar nanograins have been recently developed by using magnetron sputtering, manifesting a new realm of mechanical properties and thermal stability. Distinct solutes cause evident differences in the phase transformations and efficiencies for grain refinement and crystalline-to-amorphous transition. Certain sputtered Al-TM alloys have shown room-temperature mechanical strengths greater than 2 GPa and outstanding thermal stability up to 400 °C. In addition, the NC Al alloys show mechanical anisotropy and tension–compression asymmetry, revealed by micromechanical tests. Through the process encapsulating various compositionally distinct systems, we attempt to illuminate the solute effects on grain refinement and properties and more importantly, tentatively unravel the design criteria for high-strength and yet thermally stable NC Al alloys. Graphic Abstract
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Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.
Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.
Boron/epoxy and graphite/epoxy composite blades were impacted in a rotating whirligig facility with conditions closely simulating those which might be experienced by a STOL engine impacted with various foreign objects. The tip speed of the rotating blades was 800 feet per second. The blades were impacted with simulated birds, real birds, ice balls, and gravel. The results of composite blade impact tests were compared with a titanium blade tested under similar conditions. Neither composite material indicated a clear superiority over the other. Blades made from both composite materials showed more damage than the titanium blades.
A comprehensive experimental and analytical evaluation of the tensor polynomial failure criterion was undertaken to determine its capability for predicting the ultimate strength of a composite limina subject to a plane stress state. Results are presented demonstrating that a quadratic formulation is too conservative and a cubic representation is required. Strength comparisons with test data derived from glass/epoxy and graphite/epoxy tubular specimens are also provided to validate the cubic strength criterion. Environmental effects including ambient temperature, exposure to vacuum, length of post-cure time, and rate of cool down were also investigated. Behavior changes associated with polymer (epoxy) matrix composites were determined in terms of variations in stiffness and tensile strength.
The gains in structural efficiency are investigated that can be achieved by aligning the fibers in some or all of the layers in a laminate with the principal stress directions in those layers. The name curvilinear fiber format is given to this idea. The problem studied is a plate with a central circular hole subjected to a uniaxial tensile load. An iteration scheme is used to find the fiber directions at each point in the laminate. Two failure criteria are used to evaluate the tensile load capacity of the plates with a curvilinear format, and for comparison, counterpart plates with a conventional straightline fiber format. The curvilinear designs for improved tensile capacity are then checked for buckling resistance. It is concluded that gains in efficiency can be realized with the curvilinear format.
Panel Analysis and Sizing Code (PASCO) computer program developed for buckling and vibration analysis and sizing of prismatic structures having arbitrary cross sections. Intended for analyzing and sizing stiffened panels made of laminated orthotropic materials, and of particular value in analyzing and sizing filamentary composite structures. Macintosh version of PASCO includes interactive, graphic preprocessor called MACPASCO. Main objective to make use of PASCO faster, simpler, and less error-prone. Includes graphical user interface (GUI). PASCO written in FORTRAN IV. MACPASCO written in Macintosh Programmers Workbench 3.0, MPW Pascal 3.0, and MacAPP 2.0.
As a means of improving structural design, the concept of fabricating flat plates containing holes by incorporating curvilinear fiber trajectories to transmit loads around the hole is studied. In the present discussion this concept is viewed from a structural level, where access holes, windows, doors, and other openings are of significant size. This is opposed to holes sized for mechanical fasteners. Instead of cutting the important load-bearing fibers at the hole edge, as a conventional straightline design does, the curvilinear design preserves the load-bearing fibers by orienting them in smooth trajectories around the holes, their loading not ending abruptly at the hole edge. Though the concept of curvilinear fiber trajectories has been studied before, attempts to manufacture and test such plates have been limited. This report describes a cooperative effort between Cincinnati Milacron Inc., NASA Langley Research Center, and Virginia Polytechnic Institute and State University to design, manufacture, and test plates using the curvilinear fiber trajectory concept. The paper discusses details of the plate design, details of the manufacturing, and a summary of results from testing the plates with inplane compressive buckling loads and tensile loads. Comparisons between the curvilinear and conventional straightline fiber designs based on measurements and observation are made. Failure modes, failure loads, strains, deflections, and other key responses are compared.