Abstract The transition of shape memory alloy (SMA) actuators to production is hampered by a lack of standardized material specifications, a gap being addressed through ASTM work item WK82516, which is developing a specification for wrought NiTi-based SMAs for actuation under the active guidance of CASMART's Design Working Group with contributions from academia, government, and industry. The draft specification is intended as part of an emerging set of standards and test methods to broaden SMA adoption across industries.

Data-driven analysis techniques have recently emerged for solving nonlinear static aeroelasticity problems that leverage parallel computation to reduce computational time relative to conventional loosely-coupled schemes that iteratively exchange displacement and traction field information between independent fluid and structural models. One approach in particular, the compositional static aeroelastic analysis method, relies upon statistical exploration of shape parameters characterizing a reduced-order representation of the structural deformations, which is followed by a set of independent one-way fluid and structure model evaluations used to construct an aeroelastic surrogate model whose fixed-point parametrically represents the static aeroelastic solution. This works seeks to examine the trade-offs between solution accuracy, computational time, and computational cost of the compositional method relative to a conventional loosely-coupled analysis and considers a range of problem dimensions, shape parameter sampling domain sizes, number of surrogate training samples, and surrogate model types. Additionally, an adaptive sampling scheme is proposed that combines the parallelization capabilities and surrogate information of the compositional method with the superior convergence properties of iterative methods. The results from this study suggest that the compositional method with non-adaptive sampling is adequate for low-to-moderate fidelity analysis as solution error ranges on the order of 0.1% to 1% for moderately sized sampling domains with 20 or less shape parameters. Incorporating adaptive sampling considerably improves solution accuracy compared to non-adaptive sampling for the same total number of fluid-structure evaluations while improving the rate of convergence of fixed-point iteration up to four orders of magnitude. Depending upon analysis requirements, use of adaptive sampling improves computational time by a factor of 5 to 15 and computational cost up to a factor of 4 relative to fixed-point iteration.

During aircraft takeoff and landing, significant acoustic noise is generated by high-lift devices such as slats and flaps. The deployment of forward slats creates geometric gaps that lead to airflow recirculation and unsteady flow, which are primary sources of noise. A slat gap filler (SGF) can mitigate this noise by preventing gap flow, thereby eliminating the recirculation region. However, this also slightly reduces the aerodynamic effectiveness of the slat. To address this, a model scale SGF made from shape memory alloy (SMA) has been developed to treat an articulated 1/16th scale High Lift-Common Research Model (HL-CRM) 2D wing section model wing. This paper presents the aerodynamic and aeroacoustic results of the SGF on the wing. The findings include measurements of forces, local coefficient of pressure, and acoustic performance using an acoustic beamforming array.

Analyzing the multiphysical coupling between a deformable structural body and the forces imposed on that body from a surrounding fluid can be a challenging and computationally expensive task, especially when the structure, fluid, or both exhibit nonlinear behavior. Consequently, there exists a need for novel reduced-order static aeroelasticity analysis techniques that make efficient use of high-fidelity computational models, especially for preliminary design of next- generation aerostructures with high-aspect ratio lifting surfaces exhibiting large deformations or in situ geometric reconfigurations driven by nonlinear mechanisms. This work presents the compositional static aeroelastic analysis method: an embarrassingly parallelizable data- driven modeling technique that seeks to construct a system-level aeroelastic surrogate model representing the function composition of high-fidelity structural and fluid models in terms of shape parameters characterizing a reduced-order geometric description of the deformed fluid-structure interface. By formulating the static aeroelasticity problem as a fixed point problem, the proposed reduced-order modeling framework removes the need for a reduced- order representation of the traction field acting on the structure, unlike previous data-driven methods that independently train separate fluid and structural surrogate models. Additionally, by replacing the iterative exchange of full-order aeroelastic coupling variables with a statistical exploration of a reduced-order shape parameter space, the minimum computational time for approximating a static aeroelastic response is equivalent to one set of high-fidelity fluid and structural model evaluations. The following work presents the theoretical development of the proposed compositional method and demonstrates its use in two case studies, one of which involves a cantilevered baffle comprised of linear and nonlinear material with large deformations exceeding 35%. Numerical results show close agreement with a conventional partitioned analysis scheme, where tip displacement error is less than 1% in both material cases. It is also demonstrated how traction field information can be reused when considering structural modifications to circumvent the need for additional computationally expensive fluid model evaluations.

Morphing aircraft designers have often looked to birds for their ability to change shape and optimize performance characteristics such as range or maneuverability across different phases of flight. However, designing to optimize performance across multiple mission phases is highly challenging, in part because realistic morphing strategies are not without performance penalties. Common penalties include an increase in weight from additional actuators, structural weight to combat aeroelastic effects, and increased power requirements. In this work, a computational framework is developed to explore the adaptivity trade-space for a fixed wing unmanned aerial vehicle (UAV) across multiple mission phases early in the design process. To maximize feasibility, a preprocessor attempts to prepose for further analysis only aircraft geometry configurations that satisfy given mission requirements using textbook-level approximations. For each configuration, an aerodynamic and static stability analysis are completed in parallel to determine performance across all mission stages. Using the novel Non-dominated Sorting Genetic Algorithm for Adaptive Design (NSGA-AD), an extension of NSGA-II, the design space is decomposed into adaptive families based on morphing capability (e.g., adaptive sweep, twist, camber), these being quantitatively compared for a given set of mission requirements. High-performance families are retained and penalized based on expected structural and system disadvantages (weight, power). To demonstrate the novel computational design framework, an adaptivity scheme for a fixed wing UAV is algorithmically selected for a mission. The mission focuses on navigating through congested environments where flight through tight geometric bounds (e.g., windows or doors) inspires and guides the morphing behavior.

This paper presents the initial development of a Software Design Framework for rapid design, analysis, and performance estimation of a family of avian-inspired, fixed-wing SUAVs with novel capabilities such as gust resistance, stationary and moving obstacle avoidance, navigation through tight and constrained spaces, and potential exploitation of prevailing winds and thermals to increase range and endurance - all enabled by morphing and extreme maneuverability.

Scanning beamforming arrays are powerful tools for high-resolution acoustic imaging, but cross spectral matrix (CSM)-based methods are slow when applied to the large synthetic CSMs created by scanning arrays. Modified forms of frequency-domain beamforming (FDBF) and CLEAN-SC deconvolution have been developed that directly use partial field matrices, increasing computational efficiency while retaining the benefits of a full spectral matrix. Here these partial field techniques are implemented and tested in MATLAB R2023a. FDBF performance is improved by up to three orders of magnitude and CLEAN-SC performance is improved by up to one order of magnitude. GPU acceleration is implemented for FDBF and achieves another order of magnitude performance improvement. An experimental demonstration is conducted in the Texas A&M University 3 ft x 4 ft low-speed wind tunnel using a hybrid anechoic section and a 31-channel scanning acoustic array. Partial field FDBF and CLEAN-SC algorithms are applied and compared to the original algorithms, and acoustic imaging is shown to be effective.

The development of EVA spacesuits is critical to human survivability in the hostile environment of space. Whether in Low Earth Orbit (LEO), on the surface of the Moon, or on Mars, astronauts will encounter extremely low atmospheric pressures (such as vacuum in LEO and on the surface of the Moon) and temperature extremes (e.g. -250F to +250F in LEO) that are lethal to humans. Although EVA spacesuits must protect humans against these conditions, maintaining an astronaut’s mobility is equally important in order to achieve mission objectives, such as a return to the Moon as defined by the Artemis architectures. Improved mobility which is designed into an EVA suit should reduce energy expenditures and therefore fatigue. Spacesuit mobility is largely driven by the design of joints, such as the knee, elbow, ankle, waist, and shoulder joints. Joint design has evolved considerably since the first pressure flight suits designed in the 1930’s. One of the earliest designs was the convolute joint that has been implemented in several spacesuits, from the Apollo A7LB to the finger joints of the current Extravehicular Mobility Unit (EMU) spacesuit glove. For the Apollo A7LB spacesuits, full circumferential rubber-dipped nylon convolutes were utilized in the elbow, shoulders, elbows, wrists, hips, knees, and ankles. The current Space Shuttle/International Space Station (ISS) EVA EMU incorporates a flat pattern half circumferential gore design at the elbow. An understanding of the mobility of A7LB style elbow joint design, in comparison to the flat pattern gore design, could provide new insights for the development of future spacesuits. Our Aerospace Human Systems Laboratory (AHSL) previously developed and published a preliminary Finite Element Analysis (FEA) model of the EMU sleeve in order to predict torque as a function of "fit", number of gores, and pressure. This ‘Virtual Twin’ research is part of an ongoing effort to model human performance based on individual anthropometrics and EVA suit design variables prior to manufacturing the EVA suit. In this paper, an ABAQUS/Explicit FEA model was developed to predict elbow joint torques during pressurized convolute sleeve bends using the Apollo A7LB pressure garment assembly (PGA) arm configuration. Design data was extracted from available literature and images. The model was scripted to allow for adjustment of the number of convolutes, convolute and restraint cable geometry, sleeve thickness, internal pressure, and elbow bend angle. The results from this torque/mobility comparison are reported as a function of the effects of the identified design variables. This research could provide insight into the relative impact of the various design variables including the operational pressure differential on joint torque and, therefore, expected mobility and energy expenditure.

The low cost and low risk nature of small unmanned aerial vehicles has enabled the testing of various types of active structures which may enable significant performance enhancements including increased range and endurance, as well as optimization for varying phases of flight. These active structures allow aerial vehicles to reconfigure various features, including variable wing camber, twist, sweep, and span. While it is necessary to predict the impact of these active structures on the aerodynamic and control properties of these aerial vehicles, it is also vital to understand the inverse relationship of how aerodynamics will impact the elastic deformation of these active structures. To that end, the uncoupled static aeroelastic analysis method has been augmented to enable the analysis of active wings via the inclusion of a reconfiguration parameter. The uncoupled static aeroelastic analysis method enables rapid analysis of the aeroelastic behavior of an aerial body through the use of surrogate modeling. This method has been shown to yield accurate results when compared to both experimental results and coupled aeroelastic analyses while significantly reducing the cost (physical and computational, respectively). In the current study, a representative small unmanned aerial vehicle wing is studied with a variable wingspan. The analysis of such a wing with variable wingspan is performed for a wing with a rectangular planform and constant cambered airfoil shape, wherein the wing half-span varies from 0.6 m - 0.8 m. Results show that wing tip displacement due to out-of-plane bending (vertical displacement) as well as in-plane sweep both initially increase with higher extension amounts and angle of attack. However at approximately 70% extension and beyond, the wing tip displacement for both out-of-plane bending and in-plane sweep decrease due to reduced velocity required to maintain constant flight as well as higher in-plane strain on the skin.

Additively manufactured Nitinol (NiTi) architectured materials, designed with unit cell architectures, hold promise for customisable applications. However, the common assumption of homogeneity in modeling and additive manufacturing of these architectured materials needs further investigation because geometric-dependent melt pool behaviour results in inhomogeneous microstructure and thermomechanical properties. This study shows that property inhomogeneity at the mesoscale is one reason for pseudo-linear response and partial superelasticity of the fabricated NiTi body-centered cubic (BCC) architectured materials. We modeled using a phenomenological constitutive relation and additively manufactured NiTi architectured materials with varying relative densities. These fabricated samples showed distinct microstructural textures and compositions that affected their local recoverability. The edge effects and laser turn regions were identified as the causes underlying the observed microstructural inhomogeneity. The dimensionless Fourier number is used to describe the transition of printing modes. This study provides valuable information on rigorous experimental/computational consistency in future work.

Many scientific developments pioneered by governmental research organizations are subsequently applied to consumer products. The use of shape memory alloys (SMAs) by NASA at the end of the 20th century motivated companies to incorporate these materials and their unique properties into marketable goods. In 1997, NASA reported that the Nicklaus Golf Company had developed a line of SMA-augmented golf clubs; the company claimed that its SMA club inserts reduced vibration and imparted greater spin on balls during contact. Inspired by these claims of enhanced performance, this work investigates the impact of SMA clubfaces on golf ball carry distance and shot accuracy for several clubface contact locations and slice angles. For each combination of shot parameters tested, the ball exit velocity and spin were computed via finite element analysis (FEA) using an explicit dynamic model that accounts for stress-induced phase transformation in SMA material regions and golf ball responses calibrated from experimental testing. The exit velocity and spin rate were used to calculate the ball flight trajectories for each case simulated. Alloy and design assumptions, including the addition of an internal cavity, were made to facilitate the development of stresses necessary for meaningful SMA material responses during clubface-ball impacts. These assumptions lead to findings such as nearly equivalent performances for geometrically identical clubheads with steel and SMA clubface inserts. Overall, this work shows that the use of reasonable SMA materials in a clubhead operating under normal weather conditions is inconsequential to shot accuracy and carry distance.

A combined linear and rotary continuous-scan acoustic beamforming array is presented in this work. Conventional beamforming arrays use a set of stationary microphones to localize sources while a scanning array uses moving microphones with stationary microphones for phase referencing. This scanning approach increases the effective number of sensors, providing high resolution and dynamic range while limiting the sensor budget. A scanning phased acoustic array utilizing 62 physical sensors has been designed, fabricated, and experimentally validated at Texas A&M University at a hardware cost under $15,000. Initial results from the scanning array show improved source localization compared to stationary beamforming with the same equipment and promising performance compared to a commercially-available acoustic beamforming array.

Substructure analysis reduces the computational order of a discretized structural domain from the full set of degrees of freedom needed to solve a boundary value problem (e.g., the displace-ments of all nodes in an FEA mesh) to a predefined and much smaller set of retained degrees of freedom. Given only one initial analysis considering all degrees of freedom, this technique reduces the computational cost associated with subsequent analyses of the same domain by eliminating degrees of freedom, usually internal to the domain, which are not essential for interfacing the domain with a larger system/assembly. For large multiscale applications, such as aircraft and automotive assemblies, substructure analysis enables efficient computation of both static and dynamic responses of larger assemblies consisting of one or more of these previously analyzed and dimensionally reduced domains. However, while existing methods are exact for linear problems (e.g., small-deformation linear elasticity), they are insufficient when considering large deformations or material nonlinearities. In this work, we develop a new nonlinear substructure method to consider general nonlinear responses by leveraging the mathematical framework developed for computational plasticity, including a decomposition of deformations, criteria for nonlinearity initiation, and evolution equations. While computational plasticity provides nonlinear constitutive relationships between six independent stress and strain components, we show that the same mathematical formulation can capture similar relations between an arbitrary number of forces and displacements (i.e., the retained degrees of freedom), and thus, can be implemented with the same numerical solution algorithms. As a notional example to emphasize both the generality of the aforementioned method and the application to design frameworks, we model an infilled lattice structure exhibiting local plasticity and internal nonlinear geometric effects.

Future manned space missions will require thermal control systems that can adapt to larger fluctuations in temperature and heat flux exceeding the capabilities of current state-of-the-art technologies. Specifically, these missions will demand novel space radiators that can vary the system heat rejection rate to maintain the crew cabin at habitable temperatures throughout the entire mission. While current systems can provide a turndown ratio (defined as the ratio of maximum to minimum heat rejection rates) of 3:1 under adverse conditions, future missions are projected to demand thermal control systems that can provide a turndown ratio of more than 6:1. A novel morphing radiator concept autonomously varies the system heat rejection rate by altering the shape of the panel exposed to space, where composite materials can provide an ideal compromise between thermal conductivity, restorative stiffness and deformation capability. Shape change is accomplished through the use of shape memory alloys, a class of active materials that exhibit thermomechanically driven phase transformations and can be used as simultaneous sensors and actuators in thermal control applications. This work details progress towards testing and modeling a spaceflight-quality, high turndown ratio morphing radiator prototype in a relevant thermal environment. A prototype composite morphing radiator with shape memory alloy strip actuators and high performance thermal coatings achieved a turndown ratio of 7.2:1, while an associated multi-physical model thereof has been shown to capture all major effects and will enable future design improvements.

Surface treatments for metal additive manufacturing have been increasingly explored to remedy undesired high surface roughness in as-printed components, which can hinder intended performance. Chemical etching is a simple method of improving surface quality in mechanically inaccessible, internal, delicate, or otherwise complex regions in such parts. In this work, the chemical etching effectiveness of the sodium fluoride and ammonium persulfate solution, known as Multi-Etch , was explored on printed nickel–titanium shape memory alloy surfaces at various exposure temperatures and times. Titanium-containing alloys often require solutions of extremely hazardous hydrofluoric acid (HF), which prompts specialized safety infrastructure; in contrast, the etchant herein is a substantially safer titanium etchant alternative. Nickel–titanium parts were generated via laser powder-bed fusion (LPBF) with geometries consisting of exterior surfaces, unsupported overhangs, and internal channels. Surface morphologies were investigated with scanning electron microscopy and optical surface profilometers. A particle size analysis of partially fused particles on as-printed surfaces was performed. Various areal surface texture parameters were considered to properly compare the as-printed and etched surfaces, of which the density of peaks ( S pd ), peak curvature ( S pc ), slope ( S dq ), and developed interfacial area ratio ( S dr ) were drastically reduced. An effective reduction of surface roughness, without detrimental loss in mass and spatial dimensions, was developed by etching at temperatures ranging from 40 to 60 °C for at least one hour. Metallurgical inclusions and melt track borders were preferentially etched at lower temperatures. The etching treatment herein represents an effective process for improving the surface quality of powder-bed fused nickel–titanium.

In this paper a series of low boom adaptive structure hardware demonstrators are described.The designs are enabled by recent advances in SMA technology including improved high temperature materials, better design and modeling tools, and industry approved test methods.The test hardware replicates the centerline keel of a representative supersonic aircraft.An array of SMA based actuators are used to modify the keel structure resulting in a change to the geometry of the Outer Mold Line (OML).The shape changes are intended to maintain a low boom signature in response to changes in Mach, angle of attack, flight path, or atmospheric profile.A description of the hardware design, SMA control system, and integration into a supersonic flight simulator are shown.Test results showing real-time geometry changes minimizing the predicted boom are presented.The design, build, and test of the adaptive structure demonstrators was led by a team of undergraduate students,

The properties of shape memory alloy (SMA) wires have long been leveraged across a variety of industries. While the response of such SMA forms implemented as straight axial actuators is well understood, curved and complex configurations such as knits have received far less attention. Considering 2D configurations, it is well known that knits exhibit more in-plane compliance than weaves and meshes, the curved wires comprising the former being much more flexible than the straight wire segments in the latter. In addition, knitted structures are uniquely highly tailorable. Knitting techniques and patterns developed in the textile industry allow for variable materials and geometries in the same structure, allowing for a large range of tailored macro-structure responses. Existing efforts to model the behavior of knitted SMA structures are lacking; though finite element analysis (FEA) models have been presented for knit SMAs, these models either only consider superelastic SMA behavior, or, in those that account for actuation behavior, the applied load conditions studied are insufficient to fully leverage the thermally induced strain recoverability of SMAs. This work seeks to develop and validate a finite element model for the actuation of SMA knitted structures where individual SMA wire components are axially stressed to more than 100 MPa. A representative volume element is developed for a common knit pattern, and macro-structure responses are explored and compared with experiments. This research provides a foundation for better understanding fundamental capabilities and responses of knitted SMA structures, allowing for better design, functionality, and customizability of the applications into which they are incorporated, enabling development of unique soft actuators. A shape-set sample examined herein generated 13% extension (analogous to strain) and recovered more that 6% under a load associated with 100 MPa stress in a straight wire, and a sample knit off-the-spool generated over 20% extension and recovered 9% for the same load.