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101 records · Page 6

Transfer Function Models and Sensitivity Analysis

In many situations, real or induced flaws such as tight cracks with known morphology cannot be manufactured in part configuration specimens or in real parts. Typically, fatigue cracks are manufactured in simple geometry specimens such as flat plates, dog-bone shaped flat or round specimens. If a nondestructive evaluation (NDE) technique is required to provide a reliably detectable target flaw size denoted as α_(90/95) for induced flaws in real part, then the direct method for qualifying the NDE procedure is to use the appropriate induced flaw specimens and perform probability of detection analysis using these flaws. This can be described as direct POD demonstration testing, which may follow guidelines of MIL-HDBK-1823. This paper considers a case, where induced flaws are not available in part configuration specimens. Therefore, a direct POD demonstration study cannot be undertaken. In such situation, general practice for NDE procedure qualification is to use artificial flaws in simple geometry and part configuration specimens, and induced flaws in the chosen simple geometry specimens. Signal response data is taken on all sets of artificial and induced flaws. NDE procedure testing on induced flaw in simple geometry specimen is called NDE demonstration testing here. A transfer function NDE procedure qualification method for forward case calculates predicted induced flaw size for demonstration using a chosen target flaw size. Another transfer function method for inverse case, calculates the target flaw size using a given demonstration flaw size. The transfer function analysis assumes relationship of artificial flaw signal responses in real parts and simple geometry specimens; and induced flaw responses in simple geometry specimens to induced flaws in real parts. The signal response transfer relationships model should be defined before transfer function models can be devised. Assuming that the signal response transfer relationships model is valid, forward and inverse case transfer function methods have been devised. Because of lack of signal response data from induced flaws in real part, 90/95% POD/confidence (P/C) cannot be demonstrated directly. However, the transfer function method may be assessed using simulation to evaluate whether the resulting target flaw size or demonstration flaw size provides adequate confidence to the assumed signal response transfer relationships model. Therefore, the transfer function approach is a risk assessment approach. Both the signal response transfer relationships model and the transfer function model are important in managing risk in results provided by the transfer function NDE technique qualification or assessment. The signal response transfer relationships model needs to be validated with empirical data and then transfer function model needs to be validated for desired P/C on case-by-case basis.

Nondestructive evaluation↗

Serendipitous Geodesy from Bennu's Short-Lived Moonlets

The Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx; or OREx) spacecraft arrived at its target, near-Earth asteroid (101955) Bennu, on December 3, 2018. The OSIRIS-REx spacecraft has since collected a wealth of scientific information in order to select a suitable site for sampling. Shortly after insertion into orbit on December 31, 2018, particles were identified in starfield images taken by the navigation camera (NavCam 1). Several groups within the OSlRlS-REx team analyzed the particle data in an effort to better understand this newfound activity of Bennu and to investigate the potential sensitivity of the particles to Bennu's geophysical parameters. A number of particles were identified through automatic and manual methods in multiple images, which could be turned into short sequences of optical tracking observations. Here, we discuss the precision orbit determination (OD) effort focused on these particles at NASA GSFC, which involved members of the Independent Navigation Team (INT) in particular. The particle data are combined with other OSIRIS-REx tracking data (radiometric from OSN and optical landmark data) using the NASA GSFC GEODYN orbit determination and geodetic parameter estimation software. We present the results of our study, particularly those pertaining to the gravity field of Bennu. We describe the force modeling improvements made to GEODYN specifically for this work, e.g., with a raytracing-based modeling of solar radiation pressure. The short-lived, low-flying moonlets enable us to determine a gravity field model up to a relatively high degree and order: at least degree 6 without constraints, and up to degree 10 when applying Kaula-like regularization. We can backward- and forward-integrate the trajectory of these particles to the ejection and landing sites on Bennu. We assess the recovered field by its impact on the OSIRIS-REx trajectory reconstruction and prediction quality in the various mission phases (e.g., Orbital A, Detailed Survey, and Orbital B).

Mazarico, Erwan↗

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Trevino, Luis↗

Planning Bias: Planning as a Source of Sampling Bias

Many data-driven planning methods are trained on data generated by planners. It is well known that many statistical learning methods are sensitive to sampling bias, and yet there has been little or no attention to planning as a sampling method and its role in introducing sampling bias into planner-generated training data. Recently, it has been demonstrated that A**,* in the presence of problems with variable heuristic error, prefers some solutions over other equally cost-optimal solutions. But, as we discuss in this paper, mitigation may not be as simple as resolving arbitrary tie-breaking by sampling from ties uniformly at random. In this paper, we formalize an intuition of planning bias. We focus on problems which output a single solution. Diverse planning only complicates the problem by generalizing it to bias in the set of sets; we show how it is subject to bias in the single solution. We make some useful observations about deterministic algorithms in contrast to non-deterministic algorithms. We explain how information entropy may be a good way to measure planning bias, and discuss some issues in evaluating practical approaches to measurement. We address the intuition that uniform random tiebreaking should mitigate bias; and sketch a novel approach to constructing an appropriate random distribution for duplicate detection during forward search for unbiased A*. Finally, we suggest directions for future work.

Planning Scheduling Algorithms↗

X-Ray Spectro-Polarimetry with Photoelectric Polarimeters

We derive a generalization of forward fitting for X-ray spectroscopy to include linear polarization of X-ray sources, appropriate for the anticipated next generation of space-based photoelectric polarimeters. We show that the inclusion of polarization sensitivity requires joint fitting to three observed spectra, one for each of the Stokes parameters, I(E), U(E), and Q(E). The equations for StokesI (E) (the total intensity spectrum) are identical to the familiar case with no polarization sensitivity, and for which the model-predicted spectrum is obtained by a convolution of the source spectrum, F (E), with the familiar energy response function,(E) R(E,E), where (E) and R(E,E) are the effective area and energy redistribution matrix, respectively. In addition to the energy spectrum, the two new relations for U(E) and Q(E) include the source polarization fraction and position angle versus energy, a(E), and 0(E), respectively, and the model-predicted spectra for these relations are obtained by a convolution with the modulated energy response function, (E)(E) R(E,E), where(E) is the energy-dependent modulation fraction that quantifies a polarimeters angular response to 100 polarized radiation. We present results of simulations with response parameters appropriate for the proposed PRAXyS Small Explorer observatory to illustrate the procedures and methods, and we discuss some aspects of photoelectric polarimeters with relevance to understanding their calibration and operation.

polarization↗

Implicit Formulation of Muscle Dynamics in OpenSim

Astronauts lose bone and muscle mass during spaceflight. Exercise countermeasure is the primary method for counteracting bone and muscle mass loss in space. New spacecraft exercise device concepts are currently being developed for the NASAs new crew exploration vehicle. The NASA Digital Astronaut Project (DAP) uses computational modeling to help determine if the new exercise devices will be effective as countermeasures. The NASA Digital Astronaut Project is developing the ability to utilize predictive simulation to provide insight into the change in kinematics and kinetics with a change in device and gravitational environment (1-g versus 0-g). For example, in space exercise the subject's body weight is applied in addition to the loads prescribed for musculoskeletal maintenance. How and where these loads are applied obviously directly impacts bone and tissue loads. Additionally, due to space vehicle structural requirements, exercise devices are often placed on vibration isolation systems. This changes the apparent impedance or stiffness of the device as seen by the user. Data collection under these conditions is often impractical and limited. Predictive modeling provides a means to have a virtual subject to test hypotheses. Predictive simulation provides a virtual subject for which we are able to perform studies such as sensitivity to device loading and vibration isolation without the need for laboratory kinematic or kinetic test data.Direct Collocation optimization provides an efficient means to perform task based optimization and predictive modeling. It is relatively straight forward to structure a physical exercise task in a Direct Collocation mathematical formulation: perform a motion such that you start at an initial pose, achieve a given amount of deflection i.e a squat, return to the initial pose, and minimize muscle activation cost. Direct Collocation is advantageous in that it does not require numerical integration to evaluate the objective function. Instead, the system dynamics are transformed to discrete time and the optimizer is constrained such that the solution is not considered to be a valid unless the dynamic equations are satisfied at all time points. The simulation and optimization are effectively done simultaneously. Due to the implicit integration, time steps can be more coarse than in a differential equation solver. In a gait scenario this means that that the model constraints and cost function are evaluated at 100 nodes in the gait cycle versus 10,000 integration steps in a variable-step forward dynamic simulation. Furthermore, no time is wasted on accurate simulations of movements that are far from the optimum. Constrained optimization algorithms require a Jacobian matrix that contains the partial derivatives of each of the dynamic constraints with respect to of each of the state and control variables at all time points. This is a large but sparse matrix. An implicit dynamics formulation requires computation of the dynamic residuals f as a function of the states x and their derivatives, and controls u:f(x, dxdt, u) 0If the dynamics of musculoskeletal system are formulated implicitly, the Jacobian elements are often available analytically, eliminating the need for numerical differentiation; this is obviously computationally advantageous. Additionally, implicit formulation of musculoskeletal dynamics do not suffer from singularities from low mass bodies, zero muscle activation, or other stiff system or

physical exercise↗

Transonic Cruise Slotted Wing Design for Commercial Transport Aircraft using CDISC

A knowledge-based aerodynamic design method, CDISC, has been extended to enable the computational design of transonic cruise slotted wings for commercial transport aircraft. The cruise slotted wing is a multielement wing concept with a forward main element and an aft flap element, separated to form an intermediate slot. This slot favorably redirects airflow from the main element lower surface toward the low-momentum, upper-surface boundary layer of the flap. Relative to the supercritical wing, the cruise slotted wing enables greater aft loading that helps to reduce shock strength and transonic pressure drag. The cruise slotted wing may be considered a passive drag-reduction technology with potential fuel burn savings and increased vehicle range for next-generation aircraft. The current paper seeks to quantify the drag-saving benefits of cruise slotted wing technology in application to single-aisle commercial transport aircraft. A series of multielement design constraints were developed within CDISC for the design of a partial-span, cruise slotted wing for a Mach-0.8 variant of the Common Research Model. To mitigate the skin-friction drag penalty associated with cruise slotted wings, the design features a flap with natural laminar flow over approximately 75% of the flap surface area. Cruise drag estimates from the NASA USM3D flow solver between a supercritical wing and the partial-span, cruise slotted wing design were within one drag count. Near-cruise, off-design analyses showed limited laminar flow sensitivity to angle of attack and a more gradual drag rise compared to a supercritical wing. Based on this demonstrated benefit, future work is motivated to design a cruise slotted wing with natural laminar flow on both wing elements to achieve a significant reduction in cruise drag while providing delayed drag divergence.

CDISC↗

Transonic Cruise Slotted Wing Design for Commercial Transport Aircraft using CDISC

A knowledge-based aerodynamic design method, CDISC, has been extended to enable the computational design of transonic cruise slotted wings for commercial transport aircraft. The cruise slotted wing is a multielement wing concept with a forward main element and an aft flap element, separated to form an intermediate slot. This slot favorably redirects airflow from the main element lower surface toward the low-momentum, upper-surface boundary layer of the flap. Relative to the supercritical wing, the cruise slotted wing enables greater aft loading that helps to reduce shock strength and transonic pressure drag. The cruise slotted wing may be considered a passive drag reduction technology with potential fuel-burn savings and increased vehicle range for next-generation aircraft. The current paper seeks to quantify the drag-saving benefits of cruise slotted wing technology in application to single-aisle commercial transport aircraft. A series of multielement design constraints were developed within CDISC for the design of a partial-span, cruise slotted wing for a Mach-0.8 variant of the Common Research Model. To mitigate the skin-friction drag penalty associated with cruise slotted wings, the design features a flap with natural laminar flow over approximately 75% of the flap surface area. Cruise drag estimates from the NASA USM3D-ME flow solver between a supercritical wing and the partial-span, cruise slotted wing design were within one drag count. Near-cruise, off-design analyses showed limited laminar-flow sensitivity to angle of attack and a more gradual drag rise compared to a supercritical wing. Based on this observed benefit, future work is motivated to design a cruise slotted wing with laminar flow on both wing elements to achieve a significant reduction in cruise drag while delaying drag divergence.

CDISC↗

Application of Pressure-Sensitive Paint to Rotorcraft

In this presentation, a plan to develop methods for applying pressure-sensitive paint to rotorcraft will be described. These methods are needed because flows over rotor blades are typically very complex and poorly understood and because conventional methods for measuring unsteady pressures on rotor blades (using unsteady pressure transducers provide grossly inadequate spatial resolution. Since PSP is a surface, rather than a point, measurement technique, it has the potential to significantly increase the spatial resolution )f pressure measurements on rotor blades. PSP techniques currently in use at Ames were developed for measuring steady pressures on rigid, complex airplane configurations in large, production wind tunnels. Applying PSP to rotorcraft requires a significant departure from these techniques. First and most importantly new, fast-responding and self-referencing pressure paints are required. The paints must be fast (98% response in 1-5 msec) to resolve flow unsteadiness; they must be self-referencing (or "binary") to account for changes in incident light intensity due to deflection of flexible rotors. Self-referencing paints have been used at Ames for some time; however, these paints have response times that are far too long for unsteady applications. Flash illumination is required to resolve flow unsteadiness and to minimize image blurring due to relative motion between the model and the camera. Current practice at Ames is to use continuous illumination Finally, "in situ" paint calibration versus measurements by pressure transducers, which is current Ames practice, is not practical because of the difficulty and expense of installing transducers in rotor blades. Instead, the paint must be calibrated "a priori" in a calibration chamber. A sequence of five experiments that systematically isolates and addresses the problems involved in making PSP measurements on rotor blades has been planned. These are: (1) measurements on a rigid rotor in hover; (2) measurements on a flexible rotor in hover; measurements of paint response time in a calibration apparatus; (4) measurements on a rigid, two-dimensional oscillating airfoil; and (5) measurements on a flexible rotor in forward flight. Experiments were recently conducted at Ames where PSP measurements were made on a rigid oscillating airfoil (experiment type 4) and on a flexible rotor in hover (experiment type 2). Preliminary results from these experiments will be discussed.

Schairer, Edward T.↗

Implementation of A New Microwave Scattering Database and A Forward Model for Active Microwave Sensors in CRTM

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. CRTM is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk scattering lookup tables in order to perform all-sky RT calculations. However, the current CRTM lookup tables for microwave frequencies were generated based on the Mie theory by assuming spherical frozen particles. The scattering lookup tables generated using the DDA technique has shown to largely improve the RT scattering calculations in the MW region. This presentation targets (i) the implementation and validation of a DDA database that was originally developed for the ARTS RT model into CRTM, and (ii) developing the CRTM active sensor module that takes advantage of the backscattering coefficients computed using the DDA method. The DDA database only provides single scattering properties of different habits, while CRTM requires bulk scattering properties. The CRTM cloud coefficients were previously generated based on the effective radius for representing the size of the particles. However, effective radius is neither measurable nor provided by the NWP models, thus need to be estimated from other geophysical variables such as water content. Therefore, in addition to calculating the CRTM bulk scattering properties from the DDA single scattering database, the CRTM was also largely modified to use cloud water content (kg.m-3), instead of effective radius, for performing the interpolation over size/mass of the particles. CRTM already requires water content as input, thus no extra variables are required for performing scattering calculations using the new ARTS DDA database. The CRTM scattering modules search for effective radius in cloud coefficient files and will use the cloud water content if the effective radius dimension is not found in the cloud coefficient files. Figure 1 shows the CRTM simulated brightness temperatures computed using different cloud coefficients versus ATMS observed values over Hurricane Irma on September 7, 2017 at 18:00 UTC. We used all the cloud water content values included in ERA5 with default CRTM/DDA habits for water, rain, snow, ice, hail, and graupel. ERA5 does not provide separate water content values for ice, hail, and graupel, thus the ice water content values were divided between ice, hail, and graupel clouds similar to what was explained in the previous section. In channels with a frequency lower than 90 GHz, emission from water and rain clouds can compensate for cloud scattering so that cloud contaminated Tbs are larger than corresponding clear sky Tbs. The DDA simulations for channels 1-7 largely perform better than the Mie simulations. The DDA simulations show a mix of small negative and positive simulated minus observed values, while the Mie results show large negative biases. The weighting functions for some of the ATMS temperature sounding channels (channels 9-15) peak mostly above the clouds, therefore the measured Tbs become less sensitive to clouds so that the results of both Mie and DDA become very similar. The Mie lookup tables generate excessive scattering for channel 16, but not enough scattering for the water vapor channels. In the specific case of Hurricane Maria, the DDA lookup tables do not generate enough scattering for channel 16, but the DDA results are much more consistent with observations for water vapor channels than for channel 16. It should be noted that the results may vary if we use other habits to represent snow, hail, and graupel in the DDA simulations. Although these results clearly show the advantage of the DDA database over the Mie dataset, different error sources such as error in the observations, displacement of clouds in the ERA5 reanalysis, and also lack of convective clouds or in general errors in the input atmospheric and cloud profiles contribute to the differences between the simulated and observed values. Aside from the improvements in the simulations, a major advantage of the new dataset is a large number of habits that can be used to tune the data assimilation systems to perform well in different weather conditions.

Isaac Moradi↗

Analysis of Base Metal Microstructures and Mechanical Properties of a Single-Piece, Spin-Formed Forward Pressure Vessel Bulkhead

In 2012, a pathfinder forward pressure vessel bulkhead (FPVBH) for the Orion Multi-Purpose Crew Vehicle (MPCV) was fabricated using aluminum (Al) alloy 2219. The demonstration article was offered as a replacement for the baseline configuration, which at that time was a multi-piece welded construction using aluminum-lithium (Al-Li) alloy 2195. In 2014, the NASA Engineering and Safety Center (NESC) funded a Phase I effort to explore spin-forming as a manufacturing method to produce a complex-shaped, single-piece FPVBH for the crew module (CM) [1]. The primary focus of the NESC effort was to expand spin-forming technology to the fabrication of an Al-Li 2195 FPVBH. As a result, limited testing and analysis was performed on the original Al 2219 article. In this study, a sufficiently large plate of Al 2219 was not available for the fabrication of a FPVBH. Therefore, the forming blank comprised two plates (from different lots) butt welded together using a single friction stir weld. The welded forming blank was then spin formed into the FPVBH configuration and heat treated to the T62 temper. Mechanical property testing of the spin-formed 2219-T62 FPVBH revealed that the tensile properties were comparable to the Metallic Material Properties Development and Standardization (MMPDS) A-basis allowable for Al 2219-T6 wrought products. However, post-spin forming application of the standard heat treatment produced large, recrystallized grains in the material. The response varied within the two plates; one plate lot exhibited nearly complete recrystallization, while the other lot contained bands of recrystallization. Although no reduction in tensile properties was observed due to these microstructural variations, a more detailed investigation was recommended to better understand the effect of spin forming on the recrystallization mechanism and the impact on other material properties. The current study examined the microstructure and mechanical properties of the fully processed Al 2219-T62 FPVBH with emphasis on comparing differences between the two plates. Testing was limited to the cone region of the FPVBH. The two specific tasks in this study were: a) Characterization of the microstructure and mechanical properties in the two plates used in the FPVBH. b) Isolation of the impact of each step in the thermo-mechanical processing (TMP) sequence of the FPVBH on recrystallization and grain growth. Mechanical property testing sampled regions containing both large, recrystallized and small, unrecrystallized grains. Tensile strengths and elongations were equivalent in both regions and exceeded MMPDS A-basis allowables. Fracture toughness was equivalent in both regions and fracture morphology was typical of aluminum alloys. The fatigue precrack region of the fracture toughness specimens appeared more faceted in the recrystallized plate. This suggests that property testing that is more sensitive to grain size, such as fatigue crack growth rate and stress corrosion cracking, may be warranted. Alcoa reviewed the production records for the two plate lots and confirmed that composition of both plates was within the allowable range for Al 2219 and that plate processing steps were all performed within production limits. However, the Fe content was notably higher in the fully recrystallized plate, resulting in a greater volume fraction of large Fe-bearing inclusions and Al-Cu constituent particles. Alcoa did not provide details regarding plate processing variables for the two plate lots. It was surmised that deformation by hot rolling was the most accurate TMP simulation of commercial spin forming within a laboratory setting. Both hot rolling and spin forming comprise combinations of shear and compressive deformation. The through-thickness strain caused by hot rolling is symmetrical about the mid-plane, as the rollers contact both sides of the material. Shear strains are maximum at the inner and outer surfaces and trend toward zero at the mid-thickness. In contrast, spin forming utilizes a single roller on the outer surface, producing a gradient in shear stress through the thickness. Shear strains in spin-formed material are highest at the outer surface due to direct contact with the roller, and trend toward zero at the inner surface. Consequently, there will undoubtedly be some discrepancies in the mechanical response of hot-rolled and spin-formed products in the through-thickness direction. Interrupted TMP simulations were performed on remnant plate from the FPVBH forming blank in order to isolate the effects of a post-weld anneal, spin-forming deformation/thermal cycling, and solution heat treatment (SHT) on development of the recrystallized microstructures. Analysis confirmed that large, recrystallized grains formed exclusively during SHT and only after a certain deformation level was exceeded. Remnant plate from both lots that received thermal processing only did not exhibit recrystallization but exhibited fully recrystallized microstructures when processed by hot rolling. This indicates that (1) the level of deformation exceeded the critical level for recrystallization in both plates and (2) that the level of deformation during hot rolling was greater than that which accumulated during spin forming of the FPVBH. Comparison of the hot-rolled plate with the spin-formed material showed that the recrystallized grain size was larger in the FPVBH, providing further evidence that deformation levels were lower in the FPVBH. The most plausible explanation for the differing degrees of recrystallization in the two plates is particle stimulated nucleation (PSN) at the Fe-bearing inclusions and large Al-Cu constituent particles. In the plate with higher solute content, the greater volume fraction of these particles reduces the deformation level required to promote recrystallization. During spin forming the critical deformation level was likely exceeded for the higher Fe content plate resulting in a fully recrystallized microstructure. The lower Fe content plate developed a microstructure that exhibited bands of recrystallization due to the combination of a non-uniform distribution of particles and deformation. The critical deformation required for recrystallization was likely only exceeded during spin forming in regions of higher particle content. While there were differences in Fe content between these lots of Al 2219 plate, the composition of both was within defined alloy limits and Alcoa reported no anomalies during plate production. The observed differences in recrystallization after spin forming may reflect the inherent variability between these two lots of plate. The spin-forming vendor, Spincraft, reported that similar variations in recrystallized microstructures have been observed during examination of multiple spin-forming trials of a different 2xxx series aluminum alloy. Hence, tighter chemical specification limits on impurity levels in Al 2219 plate may help ensure uniform, predictable microstructures. Finally, the tensile and fracture toughness properties were not affected by the microstructural variations noted.

single-piece↗