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Wavefront Control Toolbox for James Webb Space Telescope Testbed

We have developed a Matlab toolbox for wavefront control of optical systems. We have applied this toolbox to the optical models of James Webb Space Telescope (JWST) in general and to the JWST Testbed Telescope (TBT) in particular, implementing both unconstrained and constrained wavefront optimization to correct for possible misalignments present on the segmented primary mirror or the monolithic secondary mirror. The optical models implemented in Zemax optical design program and information is exchanged between Matlab and Zemax via the Dynamic Data Exchange (DDE) interface. The model configuration is managed using the XML protocol. The optimization algorithm uses influence functions for each adjustable degree of freedom of the optical mode. The iterative and non-iterative algorithms have been developed to converge to a local minimum of the root-mean-square (rms) of wavefront error using singular value decomposition technique of the control matrix of influence functions. The toolkit is highly modular and allows the user to choose control strategies for the degrees of freedom to be adjusted on a given iteration and wavefront convergence criterion. As the influence functions are nonlinear over the control parameter space, the toolkit also allows for trade-offs between frequency of updating the local influence functions and execution speed. The functionality of the toolbox and the validity of the underlying algorithms have been verified through extensive simulations.

Shiri, Ron↗

Development of a Phasor Diagram Creator to Visualize the Piston and Displacer Forces in an Advanced Stirling Convertor

The steady-state, nearly sinusoidal behavior of the components in a free-piston Stirling engine allows for visualization of the forces in the system using phasor diagrams. Based on Newton's second law, F = ma, any phasor diagrams modeling a given component in a system should close if all of the acting forces have been considered. Since the Advanced Stirling Radioisotope Generator (ASRG), currently being developed for future NASA deep space missions, is made up of such nearly sinusoidally oscillating components, its phasor diagrams would also be expected to close. A graphical user interface (GUI) has been written in MATLAB (MathWorks), which takes user input data, passes it to Sage (Gedeon Associates), a one-dimensional thermodynamic modeling program used to model the Stirling convertor, runs Sage, and then automatically plots the phasor diagrams. Using this software tool, the effect of varying different Sage inputs on the phasor diagrams was determined. The parameters varied were piston amplitude, hot-end temperature, cold-end temperature, operating frequency, and displacer spring constant. These phasor diagrams offer useful insight into convertor operation and performance.

Saha, Dipanjan↗

Using 3-D Numerical Weather Data in Piloted Simulations

This report describes the process of acquiring and using 3-D numerical model weather data sets in NASA Langley's Research Flight Deck (RFD). A set of software tools implement the process and can be used for other purposes as well. Given time and location information of a weather phenomenon of interest, the user can download associated numerical weather model data. These data are created by the National Oceanic and Atmospheric Administration (NOAA) High Resolution Rapid Refresh (HRRR) model, and are then processed using a set of Mathworks' Matlab(TradeMark) scripts to create the usable 3-D weather data sets. Each data set includes radar re ectivity, water vapor, component winds, temperature, supercooled liquid water, turbulence, pressure, altitude, land elevation, relative humidity, and water phases. An open-source data processing program, wgrib2, is available from NOAA online, and is used along with Matlab scripts. These scripts are described with sucient detail to make future modi cations. These software tools have been used to generate 3-D weather data for various RFD experiments.

Daniels, Taumi S.↗

GPS Auto-Navigation Design for Unmanned Air Vehicles

A GPS auto-navigation system is designed for Unmanned Air Vehicles. The objective is to enable the air vehicle to be used as a test-bed for novel flow control concepts. The navigation system uses pre-programmed GPS waypoints. The actual GPS position, heading, and velocity are collected by the flight computer, a PC104 system running in Real-Time Linux, and compared with the desired waypoint. The navigator then determines the necessity of a heading correction and outputs the correction in the form of a commanded bank angle, for a level coordinated turn, to the controller system. This controller system consists of 5 controller! (pitch rate PID, yaw damper, bank angle PID, velocity hold, and altitude hold) designed for a closed loop non-linear aircraft model with linear aerodynamic coefficients. The ability and accuracy of using GPS data, is validated by a GPS flight. The autopilots are also validated in flight. The autopilot unit flight validations show that the designed autopilots function as designed. The aircraft model, generated on Matlab SIMULINK is also enhanced by the flight data to accurately represent the actual aircraft.

Nilsson, Caroline C. A.↗

ISS Squat and Deadlift Kinematics on the Advanced Resistive Exercise Device

Visual assessment of exercise form on the Advanced Resistive Exercise Device (ARED) on orbit is difficult due to the motion of the entire device on its Vibration Isolation System (VIS). The VIS allows for two degrees of device translational motion, and one degree of rotational motion. In order to minimize the forces that the VIS must damp in these planes of motion, the floor of the ARED moves as well during exercise to reduce changes in the center of mass of the system. To help trainers and other exercise personnel better assess squat and deadlift form a tool was developed that removes the VIS motion and creates a stick figure video of the exerciser. Another goal of the study was to determine whether any useful kinematic information could be obtained from just a single camera. Finally, the use of these data may aid in the interpretation of QCT hip structure data in response to ARED exercises performed in-flight. After obtaining informed consent, four International Space Station (ISS) crewmembers participated in this investigation. Exercise was videotaped using a single camera positioned to view the side of the crewmember during exercise on the ARED. One crewmember wore reflective tape on the toe, heel, ankle, knee, hip, and shoulder joints. This technique was not available for the other three crewmembers, so joint locations were assessed and digitized frame-by-frame by lab personnel. A custom Matlab program was used to assign two-dimensional coordinates to the joint locations throughout exercise. A second custom Matlab program was used to scale the data, calculate joint angles, estimate the foot center of pressure (COP), approximate normal and shear loads, and to create the VIS motion-corrected stick figure videos. Kinematics for the squat and deadlift vary considerably for the four crewmembers in this investigation. Some have very shallow knee and hip angles, and others have quite large ranges of motion at these joints. Joint angle analysis showed that crewmembers do not return to a normal upright stance during squat, but remain somewhat bent at the hips. COP excursions were quite large during these exercises covering the entire length of the base of support in most cases. Anterior-posterior shear was very pronounced at the bottom of the squat and deadlift correlating with a COP shift to the toes at this part of the exercise. The stick figure videos showing a feet fixed reference frame have made it visually much easier for exercise personnel and trainers to assess exercise kinematics. Not returning to fully upright, hips extended position during squat exercises could have implications for the amount of load that is transmitted axially along the skeleton. The estimated shear loads observed in these crewmembers, along with a concomitant reduction in normal force, may also affect bone loading. The increased shear is likely due to the surprisingly large deviations in COP. Since the footplate on ARED moves along an arced path, much of the squat and deadlift movement is occurring on a tilted foot surface. This leads to COP movements away from the heel. The combination of observed kinematics and estimated kinetics make squat and deadlift exercises on the ARED distinctly different from their ground-based counterparts. CONCLUSION This investigation showed that some useful exercise information can be obtained at low cost, using a single video camera that is readily available on ISS. Squat and deadlift kinematics on the ISS ARED differ from ground-based ARED exercise. The amount of COP shift during these exercises sometimes approaches the limit of stability leading to modifications in the kinematics. The COP movement and altered kinematics likely reduce the bone loading experienced during these exercises. Further, the stick figure videos may prove to be a useful tool in assisting trainers to identify exercise form and make suggestions for improvements

Newby, N.↗

Trick Simulation Environment 07

The Trick Simulation Environment is a generic simulation toolkit used for constructing and running simulations. This release includes a Monte Carlo analysis simulation framework and a data analysis package. It produces all auto documentation in XML. Also, the software is capable of inserting a malfunction at any point during the simulation. Trick 07 adds variable server output options and error messaging and is capable of using and manipulating wide characters for international support. Wide character strings are available as a fundamental type for variables processed by Trick. A Trick Monte Carlo simulation uses a statistically generated, or predetermined, set of inputs to iteratively drive the simulation. Also, there is a framework in place for optimization and solution finding where developers may iteratively modify the inputs per run based on some analysis of the outputs. The data analysis package is capable of reading data from external simulation packages such as MATLAB and Octave, as well as the common comma-separated values (CSV) format used by Excel, without the use of external converters. The file formats for MATLAB and Octave were obtained from their documentation sets, and Trick maintains generic file readers for each format. XML tags store the fields in the Trick header comments. For header files, XML tags for structures and enumerations, and the members within are stored in the auto documentation. For source code files, XML tags for each function and the calling arguments are stored in the auto documentation. When a simulation is built, a top level XML file, which includes all of the header and source code XML auto documentation files, is created in the simulation directory. Trick 07 provides an XML to TeX converter. The converter reads in header and source code XML documentation files and converts the data to TeX labels and tables suitable for inclusion in TeX documents. A malfunction insertion capability allows users to override the value of any simulation variable, or call a malfunction job, at any time during the simulation. Users may specify conditions, use the return value of a malfunction trigger job, or manually activate a malfunction. The malfunction action may consist of executing a block of input file statements in an action block, setting simulation variable values, call a malfunction job, or turn on/off simulation jobs.

Lin, Alexander S.↗

Connecting Users and Applications with Po.daac Hosted GHRSST Data

The 80+ GHRSST public datasets represent a rich resource for sea surface temperature research and applications given their time series length, resolution, spatial coverage, varying measurement types and processing levels, and availability in the full spectrum of PO.DAAC tools and services ecosystem. The PO.DAAC has created a publicly accessible recipe suite for the user community to perform straightforward yet powerful computations on GHRSST data using python recipes, Jupyter notebooks, R, Matlab, and the NCO programming language. These recipes include numerical computations for regional and global SST trends, anomaly derivations, EOF analysis, climate signal reproduction, and ocean phenology. For example, one recipe reproduces a famous SST based warming figure from the Fourth National Climate Assessment (USA) while another focuses on quantifying the regional changes in ocean SST phenology. Most are python-based while some contain hybrid calls and leverage the NCO programming interface too. All are available on the PO.DAAC user forum (https://podaac.jpl.nasa.gov/forum/) and/or via the open source NASA GitHub repository (https://github.com/nasa/podaac_tools_and_services). Several are available in the Jupyter notebook framework including podaacypy (https://github.com/nasa/podaacpy), a recipe for GHRSST granule metadata discovery and application, and more recently a Jupyter notebook developed to support data analysis and visualization of a cloud-based Zarr formatted Level 4 MUR dataset in the AWS Open Data Registry. Throughout the summer of 2020, the PO.DAAC intends to add and migrate more of its numerical recipes to the Jupyter notebook framework and publish them on its open source GitHub repository.

Gentemann, Chelle↗

Zircon, Baddeleyite, and Reidite Found in Ries Crater Suevite

Introduction: Impact events can generate superheated impact melts and even vapor [1]. In the past decade, evidence of the high temperatures and high pressures of the impact process has been found in the impact melt from terrestrial craters (e.g., Mistastin Lake [2], Meteor Crater [3]) and even on the Moon [4–5]. Often, these studies involve zircon or zirconium-bearing phases. Zircon is a particularly useful mineral, due to its robustness and durability against weathering. It is used principally for chronology, but it has a multitude of geologic applications, including geothermometry and fingerprinting magma sources. Here we focus on its capability of recording impact conditions. Grains of zircon (ZrSiO4) are converted at high temperature and/or pressure during an impact event to reidite (a high-pressure polymorph of ZrSiO4) or to tetragonal-ZrO2 + SiO2 [6]. Reidite and tertragonal-ZrO2 leave identifying relicts in the rocks, markers of the high pressures and/or temperatures these rocks underwent. Ries Crater is a 26-km-diameter peak ring crater in southern Germany that formed approximately 15 Ma [7–9]. Ries is the type locality of the polymict impact breccia known as suevite. Here, we report a microanalytical study of suevite from the Ries impact structure. These analyses are used to inform our understanding of the pressure and temperature conditions involved in creating a polymict impact breccia such as suevite in a peak ring crater. Sample Description: The sample, denoted 16RS08, originates from Otting Quarry, at 48.8777° N, 10.7921° E, approximately 17 km from the center of the Ries Crater in Germany (approximately 4 km outside the crater rim). The material recorded in sample 16RS08 is therefore considered an outer suevite. The outer suevite is a discontinuous layer of polymict impact breccia that occurs outside the central ring of Ries, up to 22 km from the center of the crater [9]. Lithic clasts in the outer suevite consist primarily of crystalline basement rocks (gneiss, granite, amphibolite), with less than 5% of lithic clasts being overlying sedimentary rocks (limestone, sandstone, shale) [9]. The thin section studied contains variably shocked lithic and mineral clasts, impact glass, and interstitial minerals that make up the matrix of the breccia (Fig. 1) [9]. Methods: We used a Cameca SX100 electron probe microanalyzer (EPMA) located in the Kuiper Materials Imaging and Characterization Facility (KMICF) at the University of Arizona to obtain 15 elemental X-ray maps of 16RS08. We next used the JEOL 7900F SEM at the Astromaterials Research & Exploration Science (ARES) at NASA Johnson Space Center (JSC) to obtain electron backscatter diffraction (EBSD) maps and energy dispersive X-ray spectroscopy (EDS) maps of select portions of the section. The EBSD data were collected under beam conditions of 20 kV, and ~9 μA, with step sizes varying from 0.05 to 2 μm. Following EBSD data collection, we processed the data using AZtecCrystal and MTEX, a free MATLAB toolbox. Results: We used the elemental X-ray maps to identify the areas of interest in the section, particularly phosphates and Zr-bearing grains. These areas of interest were then targeted for follow up EBSD and EDS analyses. We have identified, through combined EBSD and EDS analysis, the presence of zircon, reidite, and monoclinic-ZrO2 (baddeleyite) in 16RS08. In 16RS08, we have found singular grains of zircon, zircon with a vermicular baddeleyite halo (Fig. 2a), and granular zircon with reidite (Fig. 2b). The different Zr-rich phases and their corresponding textures signifies that this sample underwent a broad spectrum of pressure and temperature conditions during the impact event. For example, zircons surrounded by a vermicular baddeleyite and SiO2 intergrowth (i.e., Fig. 2a) have been shown to preserve evidence of the extremely high temperatures of impact melt, upwards of 2370 °C [2, 6]. Similarly, reidite and granular zircon (i.e., Fig. 2b) have been shown to preserve evidence of high pressure, as the transition to reidite occurs >30 GPa [3, 6]. Future Work: Next, we will process the EBSD and EDS data for these Zr-rich grains, specifically looking for indicators of cubic- or tetragonal-ZrO2 in the baddeleyite remnants and of shock-precursors to the reidite. To further inform our work, we will also obtain BSE images of these grains using a Hitachi S-4800 SEM in KMICF at the University of Arizona, as well as geochemical spot analyses via EPMA. The data collected will be used to constrain the formation conditions of the Ries Crater outer suevite. Acknowledgments: We thank Ken Domanik and Jerry Chang for their support with data collection. This work was supported by a University of Arizona RII Core Facilities Pilot Program grant and start-up funds to JJB. TME thanks A. Cavosie and N. Timms for assistance during field sampling. We acknowledge support from NASA’s Planetary Science Research program for analysis performed at JSC. References: [1] Melosh H. J. (1989) Oxf. U. Press. [2] Timms et al. (2017) EPSL 477, 52–58. [3] Cavosie et al. (2016) Geology 44:9, 703–706. [4] White et al. (2020) Nature Astr. 4, 974–978. [5] Crow C. A. et al. (2017) GCA 202, 264–284. [6] Timms et al. (2017) Earth-Sci. Rev. 165, 185–202. [7] Schmieder M. et al. (2018) GCA 220, 146–157. [8] Schwarz W. H. et al. (2020) M&PS 55:2, 312–325. [9] Stöffler et al. (2013) M&PS 43:4, 515–589.

Zircon↗

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Amini, Abolfazl M.↗

Pink Spinel in Apollo Impact Melt Rock 68815: Implications for Mg-Suite Magmatism

Introduction: Magnesian rocks from the lunar highlands are collectively termed the Mg-suite. Characterized by high (>60) Mg# (molar 100×Mg/[Mg+Fe]) in mafic phases and calcic plagioclase, these rocks are plutonic to hypabyssal in origin, and include a range of bulk mineralogies such as troctolites, dunites, norites, gabbronorites, and spinel troctolites [1]. These Mg-suite lithologies have distinct trace element concentrations and ratios that differentiate them from other lunar rock types. These rocks are ancient, generally dated to between 4.5 and 4.1 Ga, although it is unknown if this represents the full range of Mg-suite ages [1–2]. Among the Mg-suite lithologies, the spinel troctolites are relatively rare, to date only found in polymict breccias [3]. Spinel troctolites, as their name suggests, consist of calcic plagioclase and forsteritic olivine, with minor amounts of spinel (MgAl2O4), ± pyroxene and cordierite [1,4]. This form of spinel is often called ‘pink’ spinel because of its appearance in thin section under plane polarized light (PPL; Fig. 1), due to minor amounts of Cr. Spinel troctolites are generally plutonic or hypabyssal in origin (subsequently exhumed and incorporated into polymict breccias), or formed through impact processes (e.g., crystalline impact melt) [5]. A spinel-rich lithology has also been found in the Moscoviense region of the Moon via the Moon Mineralogy Mapper (M3) and lacks other mafic phases [6]. Finally, while the Mg-suite sampled thus far consists of plutonic (or hypabyssal) rocks, the question remains if such magmas could have erupted on the surface of the Moon [7]. These magmas have much lower density than mare basalts, but little sample or remote sensing evidence has been found to support the idea that extrusive Mg-suite volcanism occurred [7]. Here, we present a coordinated microanalytical study of spinel-bearing lithic and mineral clasts found in Apollo sample 68815. These data will be used to understand their petrogenesis (magmatic or impact) and modification histories, and to shed light on the existence of volcanic Mg-suite rocks. Sample Description: Apollo sample 68815 is a polymict impact melt breccia containing a variety of lithic and mineral fragments embedded in devitrified impact melt. This sample was chipped off the top of a boulder at Station 8 during the Apollo 16 mission and had an original weight of nearly 1.8 kg. In this study, we investigated two polished thin sections of 68815: 68815,17 and 68815,148, both containing spinel. Methods: The thin sections of 68815 were studied using optical light microscopy (PPL, cross-polarized light, and reflected light) with a Keyence VHX-7100 Digital Microscope. Each section was then X-ray mapped for 13–14 elements using a Cameca SX100 electron probe microanalyzer (EPMA) located in the Kuiper Materials Imaging and Characterization Facility (KMICF) at the University of Arizona. We have obtained geochemical information about the phases (olivine, plagioclase, spinel, pyroxene) in the thin sections also using the EPMA. In addition, we have used ThermoScientific Helios NanoLab 660 Focused-Ion-Beam Scanning-Electron Microscope (FIB-SEM) and a Hitachi S-4800 SEM (both in KMICF) to obtain backscattered electron (BSE) images and energy dispersive Xray spectrometry (EDS) maps of areas of interest. Using a JEOL 7900F SEM at the Astromaterials Research & Exploration Science (ARES) at NASA Johnson Space Center (JSC), we have obtained electron backscatter diffraction (EBSD) maps of the spinel-bearing portions of the thin sections. The EBSD data were collected under beam conditions of 20 kV, and ~90 μA, with step sizes varying from 0.05 to 2 μm. Following EBSD data collection, we processed the data using AZtecCrystal and MTEX, a free MATLAB toolbox. Results: We have found clasts with subophitic textures, that consist of primarily olivine and plagioclase, with minor amounts of pink Mg-Al spinel and pyroxene (Fig. 1). These clasts are up to ~1 mm in length and contain spinels up to 50 μm across. We have additionally identified pink Mg-Al spinels within the impact melt (i.e., not contained in lithic clasts) in both thin sections. In one instance, a single spinel grain is approximately 300 μm across (Fig. 1b, 2). The spinel fragments embedded in impact melt have varying compositions, typically distinct from the compositions of spinels in the lithic clasts. Spinel-Bearing Clasts: Ten lithic clasts with similar textures and mineral compositions were identified between 68815,17 (two clasts) and ,148 (eight clasts). These clasts fall into two groups. The first has skeletal olivine with intergranular plagioclase, with minor amounts of pyroxene and spinel (Fig. 1a, 2c, 2d). The spinel in these clasts are found amid the plagioclase. The second group have an intergranular texture of olivine and plagioclase, again with minor spinel and pyroxene. The second group may contain spinels surrounded by plagioclase, and spinels enclosed in olivine. Spinels located within both clast types range from no apparent Cr zoning, to reverse zoning (Cr-enrichment inward; Fig. 2d), to normal zoning (Cr-enrichment outward). In the clasts thus far investigated with EPMA, plagioclase compositions range from An# (molar 100×Ca/[Ca+Na+K]) 92–96. Olivine Mg# ranged from 77 to 94, while pyroxene had Mg# from 54–84. Spinel in the clasts have Cr# (molar 100×Cr/[Cr+Al]) 2–4 and Mg# 88–91, which is within the range of pristine and plutonic spinel troctolites [8]. Isolated Spinels: These crystals are generally euhedral to subhedral, and can exhibit reverse Cr zoning (Cr enrichment inward) or no apparent Cr zoning. The spinels thus far investigated via EPMA have Cr# 9–14 and Mg# 65–82. The Cr# for these spinels is within the range reported by [8], but have lower Mg#. Future Work: We will continue to process the EBSD data for these lithic and mineral clasts. We will also continue to characterize these clasts using EPMA and SEM. By thoroughly characterizing the various spinels and spinel-bearing clasts, we aim to constrain the petrogenesis of these minerals and rock fragments. Acknowledgments: We thank NASA for the loan of these thin sections. We thank Ken Domanik and Jerry Chang for their support with data collection. Work was supported by a University of Arizona RII Core Facilities Pilot Program grant and start-up funds to JJB. We acknowledge support from NASA’s Planetary Science Research program for analysis performed at JSC. References: [1] Shearer C. K. et al. (2015) Am. Min. 100, 294–325. [2] Borg L. E. et al. (2020) GCA 290, 312–332. [3] Warren P. H. (1993) Am. Min. 78, 360–376. [4] Dymek R. F. et al. (1976) LPS VII, 2335–2378. [5] Treiman et al. (2019) Am. Min. 104, 370–384. [6] Pieters et al. (2011) JGR: Plan. 116:E00G08. [7] Prissel et al. (2016) Icarus 277, 319–329. [8] Prissel et al. (2016) Am. Min. 101, 1624–1635.

spinel↗

Rapid Process to Generate Beam Envelopes for Optical System Analysis

The task of evaluating obstructions in the optical throughput of an optical system requires the use of two disciplines, and hence, two models: optical models for the details of optical propagation, and mechanical models for determining the actual structure that exists in the optical system. Previous analysis methods for creating beam envelopes (or cones of light) for use in this obstruction analysis were found to be cumbersome to calculate and take significant time and resources to complete. A new process was developed that takes less time to complete beam envelope analysis, is more accurate and less dependent upon manual node tracking to create the beam envelopes, and eases the burden on the mechanical CAD (computer-aided design) designers to form the beam solids. This algorithm allows rapid generation of beam envelopes for optical system obstruction analysis. Ray trace information is taken from optical design software and used to generate CAD objects that represent the boundary of the beam envelopes for detailed analysis in mechanical CAD software. Matlab is used to call ray trace data from the optical model for all fields and entrance pupil points of interest. These are chosen to be the edge of each space, so that these rays produce the bounding volume for the beam. The x and y global coordinate data is collected on the surface planes of interest, typically an image of the field and entrance pupil internal of the optical system. This x and y coordinate data is then evaluated using a convex hull algorithm, which removes any internal points, which are unnecessary to produce the bounding volume of interest. At this point, tolerances can be applied to expand the size of either the field or aperture, depending on the allocations. Once this minimum set of coordinates on the pupil and field is obtained, a new set of rays is generated between the field plane and aperture plane (or vice-versa). These rays are then evaluated at planes between the aperture and field, at a desired number of steps perceived necessary to build up the bounding volume or cone shape. At each plane, the ray coordinates are again evaluated using the convex hull algorithm to reduce the data to a minimal set. When all of the coordinates of interest are obtained for every plane of the propagation, the data is formatted into an xyz file suitable for FRED optical analysis software to import and create a STEP file of the data. This results in a spiral-like structure that is easily imported by mechanical CAD users who can then use an automated algorithm to wrap a skin around it and create a solid that represents the beam.

Howard, Joseph↗

Thermochemical Ablation Analysis of the Orion Heatshield

The Orion Multi-Purpose Crew Vehicle will one day carry astronauts to the Moon and beyond, and Orion's heatshield is a critical component in ensuring their safe return to Earth. The Orion heatshield is the structural component responsible for absorbing the intense heating environment caused by re-entry to Earth's atmosphere. The heatshield is primarily composed of Avcoat, an ablative material that is consumed during the re-entry process. Ablation is primarily characterized by two processes: pyrolysis and recession. The decomposition of in-depth virgin material is known as pyrolysis. Recession occurs when the exposed surface of the heatshield reacts with the surrounding flow. The Orion heatshield design was changed from an individually filled Avcoat honeycomb to a molded block Avcoat design. The molded block Avcoat heatshield relies on an adhesive bond to keep it attached to the capsule. In some locations on the heatshield, the integrity of the adhesive bond cannot be verified. For these locations, a mechanical retention device was proposed. Avcoat ablation was modelled in CHAR and the in-depth virgin material temperatures were used in a Thermal Desktop model of the mechanical retention device. The retention device was analyzed and shown to cause a large increase in the maximum bondline temperature. In order to study the impact of individual ablation modelling parameters on the heatshield sizing process, a Monte Carlo simulation of the sizing process was proposed. The simulation will give the sensitivity of the ablation model to each of its input parameters. As part of the Monte Carlo simulation, statistical uncertainties on material properties were required for Avcoat. Several properties were difficult to acquire uncertainties for: the pyrolysis gas enthalpy, non-dimensional mass loss rate (B´c), and Arrhenius equation parameters. Variability in the elemental composition of Avcoat was used as the basis for determining the statistical uncertainty in pyrolysis gas enthalpy and B´c. A MATLAB program was developed to allow for faster, more accurate and automated computation of Arrhenius reaction parameters. These parameters are required for a material model to be used in the CHAR ablation analysis program. This MATLAB program, along with thermogravimetric analysis (TGA) data, was used to generate uncertainties on the Arrhenius parameters for Avcoat. In addition, the TGA fitting program was developed to provide Arrhenius parameters for the ablation model of the gap filler material, RTV silicone.

Sixel, William↗

Testing and characterization of an IR CBIRD FPA

High performance IR cameras are in great demand for a variety of applications, including defense (e.g. night vision, missile detection) and space (e.g. imaging at IR wavelengths). IR focal plane arrays (FPAs) are an essential component of IR cameras. An FPA is a collection of detectors at the focal plane of an imaging device, where each detector can be thought of a pixel in the image it is detecting. The FPA in this study is based on Complimentary Barrier Infrared Detectors (CBIRDs). The CBIRD FPA was tested by imaging flat black body targets at three different temperatures, 20ºC, 25ºC, and 30ºC, with images captured using SEIR software. The important figures of merit for an IR FPA, Noise Equivalent Difference Temperature (NEDT), Noise Equivalent Irradiance (NEI), detectivity (D*), responsivity, and quantum Efficiency (QE), were extracted from the image data for each individual detector using a MATLAB program, as was the array Modulation Transfer Function MTF. The test results show a mean NEDT of 16.98mK and an MTF of about 0.34 at the Nyquist frequency. Overall, the array performs well in the MWIR range and takes quality IR images.

Das, Tanya↗

Proof Testing Aluminum and Titanium Thin-Walled Tubes for Aerospace Applications

Proof testing aerospace components aids in verifying the structural integrity of flight hardware. This process is often an important step in the certification process for critical parts. Though proof testing is a common practice at NASA and in industry, there is often a need to understand better the effectiveness of proof testing pressure systems discovering cracklike flaws or defects. Often proof tests are used in requirements and in practice as technical rationale for screening critical defects in a part in lieu of performing a non-destructive inspection. The intent of this work is to define proof test failure envelopes for thin-walled tubes composed of two materials: aluminum and titanium. Both materials are common in aerospace thin-walled tubing applications which is why these were the materials chosen for this study. The fracture mechanics software NASGRO was used to perform a parametric study on the effect of defects in thin-walled tubes subjected to proof testing. For both materials, the parameters varied in the NASGRO analyses were aspect ratio, proof test pressure, thickness, diameter, and flaw multiplier. With each case defined as a through crack or failure, the results were then pulled into MATLAB in order to parse through the data and produce failure envelope plots. Failure envelopes were created by meshing a surface in between the minimum proof pressure failing data points. As expected, based on material properties, the plots indicated the aluminum material would fail at much lower proof tests than the titanium. The parametric data and failure envelopes may be used as general qualitative insight on the effectiveness of proof testing thin-walled tubes of similar alloys.

Leah B Davis↗

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗

Identification, Uncertainty Characterization and Robust Control Synthesis Applied to Large Flexible Structures Control

This paper demonstrates an approach to frequency domain identification for the explicit purpose of designing robust H(infinity) controllers. The approach transforms raw experimental data into a plant set estimate directly usable by modern robust control design software(e.g., Matlab Robust Control Toolboxes [11][2]). A key issue in control design from raw data is the question of whether the controller will work when applied to the true system. The main feature fo this approach is that the resulting controller in guaranteed to work as designed(when applied to the true system) to a prescribed statistical confidence. While the overall methodology addresses key theoretical issues, it has at the same time been specifically designed to support practical implementations. A simulation example is included to demonstrate the overall approach.

software↗

High performance data acquisition, identification, and monitoring for active magnetic bearings

Future active magnetic bearing systems (AMB) must feature easier on-site tuning, higher stiffness and damping, better robustness with respect to undesirable vibrations in housing and foundation, and enhanced monitoring and identification abilities. To get closer to these goals we developed a fast parallel link from the digitally controlled AMB to Matlab, which is used on a host computer for data processing, identification, and controller layout. This enables the magnetic bearing to take its frequency responses without using any additional measurement equipment. These measurements can be used for AMB identification.

Herzog, Raoul↗

Swift Mission Gyro Patch and Re-Calibration Without A Calibration Campaign

The Swift spacecraft has three Two-Axis-Rate-Assemblies (TARAs) (designated as TARA 1, TARA 2, and TARA 3, and generically referred to as gyros) which until March of 2024 were all used in rate estimation as an operational workaround (dubbed “corrector-gyro”) of a software defect discovered in 2007. TARA 1 performance degraded throughout 2023 and 2024, making it an unreliable rate source. It was determined that shifting TARA 1 to be the corrector-gyro and using mainly TARAs 2 and 3, with the existing flight software (FSW) defect, would not meet performance requirements for science operations. Rather the FSW was patched to remove the defect found in 2007. This patch was delivered by the vendor in 2009, but was not fully tested or installed at that time. A decision was made in 2024 to install the patch despite limited simulation and testing capabilities. The problem facing the team was to come up with a set of alignment parameters that would work with the new patch, using data from the spacecraft operating normally in the old configuration. Calibration activities would have been possible in either the old or new FSW configuration, but were ultimately deemed unnecessary, saving staff time and pre-serving time on the spacecraft for science data collection. This paper describes the old and new FSW configurations related to gyro processing and alignment, and how the raw gyro and star tracker data from normal operation were used with a multidimensional unconstrained nonlinear minimization in MATLAB (Nelder-Mead1) to produce a fully calibrated set of gyro alignment parameters compatible with the patched FSW. Flight data is presented showing that not only did the process work, it improved performance significantly, rivaling the best slew performance of the mission to date.

MATLAB↗