ai-aerospace/ams_data_full_2000-2020 huggingface dataset:
Figure 4. Mechanism Strut Assembly Configuration  Figure 5. Instantaneous CTE over Temperature  Table 3. CTE Uncertainty  Ti6Al4V Annealed Al7075 -T7351 HP Invar36 LAA 1 LAA 2 Reference Value  (% of Mean CTE) --- --- --- 0.40 ppm/C  (3.7%)  Measured Flight  (% of Mean CTE) 0.11 ppm/C  (1.3%) 0.13 ppm/C  (0.6%) 0.06 ppm/C  (8.2%) 0.20 ppm/C  (1.9%) 0.32 ppm/C (3.0%)  NASA/CP—2018-219887 30
Key Design Features  Illustrated in Figure 6 are the mechanism key design features. The bolt spacers increase the bolt length  and thereby limit thermally induced bending stresses in the respective bolts. The single blade flexures,  coaxial double blade flexures, and the rotation flexure provide the necessary boundary conditions to  achieve a quasi-kinematic structure. KaRIn thermoelastic distortions are verified by analytically combining  subsystem test data into the instrument level Structural Thermal Optical model. Therefore, it is critical to  limit interface distortions, as they are not captured in the respective tests. The thermoelastic distortions due  to the MSA interfaces are removed by the presence of the strut interface bar in conjunction with the  respective radial flexures. The mechanism is nominally athermalized via an athermal fitting, illustrated in  Figure 4. The remaining radial flexures remove thermoelastic distortion uncertainty.  Flexure Design  All flexures were fabricated by electrical discharge machining (EDM), with the titanium flexures requiring  chemical etching post-machining to remove the beta-alpha recast layer. Trade studies were completed to  balance the competing design considerations, summarized in Table 4. To determine the appropriate FEM  mesh density for stress analysis, it is recommended to have at least two nodes across the fillet region and  the flexure thickness. To limit the FEM file size, the FEM mesh density was not sufficient to assess the  radial flexures stresses. The radial flexure stresses were analyzed using beam shear, beam axial, and  beam bending free body equations for the respective load cases, illustrated in Figure 7. The flexure fillet  radii were selected to limit the stress concentration factor to 1.5 [3]. The flexure margins were analyzed at  the worst-case manufacturing geometry tolerances. The bolt install torque is critical to include in the radial  flexure stress margins. Where appropriate, flexure stress margins also need to include imposed deflections  due to mechanism motion.  Figure 6. Key Design Features in Alignment Mechanism  Figure 7. Radial Flexure Free Body Diagrams NASA/CP—2018-219887 31
Commanded Motion Functional Testing  Before and after vibration testing, an auto-collimator coarsely measured the mechanism motion, where the  objective was to verify mechanism step repeatability. The hall sensors provide feedback on the motor step  integrity. While the mechanism is integrated with the vibration GSE hardware, a mirror is attached near the  top of the rotation flexure. See Figure 10, the mechanism motion was repeatable in both directions, and the  hall sensors measured no missed or skipped motor steps. A nearly perfect quadratic best-fit curve matches  both sets of data to better than 2%, which is better than expected when considering the crude test setup.  When the mechanism changes stepping direction or runs into either mechanical hard stop, there will be a  dead band zone. The test setup illustrated in Figure 15 will be used to create the calibration curves at  temperature limits for the mechanism motion, as well as measure the dead band zones and extraneous  motion about other axes; this test is planned for late January 2018.  By substituting Equation 3 into Equation 1, where ℎ and	 equal zero, the mechanism motion could be  estimated. However, this produced an over-estimate when compared to the motion actually measured, with  the difference being roughly 20%. Some variance due to the ACME lead, flexure geometry, or mechanism  geometry is expected, but not to this magnitude. The auto-collimator appeared clocked at a 20o, which  would cause a trigonometric projection error. Since we were borrowing the auto-collimator from another  team, the author did not tinker with their hardware. In addition, thermoelastic distortions due to motor selfheating would cause a similar effect seen in Figure 10. During LAA commanded step repeatability testing,  summarized in Figure 9, a quasi-isothermal environment was achieved, whereas this functional test did not.  While not important for this functional test, this oddity merits some further investigation if it is observed  during later characterization testing of the mechanism isothermal motion.  =  (3)  N: Commanded Steps, : Geared Motor Output Angle (rad), n: ACME Lead  Figure 10. Mechanism Functional Test (Pre & Post Vibration Testing) NASA/CP—2018-219887 34
Table 6. GSE FEM Mesh Density Modal Comparison  (a) Coarse Mesh, GSE FEM (b) Fine Mesh, GSE FEM Mode Frequency X-Input Y-Input Z-Input Mode Frequency X-Input Y-Input Z-Input 2 111 Hz 0% 14% 10% 2 115 Hz 0% 16% 10%  3 119 Hz 29% 0% 0% 3 123 Hz 25% 0% 0%  4 183 Hz 11% 51% 1% 4 181 Hz 1% 59% 1%  5 191 Hz 44% 12% 0% 5 213 Hz 49% 3% 1%  9 321 Hz 1% 0% 47% 9 354 Hz 1% 0% 0%  10 360 Hz 1% 0% 1% 10 422 Hz 3% 0% 60%  Figure 12: Random Vibration Test, Mechanism 1st Global Mode5 Figure 13. Sine Vibration Test, Single-Axis Accelerometer Responses 5To identify mode frequency, responses are normalized by force-limited inputs. When normalized, X/Y  results align well with predicts. Z result is higher than predict, likely due to GSE mesh density too small. NASA/CP—2018-219887 36
Figure 14. Random Vibration Test, Diagonal Strut 1st Bending Mode  Thermoelastic Distortion Testing  Figure 15 illustrates the test configuration, which is done at Precision Measurement and Instrumentation  Corp (PMIC). The test setup measures accurately the flight mechanism angular thermoelastic distortions  about the mechanism pivot axis. When gradients are kept small (less than 5°C), the GSE is designed to  not contribute to the thermoelastic distortion of concern. The 32-thermocouple-sensors are calibrated  together with 4-silicone-diode-sensors (Lakeshore DT-670-SD-70H) providing reference absolute  temperature measurements, with an accuracy better than 50 mK. A PMIC proprietary setup measures the  optical length between the laser and the detector. The base plate mounted mirror measures the bulk bias  of the test setup. The mirror mounted near the top of the rotation flexure is the primary data point, with the  mirrors mounted near the MSA intended as redundant measurements. The reduced chamber pressure is  backfilled with helium to balance thermal conduction with optical measurement needs. Quartz rods support  the test hardware with a quasi-kinematic interface. The quartz rods are mounted to a water-cooled plate. The GSE interfacing directly with flight hardware was titanium, which is the flight configuration, to ensure  the radial flexures are not overstressed. The large GSE pieces on top and bottom are both Invar36 to  minimize overall thermoelastic distortions. To eliminate thermoelastic distortion uncertainty between CTEmismatched GSE hardware bolted together, radial flexures are implemented (26 flexures in the GSE).  There are 24 temperature sensors mounted on the JPL hardware, where each segment illustrated in Figure  Figure 15. Thermoelastic Distortion Test Configuration NASA/CP—2018-219887 37
Table 7. MSA Thermoelastic Distortion Test Data Summary8 Approximate Bulk  Temperature Warming-Up Cooling-Down  Data (mdeg) Predict (mdeg) Data (mdeg) Predict (mdeg)  +80 Celsius -0.70 -0.95 + 0.45 -1.16 -1.02 + 0.45 +20 Celsius -0.20 +0.00 + 0.35 -0.10 -0.05 + 0.35 -40 Celsius +0.90 +0.49 + 0.45 +0.88 +0.46 + 0.45 -80 Celsius +1.11 +1.22 + 0.50 +1.39 +1.12 + 0.50 8Initial measurement bias was subtracted from test data results summarized in Table 7.  Figure 18. MSA Temperature Measurements  Figure 17. MSA Thermoelastic Distortion Angular Measurement  NASA/CP—2018-219887 39
Venus temperature and the resulting drill performance in each case. The work described herein represents  the first pass through the design-build-test cycle that would eventually culminate in a flight drill.  Honeybee’s HT Motor and Sensor Technology  Electric motors offer many advantages for actuation of robotic systems deployed to Solar System  destinations. They are versatile, simple to control and a variety of materials are available to suit different  environments. With support from NASA’s SBIR program beginning in 2005, Honeybee Robotics has built  and tested a number of different HT sensor and actuator technologies including a Switched Reluctance  Motor (SRM), a Brushless DC (BLDC) motor, a resolver, and a variable reluctance commutation sensor  known as PIPS (Pulse Injection Position Sensor) [2]. Based on this work, the BLDC motor was selected for  further development because it can produce more torque than the SRM, although the BLDC motor  operating temperature is limited by the Permanent Magnets (PMs) installed in the rotor. The PIPS sensor  was selected instead of the resolver to provide rotor position feedback for commutation and speed control  due to ease of fabrication, although the resolver can provide better resolution than PIPS.  Under a recent two-year SBIR project ending in 2017, Honeybee designed and built a new HT actuator  consisting of a BLDC motor, PIPS sensor and custom planetary gearbox to power a prototype rock sampling  drill for Venus. This actuator, shown in Figure 1, has been successfully dynamometer tested at both room  temperature and Venus temperature in a 1-atmosphere oven [3][4]. Remote PIPS interface electronics  located outside the oven provide Hall sensor signals compatible with commercial servo motor controllers.   Figure 1. Honeybee HT actuator with remote (i.e., room temperature) interface electronics  In the following sections the measured motor performance will be compared with theory and estimates  obtained using ANSYS Maxwell analysis software, demonstrating that losses at high temperature can be  predicted with reasonable accuracy.  Temperature Effects on Electric Motor Performance  Actuator sizing for operation in high-temperature environments must account not only for variability in the  driven load but also for reduced torque and efficiency available from the motor. The reduced performance  at elevated temperature is due to two important temperature dependencies that must be accounted for  when designing for operation across a wide temperature range. The first is the increase in electrical  resistance R of the motor coils at elevated temperature, which both increases i2R losses (self-heating) in  NASA/CP—2018-219887 42
the motor and decreases the theoretical stall current (and, therefore, stall torque) of the motor for a given  supply voltage. It can be calculated using the temperature coefficient of the magnet wire α R. The second is  the decrease in magnetic flux density B g in the air gap between the rotor and stator, which can be calculated  using the Reversible Temperature Coefficient (RTC) of the PMs. This decreases the motor torque constant  Kt, which, in turn, reduces the stall torque even further. The motor speed constant K e is decreased by the  same amount, thereby increasing the no-load speed. The overall effect is a reduction in motor maximum  power output.  The equations used to calculate theoretical motor stall torque and maximum power output and their  dependency on temperature are collected here [5][6]:  	 == (1)  	 = = = = (2)  = 2,,				1→∝ (3)  = (4)  =1 +− (5)  =,1 +− (6)  For the temperature range of interest (i.e., room temperature to 500°C), the temperature coefficients for the  Ni-plated Cu magnet wire and Sm 2Co17 PMs used in the Honeybee motor are, respectively:  = . 0038 ° ⁄ = −.060% ° ⁄ Competing motor designs may be compared on the basis of how efficiently they produce torque. For a  given design, this performance characteristic can be quantified by calculating the motor constant K m,  defined in Eq. 7.  = √= √			  √ (7)  In Eq. 7, T is the torque output of the motor when supplied with current I and R is the resistance of the  motor windings. In general, motors with a higher K m can produce more torque and they can operate for  longer periods of time before overheating. Larger motors have a clear advantage in this regard. A given  motor’s K m will be reduced at high temperature, however. Table 1 presents a comparison between  theoretical performance of Honeybee’s HT motor at room temperature and high temperature. The  calculations predict a reduction of 72% in stall torque and a reduction of 62% in maximum power output at  high temperature. Actual test results will vary due to the simplifying assumptions made in these calculations.  1 N = number of turns of wire in motor coil, L st = axial length of motor, R ro = air gap radius NASA/CP—2018-219887 43
Table 1. Comparison of theoretical motor performance at RT and Venus temperature  Parameter Symbol Room Temp. 20 °C High Temp. 482 °C Units Ratio  HT/RT  Supply Voltage Vs 48 48 V Coil Resistance R 1.05 2.74 ohms 2.61 Stall Current Ist 46 18 A 0.38 Torque Constant Kt 0.115 0.083 Nm/A 0.72 Speed Constant Ke 12.04 8.70 V/krpm 0.72 Stall Torque τst 5.26 1.46 Nm 0.28 Max Power Pmax 549 210 W 0.38 Motor Constant Km 0.112 0.050 NmW-0.5 0.45 Motor Model Validation and Simulation Results  Like ordinary electric motors, custom HT BLDC motors can be designed to meet mission requirements  using conventional modeling and simulation tools. If the temperature dependency of winding resistance and  magnetic flux density are known, motor performance at any temperature can readily be simulated. Other  temperature-dependent properties, such as magnetic permeability of the magnet steel used in the rotor and  stator, can be modelled as well if data are available. Prior to detailed modeling, rough estimates of motor  torque and efficiency can be obtained from simplified scaling calculations.  A 2-dimensional finite-element model of Honeybee’s HT motor was built using ANSYS Maxwell (Figure 2).  The motor is a 3-phase brushless DC motor with 6 slots and 4 poles. The PMs are housed in the rotor and  the coils are mounted on the stator.  Figure 2. Finite-element model of Honeybee’s HT motor  Motor Back-EMF (Test vs. Simulation)  To check the accuracy of the model, the simulated back-EMF waveforms of the unloaded motor were  compared with actual motor data captured at RT and 500°C at two different speeds. The back-emf  measurement is passive and the test equipment does not introduce any significant additional losses or  dynamics, making it especially useful in validating the motor model. To collect the waveforms, the HT motor  was placed in a 1-atmosphere oven and all three motor phases were connected to an oscilloscope. A  second conventional brushed DC motor was then used to rotate the motor armature at the desired speed  NASA/CP—2018-219887 44
by means of a feed-through in the oven door. The results indicate excellent agreement between the model  and the test data at both operating temperatures, as shown in Table 2. The measured and simulated  waveform plots at 3000 rpm are included in the Appendix.  Table 2. Unloaded motor back-EMF Vrms per phase at RT and 500°C (measured and simulated)  Motor Shaft  SpeedTest Simulation  RT (20C) HT (500C) HT/RT RT (25C) HT (500C) HT/RT 1500 rpm 5.34 Vrms 3.65 Vrms 0.68 5.28 Vrms 3.35 Vrms 0.63  3000 rpm 10.68 Vrms 7.26 Vrms 0.68 10.6 Vrms 6.74 Vrms 0.64  Calculated Motor Phase Back-EMF Constant  Ke per phase 3.56 V/krpm 2.41 V/krpm 0.68 3.53 V/krpm 2.25 V/krpm 0.64  Motor Performance Under Load (Test vs. Simulation)  The motor model was further validated by comparing simulated performance under load against actual  dynamometer test results at RT and 482°C. These simulations, however, require modelling of additional  components, including the commutation feedback sensor, motor controller and power supply, to generate  the motor excitation signal (see schematic in Figure 3). Because they are idealized representations, these  models introduce error and uncertainty that should be considered when evaluating simulation results. For  example, an ideal DC power supply can generate a steady output at 100% of the nominal voltage,  regardless of the current demand. However, the ideal model overlooks potentially significant inefficiencies  that could impact motor performance in a control system, resulting in a simulation that may overpredict  motor performance. If possible, these inefficiencies should be measured and included in the model to  improve its fidelity. Clearly, validating the standalone motor model using back-emf measurements helps  build confidence in the integrated control system model, as well.  Figure 3. Schematic of modelled components required to generate motor excitation signal  NASA/CP—2018-219887 45
The plots shown in Figure 4 through Figure 7 demonstrate excellent agreement between simulated and  measured performance at RT (where confidence in material properties is high) and reasonable agreement  at 482°C (where material properties are extrapolated).  Figure 4. Motor current vs. torque plots at RT & 482°C (measured and simulated)  Figure 5. Motor speed vs. torque plots at RT & 482°C (measured and simulated) 0123456 0 0.1 0.2 0.3 0.4 0.5 0.6Current (A) T orque (Nm)Motor Current vs. Torque Sim-RT Test-RT Sim-482C Test-482C 01000200030004000500060007000 0 0.1 0.2 0.3 0.4 0.5 0.6Speed (rpm) T orque (Nm)Motor Speed vs. Torque Sim-RT Test-RT Sim-482C Test-482C NASA/CP—2018-219887 46
Figure 6. Motor power output vs. torque plots at RT & 482°C (measured and simulated)  Figure 7. Motor efficiency vs. torque plots at RT & 482°C (measured and simulated)  Table 3 compares the measured and simulated motor torque constant K t calculated at RT and HT (482°C  for the test and 500°C for the simulation). The ratio of K t at HT to RT matches the theoretical result in  Table 1 almost exactly. 050100150200250 0 0.1 0.2 0.3 0.4 0.5 0.6Power Output (W) T orque (Nm)Motor Power vs. Torque Sim-RT Test-RT Sim-482C Test-482C 00.10.20.30.40.50.60.70.80.91 0 0.1 0.2 0.3 0.4 0.5 0.6Efficiency T orque (Nm)Motor Efficiency vs. Torque Sim-RT Test-RT Sim-482C Test-482C NASA/CP—2018-219887 47
Table 3. Motor torque constant K t at RT and HT (measured and simulated)  Test Simulation  RT (20C) HT (482C) HT/RT RT (25C) HT (500C) HT/RT 0.12 Nm/A 0.08 Nm/A 0.73 0.10 Nm/A 0.07 Nm/A 0.73  These comparisons validate the HT motor model and support the use of a similar model to aid in the design  of the flight motor for the Venus drill. The effects of high temperature on motor performance can be  estimated with reasonable confidence and, therefore, the motor design can be optimized for power output  vs. mass and volume.  The Venus Drill  Drilling Power  Drilling tools have been successfully deployed on the Moon, Mars and Venus to sample surface rock. In  these applications, drill rate of penetration (ROP) depends on several variables including the strength of  the rock (Unconfined Compressive Strength or UCS, expressed in MPa), weight on bit, drilling power, and  whether percussion is used or not [7]. For a given rock type, specific energy (SE) can be defined as the  amount of energy required to break up a unit volume of rock into fine particles that can be transported out  of the borehole. Since the efficiencies of different drilling heads, bits and feed mechanisms can vary widely,  specific energy (expressed in Whr/cc or J/mm3) provides a convenient measure to compare the  performance of different drilling systems.  Applied to a single drilling system, specific energy can be used to compare performance at different  environmental conditions, such as temperature and pressure. It can be calculated from the results of a  drilling trial by measuring the average rate of penetration (v ROP) achieved when drilling with a bit of diameter  db while controlling drilling parameters such that the average drilling power (P ave = motor power output)  remains approximately constant.  = (8)  Rearranging the equation slightly, drilling power is seen to be proportional to specific energy, rate of  penetration, and the square of the bit diameter.  = SE  (9)  Before the actuators for the Venus drill can be properly sized to deliver this power, the specific energy for  drilling at Venus conditions must be determined by conducting drilling trials at VTP, underscoring the need  for a high-fidelity prototype drill. A discussion of the design and fabrication of the prototype drill can be found  in [3] and [8]. The prototype is a HT version of a proven Honeybee design that has previously demonstrated  the desired drilling performance [9]. The selected drill design parameters are listed in Table 4.  NASA/CP—2018-219887 48
Table 4. Venus drill design parameters  Bit Diameter 2 cm  Weight on Bit 105 N  Spindle Speed 120 rpm  Spindle Torque 1.1 Nm  Net Spindle Power 13.7 W  Percussive Energy 2.0 J/blow  Percussive Frequency 980 blows/min Net Percussive Power 33 W  Target Penetration Rate 0.5 cm/min  Test Configuration Used in Drilling Trials  Following performance characterization on the dynamometer, two HT motors were integrated with the  prototype drill and a series of drilling trials were conducted at Venus temperature and pressure in JPL’s  VMTF environmental chamber. The VMTF is a heated-wall pressure chamber with an electrical feedthrough  mounted in the lid. The test article is suspended from the lid so that it hangs down inside the chamber when  the lid is installed (see Fig. 8). The high temperature environment in the VMTF severely restricts the choice  of materials that can be used for both the test article (i.e., the drill) and test instrumentation, in particular  materials suitable for electrical insulation and termination. Details of the material selection for the drill and  actuators are reported in [8].  Figure 8. VMTF lid with Venus drill installed  Drilling Test Results  Table 5 shows the average motor torque and speed for each of the two mechanisms comprising the Venus  drill under different test conditions. Average torque was calculated by taking the average motor current over  the entire drilling time and multiplying by the motor torque constant K t. Peak torque was measured directly  NASA/CP—2018-219887 49