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The Design and Engineering of Curiosity

Page 36

by Emily Lakdawalla


  Figure 9.11. Example APXS data. Analyzing the height of peaks in the spectrum (left) allows the APXS team to measure the composition of the rock, expressed as oxides (right). This sample data comes from the John Klein drill target, the location APXS was measuring in Figure 9.8 .

  Curiosity’s APXS has two main improvements over the ones on Spirit and Opportunity. It has a cooler for its detector that can reduce its temperature by 30°C, which allows APXS to operate at ambient temperatures up to –5°C. For comparison, the Mars Exploration Rover APXS works only at temperatures below –40°C, which means it mostly has to be used at night. The cooler allows Curiosity’s APXS to be used during the daytime, although it is more frequently used overnight because data quality is better, especially during the summer. (The APXS team performed regular characterizations of instrument performance at different times of day during the summer after sol 1600 to better characterize its performance over a range of temperatures.) The cooler also improves the Curiosity APXS resolution over that of the Spirit and Opportunity APXS.23

  There is also no alpha channel on Curiosity’s APXS (that is, unlike Spirit and Opportunity, Curiosity does not detect backscattered alpha particles). Throwing out the alpha channel allowed the instrument to be designed with the X-ray detector much closer to the surface; the closest range of 19 millimeters compares to 30 for the Spirit and Opportunity APXS. That, in turn, increases the sensitivity of the Curiosity APXS by a factor of 3; reduces the spot size of an APXS measurement; and speeds up data acquisition by a factor of 5. Curiosity’s APXS can get a “quick look” measurement of the major elements in only 20 minutes, and high-quality results in only 2 hours.24

  APXS and ChemCam both measure elemental compositions. Initially, APXS and ChemCam measurements of target compositions did not match very well, but the match has improved over time, especially as the ChemCam team has improved its calibration (see section 9.2.2.3).

  The APXS calibration target, like the MAHLI calibration target (see section 7.​4.​2), was covered with dust kicked up during the landing. That complicated the use of the calibration target for its intended purpose, but the APXS team adjusted their calibration about 6 months after landing to account for the presence of the dust.25 Another calibration adjustment around sol 1200 improved estimation of manganese abundances.26

  9.3.2 Using APXS

  APXS was first deployed on the rock Jake Matijevic on sol 46. It can be particularly difficult to find time for APXS observations when Curiosity’s goal is long-distance driving, because arm activities can’t take place at a new location until post-drive data are received on Earth. Initially, contact science days and driving days were mostly distinct. But on sol 102, the rover drivers performed the first “touch-and-go” observation, where the rover deploys the APXS on a target for a short integration in the morning before stowing the arm and driving away. Touch-and-goes allow the APXS team to track changes in major-element rock composition during long traverses without major impact on drive durations. One advantage to APXS over other instruments is that it consumes negligible data volume, using only 32 kilobytes of memory to store several spectra. It is also cheap in terms of power, especially if used overnight, when its detector doesn’t need to be cooled.

  APXS can be used either in a contact mode (where the arm is commanded to move APXS toward a target until the contact sensor is triggered) or in a hover mode of 5 to 20 millimeters from the target. When APXS is used in contact mode on unconsolidated materials, it may leave a print of the contact sensor in the soil (Figure 9.12). For unconsolidated materials, it is only used in contact mode in locations where the rover wheel has driven over the soil, compacting it. Touching unconsolidated materials can make the contact plate of APXS dirty, so the rover cleans it after every time it is used on soil. Cleaning APXS involves holding it down, then turning it sideways, then rotating it 180°, using CHIMRA vibration to gently shake it for 20 seconds in each pose.27

  Figure 9.12. The APXS “nose print” in the fine sand at Gobabeb as seen from Mastcam. The inner, open circle of the APXS contact plate is 29 millimeters in diameter. Mastcam image 1234MR0057070010603445E01. Credit: NASA/JPL-Caltech/MSSS.

  When examining fluffy targets or irregular surfaces on which it can’t be used in contact mode, APXS is often deployed using a technique called proximity mode, “proxmode” for short. APXS takes very short (10-second) integrations as it is brought closer to a target, signaling the arm to stop when it senses that it has reached the optimal distance of about 5 millimeters of standoff.28 When the sensor head is in contact with the target, the sources are only about 19 mm from the surface, and the sampled area has a diameter of 17 millimeters – similar in size to the diameter of a drill hole. When it is 20 millimeters from the target, the sampled area is larger, with a diameter of at most 31 millimeters. For comparison, the brush clears an area 45 millimeters or more in diameter. MAHLI images with a toolframe distance of 2 centimeters (a standard close-up observation distance) cover an area 33 millimeters wide, comparable to the APXS field of view.

  APXS is used heavily at drill sites. Typically, they brush a site near the drill location and use APXS to measure the composition of the rock to be drilled. They also perform an APXS analysis on the drill tailings (which come from the top 15 millimeters of the drill hole) as well as on the dumped pre- and post-sieve fractions of the drill powder (which represent the fine and coarse fractions of the drilled rock from 15 millimeters to the full drill depth). APXS integrations of dump sites taken before dumping can be compared to the post-dump analyses. In general, analysis of drill dump piles has yielded similar results to the pre-drill brushed spots.29

  Curiosity APXS’s rapid integration has allowed the team to regularly perform APXS raster observations. The APXS team most commonly uses rasters when examining a target that contains objects smaller than the field of view, like veins, concretions, and pebbles. Rasters are either a line of 3 observations in a row, or a 2-by-2 array with a central point for a total of 5 observations. Typically, APXS integrates for 20 minutes at each point, and then integrates overnight over the center point. The rasters help the APXS team to separate the signal of the small target of interest from the background signal.30

  The observation tray was specifically designed to be used for APXS analyses of sample material (see section 5.​7). However, the observation tray has not seen heavy use. The amount of sample that CHIMRA drops on it is small relative to the diameter and depth of the APXS sampling region, so for heavy elements like iron and magnesium in in particular, the sample being tested is thin and APXS calibrations do not apply, meaning that samples can’t be directly compared to each other.31 An unforeseen problem was the behavior of particulate material after it is dropped to the observation tray; vibrations within CHIMRA get transferred to the rover and bounce the sample away from the center of the tray almost as soon as it is emplaced. The mission has found it more useful to measure samples dumped from CHIMRA onto the ground than to continue use of the observation tray. One unforeseen use of the observation tray was a convenient location for APXS to measure the composition of airfall dust.32

  9.3.3 APXS rock compositional classes

  The APXS team classifies rocks along different compositional trends, and then uses those classifications to look for correlations between compositional variance and changes in location, elevation, and terrain types.33 They also look for correlations with rock types and compositional trends observed on Spirit and Opportunity traverses.

  Scientists who work with the APXS instruments on Curiosity and previous rovers have devised their own method of classifying rocks. The APXS team looks for clusters in major-element composition, and also for “co-variations,” patterns of groups of major elements occurring together in rocks (Figure 9.13).34 Each time the APXS team encounters a new rock that is compositionally distinct from previous observations, they name a new class for the first, best-described target. Sometimes, the APXS team identifies subclasses within larger groupings. Figure 9.13 shows two way
s in which APXS-defined rock classes cluster in composition along different axes. The top chart shows relative abundance of iron and silicon in the rocks; the bottom chart shows sodium and potassium.

  Figure 9.13. Two examples of charts used to identify clusters in APXS rock classifications. Top: rocks analyzed with APXS generally trend from silicon-poor and iron-rich (mafic rocks, like basalt) to silica-rich and iron-poor (like the very silica-rich Buckskin site). Gale soils (red triangles) are similar to the average Mars crust composition. Bottom: The association of potassium to sodium abundance in Gale rocks is more complex. Again, Gale soils are similar to average Mars crust composition, but most rocks that APXS has examined are richer in potassium; some of those are very sodium-rich, and some are very sodium-poor. Note that rock classes that overlap in one of these two diagrams may be entirely separate in the other. Graphs courtesy Mariek Schmidt.

  Because Mars dust is rich in sulfur and chlorine, the APXS team subtracts those elements from their analyses and renormalizes the remaining elements to make up 100% of the rock before comparing one rock to another (Table 9.3). The APXS rock classifications are not, directly, identifications of rock type; instead, they help the science team identify trends in the data and group rocks of similar composition together. Combined with ChemCam elemental compositions, CheMin mineralogy, and observations of rock textures from Mastcam and MAHLI, the APXS rock classifications can help tell the stories of Gale’s rocks.Table 9.3. Example APXS results from sites of different APXS team-defined compositional classes. From Thompson et al. ( 2016 ).

  Class

  Jake M

  Bathurst

  Rocknest 3

  Et Then

  John Klein

  Bell Island

  Mount Bastion

  Confidence Hills

  Buckskin

  Ronan

  Greenhorn

  Precision error

  Target

  Lowerre

  Oswego

  Thimble

  Secure

  Wernecke

  Eqalulik

  Heimdall

  Mojave

  Buckskin

  Big Sky

  Greenhorn

  Sol

  570

  472

  706

  560

  169

  323

  399

  809

  1057

  1114

  1130

  SiO2

  51.2

  43.0

  47.3

  45.4

  46.9

  42.0

  45.8

  51.8

  68.1

  43.4

  56.2

  0.64

  TiO2

  0.54

  0.89

  0.66

  0.67

  0.91

  0.85

  0.94

  1.07

  1.51

  0.93

  1.00

  0.05

  Al2O3

  16.2

  8.0

  12.0

  8.6

  8.9

  8.8

  10.8

  12.4

  6.1

  9.7

  5.5

  0.19

  Cr2O3

  0.07

  0.54

  0.21

  0.05

  0.41

  0.65

  0.19

  0.39

  0.10

  0.42

  0.34

  0.01

  FeOT

  11.5

  22.4

  16.9

  27.2

  20.5

  20.6

  13.2

  13.5

  4.4

  17.4

  9.4

  0.13

  MnO

  0.2

  0.5

  0.1

  0.3

  0.3

  0.4

  0.3

  0.3

  0.1

  0.4

  0.1

  0.01

  MgO

  3.08

  8.71

  6.37

  4.03

  9.80

  8.26

  7.17

  4.47

  3.45

  8.52

  4.77

  0.08

  CaO

  5.71

  6.13

  5.23

  3.67

  5.40

  6.54

  7.46

  4.29

  3.87

  6.87

  5.98

  0.07

  Na2O

  5.4

  2.7

  5.0

  4.1

  3.0

  3.0

  3.3

  2.8

  2.2

  2.8

  2.5

  0.14

  K2O

  2.23

  1.96

  2.16

  1.47

  0.62

  0.78

  0.97

  0.65

  0.82

  0.47

  0.44

  0.02

  P2O5

  0.6

  0.8

  0.7

  0.7

  1.0

  0.8

  0.9

  1.4

  1.3

  0.9

  1.2

  0.09

  SO3

  2.1

  3.3

  2.2

  3.2

  0.9

  6.1

  7.8

  5.8

  7.2

  6.9

  10.8

  0.1

  Cl

  0.89

  0.95

  0.71

  0.64

  1.13

  1.15

  0.97

  0.52

  0.71

  1.27

  1.54

  0.02

  Total

  98.90

  98.78

  98.84

  99.87

  98.63

  98.68

  98.87

  99.07

  99.84

  99.94

  99.76

  Ni ppm

  97

  360

  316

  194

  694

  276

  214

  839

  110

  411

  160

  10

  Zn ppm

  617

  1214

  680

  232

  794

  963

  782

  1737

  206

  273

  107

  10

  Br ppm

  33

  176

  40

  183

  401

  167

  10

  85

  58

  205

  336

  20

  K2O/Na2O

  0.41

  0.73

  0.43

  0.36

  0.20

  0.26

  0.29

  0.23

  0.38

  0.17

  0.17

  Same as above, renormalized to remove sulfate and chlorine

  SiO2

  52.8

  44.9

  48.7

  47.3

  47.8

  45.3

  50.2

  55.4

  74.1

  47.3

  64.3

  TiO2

  0.56

  0.93

  0.68

  0.70

  0.93

  0.92

  1.03

  1.14

  1.64

  1.01

  1.14

  Al2O3

  16.7

  8.3

  12.4

  8.9 />
  9.1

  9.4

  11.9

  13.3

  6.6

  10.6

  6.3

  Cr2O3

  0.07

  0.56

  0.22

  0.05

  0.42

  0.70

  0.21

  0.42

  0.11

  0.46

  0.39

  FeOT

  11.8

  23.3

  17.4

  28.3

  20.9

  22.2

  14.5

  14.4

  4.8

  19

  10.8

  MnO

  0.2

  0.5

  0.1

  0.3

  0.3

  0.4

  0.3

  0.4

  0.1

  0.4

  0.1

  MgO

  3.18

  9.10

  6.56

  4.20

  10.00

  8.90

  7.86

  4.77

  3.75

  9.28

  5.46

  CaO

  5.89

  6.40

  5.38

  3.82

  5.51

  7.05

  8.18

  4.58

  4.21

  7.49

  6.84

  Na2O

  5.6

  2.8

  5.1

  4.3

  3.1

  3.2

  3.6

  3.0

  2.4

  3.1

  2.9

  K2O

  2.30

  2.05

  2.22

  1.53

  0.63

  0.84

  1.06

  0.69

  0.89

  0.51

  0.50

  P2O5

  0.6

  0.8

  0.7

  0.7

  1.0

  0.9

  1.0

  1.5

  1.4

  1.0

  1.4

  9.3.4 Anomalies

  In general, APXS has been a healthy and productive instrument with one minor technical issue. Since launch, Curiosity’s APXS has exhibited an unusual behavior that has never been seen in any other instrument from previous generations. Occasionally, in the middle of acquiring data, it stops counting real X-ray events, instead counting only spurious X-ray counts at the lowest detectable energy. The APXS team calls this behavior “lockup.” The ultimate cause of the behavior is unknown; it happens randomly. To prevent loss of data, the team splits long APXS integrations into two parts and reboots the instrument in between them, reducing the risk that early lockup would cause the loss of all the data from a single integration.35 This mitigation strategy has prevented any loss of observations. If it happens early in an integration, lockup can affect the signal-to-noise ratio of observations, but these effects have been minimal in practice.36

 

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