NASA GRC Simulated Lunar Operations Laboratory
NASA/GRC/ Bridget Caswell. Public domain (NASA / US government work).
The Simulated Lunar Operations laboratory at NASA GRC is NASA’s terramechanics facility, and the anchor of the center’s mTRAX Planetary Exploration group in the Engine Research Building: three simulant soil tanks including a hydraulically actuated tilt bed, a drawbar pull lane, a 777 m3 motion capture volume, and alongside them the TREC single-wheel dynamometer, the Excavation Lab, the XCEL and XTERra tire rigs and the VOiD vacuum dust chamber [1][8]. Its distinguishing asset is not the bins but the terrain preparation standard that goes with them, a published procedure that produces three repeatable GRC-1 conditions whose cone index gradients bracket the values measured on the Moon by Apollo 15 and 16 [2].
A terramechanics laboratory has to put a wheel, a tool or a whole vehicle on soil whose strength is known and repeatable, so that a measured drawbar pull or sinkage can be attributed to the vehicle and not to the bed. The lunar surface makes that hard in three ways. The in-situ record is thin: the Apollo soil mechanics experiments supplied the density, strength and penetration data every later simulant is tied to [19][18]. Lunar mechanical behavior depends on one sixth gravity and on vacuum, and no vehicle-scale soil bin supplies either. And the faithful simulants exist in small quantities, so a large bin needs a different material [20][21]. The design space that results has four families: wheel dynamometers on a prepared bed, as at the Army Waterways Experiment Station for the Apollo wheels [12][13]; strength simulants at vehicle scale, which is where SLOPE sits [2]; reduced-gravity testing by parabolic flight [17][24]; and numerical contact models calibrated against bin data [6][26]. None of the first three reproduces the lunar condition in full, and the sections below say which part each gives up.
Laboratory data
Section titled “Laboratory data”| Parameter | Value |
|---|---|
| Operator | NASA GRC, mTRAX Planetary Exploration team |
| Location | Cleveland, Ohio, United States [1][8] |
| Commissioned | Not published; GRC-1 characterized 2010 |
| Type | Terramechanics, excavation and tire-environment laboratory |
| Floor area | Not published |
| Capabilities, terrain | GRC-1 lane, tilt bed, Sink Tank, DRAGON M |
| Capabilities, rigs | TREC, Excavation Lab, XCEL, XTERra, VOiD |
| Simulant or terrain | GRC-1, GRC-3, GRC-3B, Fillite, #90 silica sand, JSC-1A, pea gravel; tonnages not published [2][8] |
| Instrumentation | OptiTrack, 32 cameras, sub-mm; Rimik CP40II cone penetrometer |
| Ground truth | Cone penetrometer at 8 points per test; motion capture pose independent of odometry [1][2] |
| Fidelity limits | 1 g, Earth ambient; GRC-1 cohesionless against up to 1 kPa lunar cohesion [2] |
| Access | Open to industry, government and academia through the ERB facility manager; no lead time published |
| Cited by | VIPER [10], Scarab [3][4], Spirit [1] |
The laboratory is indoors and climate controlled, and the operators state that stable temperature and humidity are what limit variability in soil conditions between tests. Full scale vehicles, subsystems and components are all accepted, and the material in any tank can be removed and replaced with alternate granular media on request [8]. No open document gives a floor area, an article mass limit, or the tonnage held in any tank. Glenn provides its ground test facilities to industry, government and academia, with the Engine Research Building facility manager and the Test Facility Management Branch published as the route in; no fee schedule is published.
Capabilities
Section titled “Capabilities”GRC-1 lane
Section titled “GRC-1 lane”
NASA/GRC/Bridget Caswell. Public domain (NASA / US government work).
| Parameter | Value |
|---|---|
| Working volume | 12 x 3 x 0.3 m soil tank |
| Test article limits | Largest run is the 400 kg Scarab rover [3] |
| Illumination | Not published; no solar simulator |
| Simulant or terrain | GRC-1, 0.3 m bed, three conditions by cone index gradient [2][8] |
| Instrumentation | Smart-winch drawbar pull rig; OptiTrack, 32 cameras |
Vehicles traverse prepared simulant and obstacles in this tank, and a drawbar pull rig can be positioned at the end of the bed to apply a chosen resistive force through a smart winch, so tractive performance is measured as a function of drawbar pull force [8]. Published dimensions differ between NASA documents and are not reconciled in any of them: the motion capture characterization gives 11.8 x 2.9 x 0.6 m, 11.8 x 3.0 x 0.3 m and 6.7 x 4.7 x 0.2 m for the three tanks [1]; the drawbar pull procedure describes a 12 x 6 x 0.3 m bin split into two equal lanes [2]. The operator’s 2025 figures are used above.
Source: [1]. Public domain (NASA / US government work).
GRC-1 is the defining material choice. Lunar simulants such as MLS-1, JSC-1 and JSC-1A reproduce composition, but they exist only in small quantities and would need vacuum and reduced gravity to exhibit lunar mechanical strength, which is impractical at vehicle scale. GRC-1 was therefore developed at Glenn as a strength simulant for Earth ambient conditions: a cohesionless sub-angular sand, D10 0.094 mm, D60 0.390 mm, specific gravity 2.583, whose cone index gradient can be conditioned to match the values measured by the Apollo 15 and 16 cone penetrometers [2][3]. The underlying assumption is stated explicitly, that if a dry granular terrain matches the measured lunar cone penetration observations then it will respond similarly to vehicle loading in compaction and shear resistance. The operator adds that GRC-1 targets the softer, more conservative end of equatorial lunar terrain strength with respect to vehicle mobility [8].
Three standard conditions are defined by target cone index gradient G. T1: G = 5.0 +/- 0.3 kPa/mm, relative density about 41 percent, bulk density about 1.71 g/cm3, seven passes of a 4.5 kg 8 x 8 in tamper dropped from about 8 cm [8]. T2: G = 3.5 +/- 0.5 kPa/mm, about 23 percent relative density, about 1.66 g/cm3, one winch-pulled pass of a 24 x 18 in lawn roller filled with GRC-1 to 172.5 kg; T3: G = 2.5 +/- 0.5 kPa/mm, about 11 percent relative density, about 1.63 g/cm3, loosening and leveling only. The relationship between cone index gradient and relative density for air-dry GRC-1 was established over more than 180 cone penetration tests and is considered reliable to 80 percent relative density, giving G = 0.0834 D_R + 1.5811 [8]. That relation is what makes the terrain a controlled variable rather than a nuisance parameter.
Preparation is manual and procedural, in three stages. Loosening returns the soil to its original state, without which compaction accumulates and density drifts upward over a test series. The published method inserts a flat-blade shovel perpendicular to the surface to its full depth of about 25 cm, pulls the handle back to about 45 degrees to lift and break up the soil, returns the shovel upright and lifts it out, then repeats 12 to 13 cm behind the resulting valley with about 25 percent overlap, over an area at least twice as wide as the wheel track [8]. Leveling first rakes out major hills and valleys, then draws a leveling blade that is suspended from above or carried on rails at the bin sides, so the blade never rests on the soil and cannot compact it. Compaction is either the tamper, which gives fine control through drop height and pass count, or the winch-pulled roller, which is faster and more consistent but offers little density control, since cone index gradient does not increase appreciably after the first pass. Verification is by cone penetrometer at eight locations, four along each wheel track centerline, before every vehicle test, judged on the gradient over 0 to 18 cm and on the linearity of the penetration-resistance curve, with target linearity coefficients of 0 +/- 0.015 kPa/mm2 for T1 and 0 +/- 0.01 for T2 and T3 [8].
Tilt bed
Section titled “Tilt bed”
NASA/GRC/Bridget Caswell. Public domain (NASA / US government work).
| Parameter | Value |
|---|---|
| Working volume | 6 x 5 x 0.3 m tilting soil tank |
| Test article limits | The 400 kg Scarab rover has been run on it [3] |
| Simulant or terrain | GRC-1 as filled, changeable on request [8] |
| Slope | 0 to 45 degrees, hydraulic lift; usable maximum set by the angle of repose |
| Instrumentation | Inclinometer on the bed; photogrammetric best-fit plane through the surface [1][3] |
The tilt bed is the only slope capability in the laboratory, and it is set rather than measured: a hydraulic lift system takes the bed to 45 degrees of inclination, but the operator notes that in practice the maximum is limited by the angle of repose of the simulant in the bed rather than by the lift [8]. Slope angle was verified in earlier campaigns by an inclinometer on the side of the bed and, in later work, by fitting a plane through a photogrammetric point cloud of the actual soil surface [1][3]. Whether the bed can be moved under load is not published. Two cameras of the motion capture array sit at 4.9 m behind the tilt bed specifically so that the soil surface stays in view at maximum inclination [1].
Earlier documents describe the same bed as 7 x 5 x 0.3 m [2] and as approximately 6 x 4.5 m filled to 23 cm [3]; the operator’s 2025 figure is used above [8].
Sink Tank
Section titled “Sink Tank”| Parameter | Value |
|---|---|
| Working volume | 12 x 3 x 0.6 m, twice the depth of the other tanks |
| Simulant or terrain | Fillite, hollow alumino-silicate microspheres, 0.6 m bed |
| Instrumentation | OptiTrack, 32 cameras |
Source: [8].
The Sink Tank exists to produce the failure case rather than the nominal one. Fillite is a low-density hollow microsphere medium with extremely low bearing and shear strength, chosen to mimic the wind-blown dune soil found on Mars that has produced entrapped conditions for rovers, of the kind that immobilized Spirit in iron(III) sulfate deposits [1]. The operator is explicit that it is not a high-fidelity simulant: it reproduces a trafficability case, not a material.
DRAGON M
Section titled “DRAGON M”| Parameter | Value |
|---|---|
| Working volume | Dual-rail gantry over a soil bin, X 1850 mm, Y and Z 850 mm travel |
| Test article limits | Tooling rather than vehicles: auger, cone penetrometer, wheel-soil assembly |
| Simulant or terrain | GRC-3B |
| Instrumentation | Six-axis load cell, 1 kN Fy, 4 kN Fx and Fz, 250 Nm; string potentiometer |
Source: [6].
DRAGON M is the automated successor to the manual three-stage preparation procedure: a rigid steel frame bolted to the floor around a soil bin, carrying a dual-rail gantry with a vertical drive mast and a rotating tool carriage on five servo axes [6]. X runs to 5 m/s over 1850 mm at 0.02 mm resolution and 1366 N; Y and Z to 1 m/s over 850 mm at 0.02 mm and 6146 N; A rotates continuously to 600 rpm at 0.02 degrees and 109 Nm; B continuously to 57 rpm at 0.02 degrees and 48 Nm. Tools include a 101.6 mm auger, a 60 degree cone penetrometer of 500 mm2 base area, and a wheel-soil assembly on the six-axis load cell, with a string potentiometer on the Z carriage reading sinkage [6].
It both loosens and compacts the full depth of a bin and characterizes it in place, which is what a ground contact model calibration needs: drag data and cone penetrometer measurements from a single preparation [6]. Loosening trials drove 96 auger holes distributed evenly across the bin with a 101.6 mm diameter, 67.73 mm pitch, 609.6 mm bladed auger at 400 degrees/s insertion and -360 degrees/s withdrawal at a 68 mm/s feed rate, followed by manual leveling with a wooden drag. Cone penetration at nine locations showed high consistency in tip resistance between 0 and 100 mm, increasing variability beyond 100 mm attributed to the limit of auger penetration or to re-consolidation at depth, and no measurable edge effects between central and peripheral locations [6]. DRAGON M does not appear on the operator’s current capability page and its present status is unconfirmed [8].
| Parameter | Value |
|---|---|
| Working volume | Two adjacent soil tanks, each 3 x 2 x 0.75 m |
| Test article limits | Tires to 95 cm diameter; vertical load about 90 to 900 N |
| Simulant or terrain | GRC-3 in one tank, commercial #90 silica sand in the other |
| Gravity offload | Vertical tire load adjustable below vehicle weight, including offloading |
| Instrumentation | In-hub six-axis load cell, 900 N and 230 Nm; laser displacement sensor |
Source: [8].
The TRaction and Excavation Capabilities rig is the laboratory’s single-wheel dynamometer. Carriage and tire are driven independently so that forced slip from 0 to 90 percent can be commanded, at linear speeds to 6 cm/s, and the in-hub load cell captures drive force and ground force together so a net traction versus slip curve comes out of a single run; a laser displacement sensor records tire sinkage against time [8]. GRC-3 is a custom silty-sand lunar simulant of semi-angular silica particles with Bonnie silt added for strength, aimed at in-situ resource utilization work such as excavation; #90 is a poorly graded silica sand representing aeolian Martian terrain. A semi-automated rake and screed method prepares both to repeatable conditions, and as in SLOPE the simulant can be swapped on request. Static and dynamic net traction over bedrock can also be measured on the rig.
Excavation Lab
Section titled “Excavation Lab”| Parameter | Value |
|---|---|
| Working volume | GRC-3B bin 76.2 x 183 x 76 cm; pea gravel bin 61 x 91 x 51 cm |
| Test article limits | Excavation tools on the arm end; 900 lbf (4005 N) vertical as installed |
| Temperature | Lab ambient, air conditioned |
| Simulant or terrain | GRC-3B, silica sand and silt matched to lunar particle size distribution |
| Instrumentation | 156.5 mm six-axis load cell, 1300 N Fx and Fy, 3900 N Fz, 203 Nm |
Source: [8].
The Advanced Planetary Excavator is a four degree of freedom backhoe-like arm with sealed rotary joints, 360 degrees of rotation about a vertical axis, over 2 m of reach and a 3 m maximum swing radius with bucket and load cell fitted [8]. It runs on electric linear actuators fed from facility 208 VAC three-phase power converted to 325 VDC at 100 A; joint speeds are 4.67 cm/s at the shoulder, 9.37 cm/s at the elbow and 11.71 cm/s at the wrist. Mechanical maximum vertical force is 1165 lbf (5184 N), controlled as installed to 900 lbf (4005 N) vertical and 400 lbf (1780 N) horizontal [8]. Load cell full-scale uncertainty is 1.25 percent in Fx, Fy, Tx and Ty and 2.00 percent in Fz and Tz.
Tools can be lowered to a chosen digging depth and driven at controlled rates along pre-programmed paths, under joystick control or planned trajectory for repeatability, and are either tethered to wall AC power or powered from the arm at a nominal 300 VDC [8]. The bin sits on an 81 x 188 x 36 cm shaker table of 22.24 kN capacity used to compact the simulant, the dump bin stands on a 61 x 61 cm platform scale reading to 2224 N in 0.22 N steps to weigh each delivered load, and a HEPA-filtered dust enclosure surrounds the arm and bins to protect operators from the respiratory hazard [8].
| Parameter | Value |
|---|---|
| Working volume | Environmental chamber 139 cm tall x 101 cm deep x 50 cm wide |
| Test article limits | Full-scale wheel or tire; maximum size set by fixture and stroke |
| Temperature | 133 K to 370 K, liquid nitrogen or liquid carbon dioxide cooling |
| Instrumentation | Hydraulic load frame, nominal cyclic rate 1 Hz |
Source: [8].
The Extreme Cyclic Environmental Load rig is a hydraulic load frame coupled to an environmental chamber sized to enclose a full-scale wheel, used for cyclic radial compression tests against a flat plate at planetary temperatures. The 133 K figure is the lowest tested to date rather than a floor [8].
XTERra
Section titled “XTERra”| Parameter | Value |
|---|---|
| Test article limits | Tires to 95 cm diameter; vertical force to 1000 N, 2500 N peak |
| Temperature | Heated to 60 C; cooling possible, minimum temperature unknown |
| Simulant or terrain | Customizable regolith and rock terrain elements on a carousel |
| Instrumentation | Six-axis load cell at the tire; thermocouples; front and side cameras |
Source: [8].
The Extreme Terrain Endurance Rig is a single-wheel life test rig. Carousel and tire are driven independently for forced slip from 0 to 100 percent, at linear speeds on the order of 100 cm/s depending on tire load, with continuous torque to 300 Nm and 500 Nm instantaneous [8]. Vertical tire motion is recorded through an inclinometer on the mounting arm [8]. It is where durability rather than traction is measured, over representative terrain elements including rocks rather than a prepared flat bed.
| Parameter | Value |
|---|---|
| Working volume | 89 x 89 x 82.5 cm (35 x 35 x 32.5 in) internal |
| Test article limits | Sub-meter-cubed experiments; 4 ceiling mounts at 50 lb each |
| Vacuum | 1e-6 torr, with filters and a throttle valve for pumpdown with simulant in |
| Temperature | -180 to +150 C, LN2-cooled shroud with internal heaters |
| Simulant or terrain | Regolith simulant in the chamber; product not specified |
Source: [8].
The Vacuum Operations in Dust Environment chamber is the one rig in the group that supplies vacuum, and it is designed around the awkward part of that, pumping down with loose simulant present: a series of filters and a throttle valve allow a safe pumpdown with regolith in the chamber, and a thermal shroud cooled by liquid nitrogen dewars and heated by internal heaters sets the wall temperature. It is aimed at raising the technology readiness level of payloads past component-level testing. Customer feedthroughs run through fourteen DN-40 KF/QF ports, two DN-63 LF and five DN-250 LF; the DN-250 ports and two of the DN-40 ports are line of sight to the chamber center. The operator’s page states the rig was being built and was slated to be operational in summer 2024 [8].
Instrumentation
Section titled “Instrumentation”The motion capture array has grown since it was characterized. The 2022 report describes 16 Primex41 cameras on the laboratory walls: 14 at 4.3 m to clear the perimeter walkways and two at 4.9 m behind the tilt bed, so that the soil surface stays in view at maximum inclination [1]. Orientations were set at installation to maximize soil bin area in each field of view, with neighboring fields overlapping for redundancy, and four or more further cameras can be placed on tripods. The system tracks up to 300 rigid bodies in real time at a quoted plus or minus 0.1 mm and 0.5 degrees [1]. The operator’s capability page dated 31 March 2025 gives 32 cameras, 20 permanently wall-mounted and 12 on tripods, providing a full 360 degree field of view at sub-millimeter accuracy [8].
The accuracy figures were measured on the 16 camera configuration and bound the current array rather than describing it [1].
Source: [1]. Public domain (NASA / US government work).
The array was validated rather than assumed. An eight-LED OptiTrack active puck was mounted on a Thorlabs LTS300 300 mm precision linear stage under MATLAB control, elevated on aluminum extrusion and two heavy tripods to keep it out of the simulant, and stepped across its travel in 10 mm increments with about 600 OptiTrack samples taken at 100 Hz at each setpoint [1]. The bins were divided into 12 cells, the stage placed at three random locations in each, and the resulting error compared against the wand error Motive reports after calibration. Mean reported wand error was 0.17 mm against an independently calculated -0.06 +/- 0.65 mm over 2,249,327 measurements across the capture volume [1].
Bed state is measured rather than assumed. The laboratory standard is a Rimik CP40II cone penetrometer with a 30 degree apex and a 20.3 mm base diameter cone of 323 mm2 base area on a reduced-diameter shaft, pushed manually at a target 3 cm/s, recording average cone index over 10 mm depth increments to 18 cm [2].
Before the motion capture installation, vehicle tracking used stereo photogrammetry: coded two-dimensional targets on the wheels, a fixed camera pair triggering every 2 s, and GOM Pontos to recover three-dimensional target coordinates [3]. Terrain surface was recovered by projecting a speckled dot pattern onto the bed and processing the stereo pair in GOM Aramis, averaging each point over a 19 x 19 pixel square with centers 15 pixels apart, or 22.5 to 30 mm on the terrain, into a point cloud used as the sinkage datum. Camera resolution was 4272 x 2848 pixels for a spatial resolution of 1.5 to 2 mm, with calibration deviation between computed and actual coordinates averaging 0.196 pixels, roughly 0.29 to 0.39 mm [3]. For wheel-soil flow visualization the laboratory keeps a small bin with a clear glass wall against which a tire can be positioned and the soil displacement imaged through the sidewall [4][5]. The Shear Interface Imaging Analysis Tool, developed on this glass-walled bin, runs a half-width wheel at half payload against the glass at 8 frames per second and recovers soil flow magnitude, flow direction and the shear interface beneath the wheel by optical flow. It found the shear interface is set mainly by rim tangential stress rather than by drawbar load, since its extent barely changes from 5 to 20 percent slip while drawbar pull quadruples over that range, and that a walking or pushed wheel fails the soil in general shear rather than the forced rotational failure of a rolling wheel [9].
Where the laboratory sits among approaches
Section titled “Where the laboratory sits among approaches”Wheel dynamometers on a prepared bed. The Apollo wheels were selected on this basis. The Army Waterways Experiment Station compared five candidate lunar wheels in fine sand at five strength levels, and found pull coefficient independent of wheel load below about 220 N [13]. Boeing wire mesh wheel variants were then run in a crushed basalt simulant prepared to several densities [14][15]. The earlier synthesis of wheel-on-soft-soil data had set the dimensional analysis school against Bekker’s soil-value approach [12], and the stress-distribution treatment of rigid wheels gave a third basis [16]. The Glenn retrospective on the Apollo wheel reports that the Bekker analysis overpredicted the flown wheel, and that the 25 degree requirement implied roughly 59.5 percent mean slip [11]. These tests ran in air at 1 g on terrestrial soils, with cohesion supplied partly by moisture [13][15], which is the same limitation SLOPE carries with a dry cohesionless bed.
Strength simulants versus composition simulants. NASA’s simulant framework separates root simulants chosen for composition from derivatives [20]. The current user’s guide concludes that no simulant reproduces every aspect of lunar regolith and scores fourteen of them against Apollo and Luna references [21], and an earlier figure of merit scheme scored composition, size, shape and density [22]. GRC-1 is outside that scheme by design: it matches a mechanical quantity, the cone index gradient, and not composition. The lunar gradient values trace to Apollo penetration data and to terrestrial simulant tests extrapolated to lunar gravity by a bearing capacity equation [18], so the target the bed is conditioned to is itself partly inferred. Standardized ASTM testing of six lunar simulants at about 90 percent relative density found that simulants matching the lunar average particle size distribution within one standard deviation still differ substantially in shear strength and compressibility, so size distribution alone does not establish mechanical fidelity [35]. The Apollo consolidated model gives bulk density rising with depth, with an average of 1.50 g/cm3 over the top 15 cm [19].
Reduced gravity. Cone penetration resistance and its depth gradient were measured on a KC-135 at 1/6, 1 and 2 g and fall with gravity [17], which is the reason 1 g strength matching needs a stated assumption. Parabolic flight on the NRC Falcon 20 has since carried a single wheel testbed and a cone penetrometer, with a pneumatic soil preparation system that readies the bed in under 15 s [23]. A thesis built on those flights grades three Earth-based prediction methods against the lunar gravity data, and every run is a 20 to 30 second parabola that approaches quasi-steady state without settling [24]. Neither campaign carried a vehicle. A discrete element model of the same flights did not reach quantitative agreement, with drawbar pull to weight about 45 percent below experiment when sinkage was matched [25]. Cable offload for crew suits, such as ARGOS, addresses a different article, a suited human, and its fidelity analysis concerns gimbal pivot geometry rather than soil [33].
Vacuum and dust. The Glenn Lunar Dust Adhesion Bell Jar treats dust, vacuum, temperature, solar radiation and reduced gravity as five environmental factors, and the source is a design description with no measured chamber performance [32]. VOiD in this laboratory covers the same gap for payloads at sub-meter scale [8].
Contact models and simulation. Single-wheel bin data is the calibration set for models. A discrete element model of a spare MER wheel was fit to drawbar pull and sinkage at slips up to 0.5 and then predicted slips of 0.7 to 0.99, with test data existing only to 0.7 [26]. A steering model with an explicit side force term was fit in FJS-1 simulant at 1 g [27]. The JPL ROAMS simulator compared its wheel-terrain model with MER slope-slip data without a characterization of the natural terrain [28]. A regression based slip and sinkage layer in a real-time lunar simulator was fit to field data from a 21.63 kg rover, and its headline errors are fit errors and not validation errors [29]. The NASA survey of these approaches is the framing for the SLOPE calibration work [6].
Soil preparation. The manual three-stage procedure above has automated counterparts: DRAGON M [6], the flight pneumatic system [23], and an end effector that vibrates the surface to 80 percent relative density in BP-1 and LHS-1, with most densities inferred from a penetrometer correlation [31]. The Scarab rover used for most SLOPE campaigns was described at design as 280 kg with skid loader tires [30]; the angle of attack report gives 400 kg [3], and the difference is not reconciled in either source.
What it does not reproduce
Section titled “What it does not reproduce”Gravity. The laboratory operates at 1 g and has no offload rig; only TREC can relieve part of the wheel load, and it does so at the wheel rather than at the vehicle [8]. The historical workaround, still the one in use, is to build test vehicles light enough that wheel loads match what would be expected at one sixth Earth gravity, as was done for the Surveyor Lunar Roving Vehicle 6x6 and 4x4 test vehicles and for the Mobility Test Article GM-1 at one fifth of the Lunar Mobile Laboratory mass [2]. That reproduces the load but not the gravitational body force in the soil column.
Vacuum, and therefore composition-driven soil behavior, in the mobility bins. GRC-1 exists because controlling the atmospheric conditions needed for a compositional simulant to show lunar mechanical strength is impractical at this scale [2]. The trade is explicit: SLOPE reproduces terrain strength and gives up composition, particle shape beyond sub-angular, electrostatic behavior and cohesion. GRC-1 is cohesionless, against the up to 1 kPa of cohesion observed in lunar regolith [2]. VOiD supplies vacuum and dust, but in a sub-meter-cubed volume, so no vehicle-scale test is run under vacuum here [8].
The strongest lunar terrain. Over its full density range in Earth ambient conditions, GRC-1 covers four of the five lunar cone index gradient values in the National Space Science Data Center set. The one that cannot be reproduced is a high terrain strength, which the operators note does not pose a mobility challenge [2]. The facility is therefore biased conservative: it can be harder than the Moon but not easier.
Bed repeatability at scale. Because of the size of the bins the soil has to be processed in place. Removing and replacing it systematically for each test, which is the best way to guarantee a homogeneous bed, was judged unrealistic without an automated mechanical system, so the manual three-stage procedure exists as the alternative [2]. DRAGON M is the response to that limitation and its consistency falls off below 100 mm depth [6].
Motion capture accuracy is not uniform. These figures describe the 16 camera array as characterized in 2022, not the 32 camera array the operator lists in 2025 [1][8]. Mean error across the 777 m3 capture volume is submillimeter and matches the reported wand error, but measured error in some cells exceeds that mean, attributed to camera occlusion by the TREC test rig and the stairwell. The recommendation in the characterization report is that additional cameras be placed to raise accuracy in those regions [1]. Even-numbered cells, over the GRC-1 lane, more often showed greater absolute localized error than odd-numbered cells, and cell 10, on the tilt bed, showed the effect on every day of testing [1].
Slope surface is not flat. Even after hand raking, terrain height varies across the tilt bed enough that wheel position alone does not give true sinkage; the relative distance between wheel center and terrain has to be measured, which is why the photogrammetric terrain point cloud exists [3].
Test throughput. The angle of attack campaign notes that test preparation and post-processing are time-intensive enough that repeat tests were not conducted unless there was a known error [3]. Single-sample results are the norm rather than the exception.
Campaigns run there
Section titled “Campaigns run there”Drawbar pull method development, published 2017. The standing drawbar pull procedure for off-road planetary vehicles was written at SLOPE, covering terrain preparation, the three GRC-1 conditions, hitch geometry and the metrics [2]. Findings that constrain the method: cone index gradient corresponds to bulk density for dry granular soils and can be mapped to other mechanical properties, and because the cone penetrometer flew on Apollo, lunar G values can be used directly to set up lunarlike conditions on Earth. The report also establishes that hitch height matters, with a worked case for a drawbar pull coefficient of 0.2 at a hitch height of 29 percent of the wheelbase [2].
Push-pull locomotion, 2014 to 2015. An inching gait, in which the vehicle alternately extends and retracts between wheel sets rather than rolling continuously, was tested in a soil bin of approximately 8 x 3 x 0.3 m of GRC-1 against a controlled drawbar pull load [4]. Inching generated about 37 percent of vehicle weight in drawbar pull with pneumatic tires against 27 percent when rolling, and about 33 percent against 25 percent with rigid tires [4]. An earlier account of the same work reports a pull coefficient rising to 0.28 when rolling with a maximum inching force about 30 to 40 percent higher [5]. Rolling resistance was measured separately by towing a chassis on free-running wheels and found to be about 5 percent of vehicle weight [4]. The mechanism, a more efficient soil shearing method, was identified through the glass-walled single-wheel bin [4][5].
Angle of attack on slopes, published 2018. The 400 kg Scarab rover on 71 cm rigid wheels was driven on the tilt bed at 16 combinations of four slope angles and four angles of attack, in GRC-1 prepared to the loose T3-like condition of G = 2.5 +/- 0.5 kPa/mm, relative density 11 percent, bulk density 1.63 g/cm3, friction angle 31.5 degrees and essentially zero cohesion [3]. Each run was a constant 0.13 rad/s wheel speed for 30 s, tracked photogrammetrically against a projected-pattern terrain point cloud. The trajectory always trended downslope of the intended path except at 90 degrees angle of attack; at 10 degrees angle of attack the vehicle made no uphill progress on slopes above 9 degrees, and on the 15 degree slope it made no progress at either 10 or 30 degrees [3]. Sinkage increased with angle of attack, rear wheel sinkage running consistently greater than front and reaching 8 cm, and wheel slip increased with both slope angle and angle of attack, front and rear differing by under 0.5 percent [3].
Motion capture characterization, 2022. Four data sessions validated the OptiTrack installation across the 12 cells at tilt bed inclinations of 0, 10 and 20 degrees [1]. Error magnitude showed no positive correlation with tilt bed angle. The conclusion validates the system for characterizing mobility and tractive performance, with the localized-occlusion caveat above [1].
Scale model vehicle dynamics, published 2017. A modular six or eight wheel-pod vehicle was built to evaluate whether scale models can simulate lunar vehicle dynamics [7]. Wheel pods came in at 0.73 kg each, 28 percent over the 0.57 kg mass target. Turning off one pair of tires reduced distance traveled by 22 percent in one configuration and 53 percent in another, and the eight-pod configuration performed worse than the six-pod configuration [7].
Ground contact model calibration, 2025. Terramechanics, discrete element and finite-element ground contact modeling approaches are being calibrated against SLOPE single-wheel data, with GRC-1 parameter sets drawn from the literature described as a first pass toward consistency between sources [6]. DRAGON M was built to supply the consistently prepared soil volumes that this calibration needs, capturing drag test data and cone penetrometer measurements from a single preparation [6].
VIPER ground truth, published 2025 [10]. VIPER carries a torque transducer in each of its four actuated suspension joints and a quadrature encoder pattern machined into the inboard wheel rim that its wheel-well cameras can read, so it measures wheel normal force and sinkage directly rather than inferring them, a combination no prior planetary rover flew. Those measurements were designed to be inverted through Bekker and classical bearing capacity relations for cohesion, internal friction angle, bearing strength and modulus of subgrade reaction at the lunar south pole, a region so far constrained only by Apollo equatorial data and Yutu-2. The published slope versus mean wheel slip curves come from the MGRU mobility surrogate driven uphill and downhill in loose GRC-1 simulant at 15 to 20 percent relative density on the tilt bed, the terrestrial proxy for the ten 10 m rail segments across 0 to 15 degrees of slope the mission itself planned to drive [10].
What is not established
Section titled “What is not established”No document gives the commissioning date, floor area, article mass limit or simulant tonnage of the laboratory [8]. The tank dimensions disagree across NASA documents [1][2][3]. The motion capture accuracy was measured on 16 cameras and the operator now lists 32 [1][8]. The gap between GRC-1 cone index matching and lunar vehicle response has not been closed by a flight measurement: the VIPER torque and sinkage instrumentation was designed to supply one, and the published curves here are from a surrogate in the terrestrial bed [10]. No source reconciles bed-to-bed repeatability for the manual procedure with that of DRAGON M, whose status is unconfirmed [6][8]. NASA’s 2025 mobility test best practices document, a first release based on an abbreviated literature review, flags cone index gradient matching under a different gravity field as of uncertain validity, and lists no NASA standard simulant for the lunar south pole [34]. Whether 1 g strength matching predicts lunar mobility is graded in parabolic flight data that approach quasi-steady state only [24].
References
- Schepelmann, A. and Gerdts, S. (2022). Characterization of Infrared Optical Motion Tracking System in NASA's Simulated Lunar Operations (SLOPE) Laboratory
. NASA, NASA/TM-20220005304. Source
BibTeX
@techreport{schepelmann2022characterization, title = {Characterization of Infrared Optical Motion Tracking System in NASA's Simulated Lunar Operations (SLOPE) Laboratory}, author = {Schepelmann, Alexander and Gerdts, Stephen}, number = {NASA/TM-20220005304}, institution = {NASA}, year = {2022}, url = {https://ntrs.nasa.gov/citations/20220005304}, abstract = {This work characterizes the accuracy of a 16 camera OptiTrack motion tracking system installed in NASA Glenn Research Center's Simulated Lunar Operations (SLOPE) laboratory. The position of a rigid body mounted on a motorized linear stage is compared to its position reported by the motion tracking system as it travels through the facility's 777m$^3$ capture volume of interest. Experiments show that the mean error reported by the motion tracking system for the aggregate capture volume is in-line with independent measurements collected using the motion stage. Error within regions of the capture volume exceed the mean error reported by the motion tracking system, likely due to occlusion, and suggests that additional cameras should be used to increase measurement accuracy in these regions. Overall, results show that error values reported by the motion tracking system are representative of the measurement error in a collected data set and validates the system's use for characterizing the mobility and tractive performance of robots, rovers, and other vehicles for planetary exploration.} } - Creager, C., Asnani, V., Oravec, H. and Woodward, A. (2017). Drawbar Pull (DP) Procedures for Off-Road Vehicle Testing
. NASA Glenn Research Center, NASA/TP-2017-219384. Source
BibTeX
@techreport{creager2017drawbar, title = {Drawbar Pull (DP) Procedures for Off-Road Vehicle Testing}, author = {Creager, Colin and Asnani, Vivake and Oravec, Heather and Woodward, Adam}, number = {NASA/TP-2017-219384}, institution = {NASA Glenn Research Center}, year = {2017}, url = {https://ntrs.nasa.gov/citations/20170010706}, abstract = {As NASA strives to explore the surface of the Moon and Mars, there is a continued need for improved tire and vehicle development. When tires or vehicles are being designed for off-road conditions where significant thrust generation is required, such as climbing out of craters on the Moon, it is important to use a standard test method for evaluating their tractive performance. The drawbar pull (DP) test is a way of measuring the net thrust generated by tires or a vehicle with respect to performance metrics such as travel reduction, sinkage, or power efficiency. DP testing may be done using a single tire on a traction rig, or with a set of tires on a vehicle; this report focuses on vehicle DP tests. Though vehicle DP tests have been used for decades, there are no standard procedures that apply to exploration vehicles. This report summarizes previous methods employed, shows the sensitivity of certain test parameters, and provides a body of knowledge for developing standard testing procedures. The focus of this work is on lunar applications, but these test methods can be applied to terrestrial and planetary conditions as well. Section 1.0 of this report discusses the utility of DP testing for off-road vehicle evaluation and the metrics used. Section 2.0 focuses on test-terrain preparation, using the example case of lunar terrain. There is a review of lunar terrain analogs implemented in the past and a discussion on the lunar terrain conditions created at the NASA Glenn Research Center, including methods of evaluating the terrain strength variation and consistency from test to test. Section 3.0 provides details of the vehicle test procedures. These consist of a review of past methods, a comprehensive study on the sensitivity of test parameters, and a summary of the procedures used for DP testing at Glenn.} } - Creager, C. M., Jones, L. and Smith, L. M. (2017). Effect of Angle of Attack on Slope Climbing Performance
. ASCE Earth and Space Conference, NASA/TM-2017-219549. Source
BibTeX
@inproceedings{creager2017effect, title = {Effect of Angle of Attack on Slope Climbing Performance}, author = {Creager, Colin M. and Jones, Lucas and Smith, Lauren M.}, booktitle = {ASCE Earth and Space Conference}, number = {NASA/TM-2017-219549}, pages = {402-413}, institution = {NASA Glenn Research Center}, year = {2017}, doi = {10.1061/9780784479971.039}, abstract = {Ascending steep slopes is often a very difficult challenge for off-road vehicles, whether on Earth or on extraterrestrial bodies. This challenge is even greater if the surface consists of loose granular soil that does not provide much shear strength. This study investigated how the path at which a vehicle traverses a slope, specifically the angle that it is commanded to drive relative to the base of the hill (the angle of attack), can affect its performance. A vehicle was driven in loose sand at slope angles up to 15 degrees and angles of attack ranging from 10 to 90 degrees. A novel photogrammetry technique was implemented to both track vehicle motion and create a three dimensional profile of the terrain. This allowed for true wheel sinkage measurements. The study showed that though low angles of attack result in lower wheel slip and sinkage, the efficiency of the vehicle’s uphill motion increased at higher angles of attack. For slopes up to 15 degrees, a 90 degree angle of attack provided the greatest likelihood of successful ascent.} } - Creager, C. M., Johnson, K. A., Plant, M., Moreland, S. J. and Skonieczny, K. (2014). Push-Pull Locomotion for Vehicle Extrication
. Journal of Terramechanics, NASA/TM-2014-218431. Source
BibTeX
@article{creager2014push, title = {Push-Pull Locomotion for Vehicle Extrication}, author = {Creager, Colin M. and Johnson, Kyle A. and Plant, Mark and Moreland, Scott J. and Skonieczny, Krzysztof}, journal = {Journal of Terramechanics}, volume = {57}, number = {NASA/TM-2014-218431}, pages = {71-80}, institution = {NASA}, year = {2014}, doi = {10.1016/j.jterra.2014.12.001}, abstract = {For applications in which unmanned vehicles must traverse unfamiliar terrain, there often exists the risk of vehicle entrapment. Typically, this risk can be reduced by using feedback from on-board sensors that assess the terrain. This work addressed the situations where a vehicle has already become immobilized or the desired route cannot be traversed using conventional rolling. Specifically, the focus was on using push-pull locomotion in high sinkage granular material. Push-pull locomotion is an alternative mode of travel that generates thrust through articulated motion, using vehicle components as anchors to push or pull against. It has been revealed through previous research that push-pull locomotion has the capacity for generating higher net traction forces than rolling, and a unique optical flow technique indicated that this is the result of a more efficient soil shearing method. It has now been found that pushpull locomotion results in less sinkage, lower travel reduction, and better power efficiency in high sinkage material as compared to rolling. Even when starting from an "entrapped" condition, push-pull locomotion was able to extricate the test vehicle. It is the authors' recommendation that push-pull locomotion be considered as a reliable back-up mode of travel for applications where terrain entrapment is a possibility.} } - Creager, C., Moreland, S., Skonieczny, K., Johnson, K., Asnani, V. and Gilligan, R. (2012). Benefit of Push-pull Locomotion for Planetary Rover Mobility
. ASCE Earth and Space Conference. Source
BibTeX
@inproceedings{creager2012benefit, title = {Benefit of Push-pull Locomotion for Planetary Rover Mobility}, author = {Creager, Colin and Moreland, Scott and Skonieczny, Krzysztof and Johnson, Kyle and Asnani, Vivake and Gilligan, Ryan}, booktitle = {ASCE Earth and Space Conference}, pages = {11-20}, publisher = {American Society of Civil Engineers}, year = {2012}, doi = {10.1061/9780784412190.002}, abstract = {As NASA's exploration missions on planetary terrains become more aggressive, a focus on alternative modes of locomotion for rovers is necessary. In addition to climbing steep slopes, the terrain in these extreme environments is often unknown and can be extremely hard to traverse, increasing the likelihood of a vehicle or robot becoming damaged or immobilized. The conventional driving mode in which all wheels are either driven or free-rolling is very efficient on flat hard ground, but does not always provide enough traction to propel the vehicle through soft or steep terrain. This paper presents an alternative mode of travel and investigates the fundamental differences between these locomotion modes. The methods of "push-pull" locomotion discussed can be used with articulated wheeled vehicles and are identified as "walking" or "inching/inch-worming". In both cases, the braked non-rolling wheels provide increased thrust. An in-depth study of how soil reacts under a rolling wheel vs. a braked wheel was performed by visually observing the motion of particles beneath the surface. This novel technique consists of driving or dragging a wheel in a soil bin against a transparent wall while high resolution, high-rate photographs are taken. Optical flow software was then used to determine shearing patterns in the soil. Different failure modes were observed for the rolling and braked wheel cases. A quantitative comparison of inching vs. conventional driving was also performed on a full-scale vehicle through a series of drawbar pull tests in the Lunar terrain strength simulant, GRC-1. The effect of tire stiffness was also compared; typically compliant tires provide better traction when driving in soft soil, however it's been observed that rigid wheels may provide better thrust when non-rolling. Initial tests indicate up to a possible 40% increase in pull force capability at high slip when inching vs. rolling.} } - Schepelmann, A., Creager, C. M., Proctor, M. P., Johnson, K. A., Breckenridge, J. R., Elmland, A., Naghipour Ghezeljeh, P. and Oravec, H. A. (2025). An Overview of Tire-Ground Contact Modeling Approaches for Surface Mobility Applications
. NASA Glenn Research Center, NASA/TM-20250006958. Source
BibTeX
@techreport{schepelmann2025overview, title = {An Overview of Tire-Ground Contact Modeling Approaches for Surface Mobility Applications}, author = {Schepelmann, Alexander and Creager, Colin M. and Proctor, Margaret P. and Johnson, Kyle A. and Breckenridge, John R. and Elmland, Asher and Naghipour Ghezeljeh, Paria and Oravec, Heather A.}, number = {NASA/TM-20250006958}, institution = {NASA Glenn Research Center}, year = {2025}, url = {https://ntrs.nasa.gov/citations/20250006958}, abstract = {Wheels and tires serve as the critical interface between vehicles and the ground, enabling traction, force transmission, and ultimately mobility. As planetary exploration systems adopt increasingly complex wheel and tire designs, look to explore increasingly extreme terrains, and adopt increasingly aggressive performance requirements, physics-based modeling has become essential for both designing these mechanisms and predicting performance under conditions that are difficult or impractical to replicate experimentally, such as reduced gravity. This paper provides a high-level overview of commonly used modeling approaches for simulating tireground interaction, including those currently employed or under development at NASA Glenn Research Center, NASA Johnson Space Center, and the Jet Propulsion Laboratory. The paper first categorizes modeling techniques based on their fidelity and underlying assumptions. It then discusses the applications, benefits, and limitations of each approach, highlighting current knowledge gaps and modeling challenges. Finally, the paper outlines ongoing and future work aimed at addressing these limitations, including initial results from automated soil preparation experiments that support the generation of consistent physical test data and the development of terramechanics simulations for evaluating and comparing model fidelity.} } - Johnson, K., Asnani, V., Polack, J. and Plant, M. (2017). Experimental Evaluation of the Scale Model Method to Simulate Lunar Vehicle Dynamics
. International Society for Terrain-Vehicle Systems Americas Regional Conference, 20170000950. Source
BibTeX
@inproceedings{johnson2017experimental, title = {Experimental Evaluation of the Scale Model Method to Simulate Lunar Vehicle Dynamics}, author = {Johnson, Kyle and Asnani, Vivake and Polack, Jeff and Plant, Mark}, booktitle = {International Society for Terrain-Vehicle Systems Americas Regional Conference}, number = {20170000950}, institution = {NASA}, address = {Detroit, Michigan}, year = {2017}, url = {https://ntrs.nasa.gov/citations/20170000950}, abstract = {As compared to driving on Earth, the presence of lower gravity and uneven terrain on planetary bodies makes high speed driving difficult. In order to maintain ground contact and control vehicles need to be designed with special attention to dynamic response. The challenge of maintaining control on the Moon was evident during high speed operations of the Lunar Roving Vehicle (LRV) on Apollo 16, as at one point all four tires were off the ground; this event has been referred to as the Lunar Grand Prix. Ultimately, computer simulation should be used to examine these phenomena during the vehicle design process; however, experimental techniques are required for the validation and elucidation of key issues. The objectives of this study were to evaluate the methodology for developing a scale model of a lunar vehicle using similitude relationships and to test how vehicle configuration, six or eight wheel pods, and local tire compliance, soft or stiff, affect the vehicles dynamic performance. A wheel pod consists of a drive and steering transmission and wheel. The Lunar Electric Rover (LER), a human driven vehicle with a pressurized cabin, was selected as an example for which a scale model was built. The scaled vehicle was driven over an obstacle and the dynamic response was observed and then scaled to represent the full-size vehicle in lunar gravity. Loss of ground contact, in terms of vehicle travel distance with tires off the ground, was examined. As expected, local tire compliance allowed ground contact to be maintained over a greater distance. However, switching from a six-tire configuration to an eight-tire configuration with reduced suspension stiffness had a negative effect on ground contact. It is hypothesized that this was due to the increased number or frequency of impacts. The development and testing of this scale model provided practical lessons for future low-gravity vehicle development. } } - NASA Glenn Research Center. (2025). Planetary Exploration Test Facilities. nasa.gov/centers-and-facilities/glenn/planetary-exploration-test-faci...
BibTeX
@misc{grc2025planetary, title = {Planetary Exploration Test Facilities}, author = {{NASA Glenn Research Center}}, organization = {nasa.gov}, year = {2025}, url = {https://www.nasa.gov/centers-and-facilities/glenn/planetary-exploration-test-facilities/} } - Moreland, S., Skonieczny, K., Wettergreen, D., Creager, C. and Asnani, V. (2011). Soil Motion Analysis System for Examining Wheel-Soil Shearing
. Conference of the International. Source
BibTeX
@inproceedings{moreland2011soil, title = {Soil Motion Analysis System for Examining Wheel-Soil Shearing}, author = {Moreland, Scott and Skonieczny, Krzysztof and Wettergreen, David and Creager, Colin and Asnani, Vivake}, booktitle = {Conference of the International}, address = {Blacksburg, Virginia}, year = {2011}, doi = {10.1184/r1/6560918.v1} } - Rezich, E., Bickel, V. T., Francis, P. L., Rogg, A., Tardy, A., Creager, C., Oravec, H. A., Schepelmann, A., Ennico-Smith, K., Deutsch, A. and Hirabayashi, M. (2025). Investigating the Geotechnical Properties of the Lunar South Pole with NASA VIPER's Mobility System
. The Planetary Science Journal, 7. Source
BibTeX
@article{rezich2025investigating, title = {Investigating the Geotechnical Properties of the Lunar South Pole with NASA VIPER's Mobility System}, author = {Rezich, Erin and Bickel, Valentin T. and Francis, Parker L. and Rogg, Arno and Tardy, Antoine and Creager, Colin and Oravec, Heather A. and Schepelmann, Alexander and Ennico-Smith, Kimberly and Deutsch, Ariel and Hirabayashi, Masatoshi}, journal = {The Planetary Science Journal}, volume = {6}, number = {7}, pages = {169}, year = {2025}, doi = {10.3847/psj/add13f}, abstract = {Abstract The NASA Volatiles Investigating Polar Exploration Rover (VIPER) is capable of assessing the geotechnical properties of the lunar south pole’s terrain, specifically as they pertain to terramechanics or the wheel–terrain interaction, combining the rover’s mobility system and science payloads. This paper focuses on one key aspect of VIPER’s mission: the quantitative evaluation of geotechnical parameters via tractive performance by analyzing wheel and wheel–regolith interaction dynamics. As VIPER navigates the largely uncharted terrain of the Moon’s south pole, sophisticated onboard instrumentation will monitor and record detailed interactions between the rover’s wheels, chassis, and the lunar surface. These measurements will capture critical data such as wheel slip and sinkage, offering insights into the mechanical behavior of the soil under actual lunar conditions. The findings from VIPER are expected to provide a foundational understanding of the lunar south pole’s regolith mechanics, directly informing the design and navigation strategies of future lunar missions, including the deployment of more advanced rovers and crewed vehicles. By integrating lunar surface observations with the rover’s kinematic model and understood terrestrial mobility performance, the study aims to enhance predictive accuracy regarding rover tractive performance over sloped, level, and potentially volatile-rich terrain. Ground truth geotechnical assessments and proceeding mobility characterization work will serve as a cornerstone for verifying and improving both terrestrial test approaches and simulation models that underpin mission planning and risk management for subsequent explorations.} } - Asnani, V., Delap, D. and Creager, C. (2009). The Development of Wheels for the Lunar Roving Vehicle
. Journal of Terramechanics, NASA/TM-2009-215798, 20100000019. Source
BibTeX
@article{asnani2009development, title = {The Development of Wheels for the Lunar Roving Vehicle}, author = {Asnani, Vivake and Delap, Damon and Creager, Colin}, journal = {Journal of Terramechanics}, volume = {46}, number = {NASA/TM-2009-215798, 20100000019}, pages = {89-103}, institution = {NASA Glenn Research Center}, year = {2009}, doi = {10.1016/j.jterra.2009.02.005}, abstract = {The Lunar Roving Vehicle (LRV) was developed for NASA s Apollo program so astronauts could cover a greater range on the lunar surface, carry more science instruments, and return more soil and rock samples than by foot. Because of the unique lunar environment, the creation of flexible wheels was the most challenging and time consuming aspect of the LRV development. Wheels developed for previous lunar systems were not sufficient for use with this manned vehicle; therefore, several new designs were created and tested. Based on criteria set by NASA, the choices were narrowed down to two: the wire mesh wheel developed by General Motors (GM), and the hoop spring wheel developed by the Bendix Corporation. Each of these underwent intensive mechanical, material, and terramechanical analyses, and in the end, the wire mesh wheel was chosen for the LRV. Though the wire mesh wheel was determined to be the best choice for its particular application, it may be insufficient towards achieving the objectives of future lunar missions that could require higher tractive capability, increased weight capacity, or extended life. Therefore lessons learned from the original LRV wheel development and suggestions for future Moon wheel projects are offered.} } - Freitag, D. R. (1965). Wheels on soft soils: an analysis of existing data
. U.S. Army Engineer Waterways Experiment Station, Technical Report No. 3-670. Source
BibTeX
@techreport{freitag1965wheels, title = {Wheels on soft soils: an analysis of existing data}, author = {Freitag, Dean R.}, number = {Technical Report No. 3-670}, institution = {U.S. Army Engineer Waterways Experiment Station}, year = {1965}, url = {https://erdc-library.erdc.dren.mil/handle/11681/4716} } - Freitag, D. R., Green, A. J. and Melzer, K.-J. (1970). Performance Evaluation of Wheels for Lunar Vehicles (Summary Report)
. U.S. Army Engineer Waterways Experiment Station, Technical Report M-70-2. Source
BibTeX
@techreport{freitag1970performance, title = {Performance Evaluation of Wheels for Lunar Vehicles (Summary Report)}, author = {Freitag, Dean R. and Green, Andrew J. and Melzer, Klaus-Jurgen}, number = {Technical Report M-70-2}, institution = {U.S. Army Engineer Waterways Experiment Station}, year = {1970}, url = {https://ntrs.nasa.gov/citations/19700027358}, abstract = {Performance evaluation of lunar surface vehicle wheels in fine sand} } - Green, A. J. and Melzer, K.-J. (1971). Performance of Boeing LRV wheels in a lunar soil simulant. Report 1: Effect of wheel design and soil
. U.S. Army Engineer Waterways Experiment Station, Technical Report M-71-10, Report 1. Source
BibTeX
@techreport{green1971performance, title = {Performance of Boeing LRV wheels in a lunar soil simulant. Report 1: Effect of wheel design and soil}, author = {Green, Andrew J. and Melzer, Klaus-Jurgen}, number = {Technical Report M-71-10, Report 1}, institution = {U.S. Army Engineer Waterways Experiment Station}, year = {1971}, url = {https://erdc-library.erdc.dren.mil/handle/11681/29961} } - Melzer, K.-J. (1971). Performance of the Boeing LRV wheels in a lunar soil simulant. Report 2: Effects of speed, Wheel load, and soil
. U.S. Army Engineer Waterways Experiment Station, NASA-CR-129612. Source
BibTeX
@techreport{melzer1971performance, title = {Performance of the Boeing LRV wheels in a lunar soil simulant. Report 2: Effects of speed, Wheel load, and soil}, author = {Melzer, Klaus-Jurgen}, number = {NASA-CR-129612}, institution = {U.S. Army Engineer Waterways Experiment Station}, year = {1971}, url = {https://ntrs.nasa.gov/citations/19730004536}, abstract = {Two nearly identical Boeing-GM wire-mesh Lunar Roving Vehicle (LRV) wheels were laboratory tested in a lunar soil simulant to determine the influence of wheel speed and acceleration, wheel load, presence of a fender, travel direction, and soil strength on the wheel performance. Constant-slip and three types of programmed-slip tests were conducted with a single-wheel dynamometer system. Test results indicated that performance of single LRV wheels in terms of pull coefficient, power number, and efficiency were not influenced by wheel speed and acceleration, travel direction, the presence of a fender, or wheel load. Of these variables, only load influenced sinkage, which increased with increasing load. For a given slip, the pull coefficient and power number increased with increasing soil strength. However, for a given pull coefficient or slope, slip was less in firmer soil; thus, the power number decreased and efficiency increased with increasing soil strength.} } - Wong, J. Y. and Reece, A. R. (1967). Prediction of Rigid Wheel Performance Based on the Analysis of Soil-Wheel Stresses
. Journal of Terramechanics, 2. Source
BibTeX
@article{wong1967prediction, title = {Prediction of Rigid Wheel Performance Based on the Analysis of Soil-Wheel Stresses}, author = {Wong, J. Y. and Reece, A. R.}, journal = {Journal of Terramechanics}, volume = {4}, number = {2}, pages = {7--25}, year = {1967}, doi = {10.1016/0022-4898(67)90047-x} } - Costes, N. C., Cohron, G. T. and Moss, D. C. (1971). Cone Penetration Resistance Test---An Approach to Evaluating In-Place Strength and Packing Characteristics of Lunar Soils
. Lunar Science Conference. Source
BibTeX
@inproceedings{costes1971cone, title = {Cone Penetration Resistance Test---An Approach to Evaluating In-Place Strength and Packing Characteristics of Lunar Soils}, author = {Costes, Nicholas C. and Cohron, G. T. and Moss, D. C.}, booktitle = {Lunar Science Conference}, volume = {3}, pages = {1973-1987}, publisher = {The M.I.T. Press}, year = {1971}, url = {https://articles.adsabs.harvard.edu/pdf/1971LPSC....2.1973C} } - Houston, W. N. and Namiq, L. (1971). Penetration resistance of lunar soils
. Journal of Terramechanics, 1. Source
BibTeX
@article{houston1971penetration, title = {Penetration resistance of lunar soils}, author = {Houston, William N. and Namiq, L.I.}, journal = {Journal of Terramechanics}, volume = {8}, number = {1}, pages = {59-69}, publisher = {Elsevier BV}, year = {1971}, doi = {10.1016/0022-4898(71)90071-1} } - Mitchell, J. K., Carrier, W. D. I., Costes, N. C., Houston, W. N., Scott, R. F. and Hovland, H. J. (1974). Apollo soil mechanics experiment S-200
. NASA, NASA-CR-134306. Source
BibTeX
@techreport{mitchell1974apollo, title = {Apollo soil mechanics experiment S-200}, author = {Mitchell, James K. and Carrier, W. D., III and Costes, Nicholas C. and Houston, William N. and Scott, Ronald F. and Hovland, H. John}, number = {NASA-CR-134306}, institution = {NASA}, year = {1974}, url = {https://ntrs.nasa.gov/citations/19740019219}, abstract = {The physical and mechanical properties of the unconsolidated lunar surface material samples that were obtained during the Apollo missions were studied. Sources of data useful for deduction of soil information, and methods used to obtained the data are indicated. A model for lunar soil behavior is described which considers soil characteristics, density and porosity, strength, compressibility, and trafficability parameters. Lunar history and processes are considered, and a comparison is made of lunar and terrestrial soil behavior. The impact of the findings on future exploration and development of the moon are discussed, and publications resulting from lunar research by the soil mechanics team members are listed.} } - Sibille, L., Carpenter, P., Schlagheck, R. and French, R. A. (2006). Lunar Regolith Simulant Materials: Recommendations for Standardization, Production, and Usage
. NASA Marshall Space Flight Center, NASA/TP-2006-214605. Source
BibTeX
@techreport{sibille2006development, title = {Lunar Regolith Simulant Materials: Recommendations for Standardization, Production, and Usage}, author = {Sibille, Laurent and Carpenter, Paul and Schlagheck, R. and French, R. A.}, number = {NASA/TP-2006-214605}, institution = {NASA Marshall Space Flight Center}, type = {NASA Technical Publication}, year = {2006}, url = {https://ntrs.nasa.gov/citations/20060051776}, abstract = {Experience gained during the Apollo program demonstrated the need for extensive testing of surface systems in relevant environments, including regolith materials similar to those encountered on the lunar surface. As NASA embarks on a return to the Moon, it is clear that the current lunar sample inventory is not only insufficient to support lunar surface technology and system development, but its scientific value is too great to be consumed by destructive studies. Every effort must be made to utilize standard simulant materials, which will allow developers to reduce the cost, development, and operational risks to surface systems. The Lunar Regolith Simulant Materials Workshop held in Huntsville, AL, on January 24 26, 2005, identified the need for widely accepted standard reference lunar simulant materials to perform research and development of technologies required for lunar operations. The workshop also established a need for a common, traceable, and repeatable process regarding the standardization, characterization, and distribution of lunar simulants. This document presents recommendations for the standardization, production and usage of lunar regolith simulant materials.} } - Slabic, A., Gruener, J. E., Kovtun, R. N., Rickman, D. L., Sibille, L., Oravec, H. A., Edmunson, J. and Keprta, S. (2024). Lunar Regolith Simulant User's Guide, Revision A
. NASA, NASA/TM-20240011783. Source
BibTeX
@techreport{slabic2024lunar, title = {Lunar Regolith Simulant User's Guide, Revision A}, author = {Slabic, Ane and Gruener, John E. and Kovtun, Rostislav N. and Rickman, Douglas L. and Sibille, Laurent and Oravec, Heather A. and Edmunson, Jennifer and Keprta, Sean}, number = {NASA/TM-20240011783}, institution = {NASA}, year = {2024}, url = {https://ntrs.nasa.gov/citations/20240011783}, abstract = {This guide is titled Lunar Regolith Simulant User's Guide, Rev A, and two points need to be made about the title. First, is the use of the term "regolith". During the Apollo Program, the term "soil" was used for taking a sample of the loose material on the surface, and then cataloging that sample in the lunar curation database as a "soil sample". By the 1980s, the term "regolith" gained favor by lunar scientists. In the Lunar Sourcebook (Heiken et al., 1991), regolith is defined as "a general term for the layer or mantle of fragmental and unconsolidated rock material, whether residual or transported and of highly varied character, that nearly everywhere forms the surface of the land and overlies or covers bedrock". Regolith is a terrestrial term that seems to go back to 1897, according to a recent paper by Huggett (2023). Huggett summed up his paper by writing, "soil and regolith are one in the same". "Regolith" will mostly be used throughout this guide, as it tends to separate in one's mind the unique nature of the Moon's surface when compared to the inherent bias humans have in their mind when they hear and use the word "soil". When referring to Apollo samples, "soil" is used for historical context and in some places the simple term "lunar simulant" is also used. Secondly, Rev A is used in the title because NASA released its first Lunar Regolith Simulant User's Guide in 2010, near the end of NASA's Constellation Program (Schrader et al., 2010). This guide follows in the pattern of that first guide and will be updated on a periodic basis as new simulants are created, characterized and used, and as new information emerges about the Moon's regolith due to new lunar exploration missions, both robotic and human.} } - Rickman, D., Hoelzer, H., Carpenter, P., Sibille, L., Howard, R. and Owens, C. (2007). A Quantitative Method for Evaluating Regolith Simulants
. AIP Conference. Source
BibTeX
@inproceedings{rickman2007quantitative, title = {A Quantitative Method for Evaluating Regolith Simulants}, author = {Rickman, Doug and Hoelzer, Hans and Carpenter, Paul and Sibille, Laurent and Howard, Rick and Owens, Charles}, booktitle = {AIP Conference}, volume = {880}, pages = {957-963}, publisher = {AIP}, year = {2007}, doi = {10.1063/1.2437539}, abstract = {Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Doug Rickman, Hans Hoelzer, Paul Carpenter, Laurent Sibille, Rick Howard, Charles Owens; A Quantitative Method for Evaluating Regolith Simulants. AIP Conf. Proc. 30 January 2007; 880 (1): 957–963. https://doi.org/10.1063/1.2437539 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search} } - Skonieczny, K., Niksirat, P. and Nassiraei, A. A. F. (2019). Rapid automated soil preparation for testing planetary rover-soil interactions aboard reduced-gravity aircraft
. Journal of Terramechanics. Source
BibTeX
@article{skonieczny2019rapid, title = {Rapid automated soil preparation for testing planetary rover-soil interactions aboard reduced-gravity aircraft}, author = {Skonieczny, Krzysztof and Niksirat, Parna and Nassiraei, Amir Ali Forough}, journal = {Journal of Terramechanics}, volume = {83}, pages = {35-44}, publisher = {Elsevier BV}, year = {2019}, doi = {10.1016/j.jterra.2019.03.001} } - Daca, A. (2023). Predicting Planetary Rover Mobility in Reduced Gravity Using 1-g Experiments
. Unpublished. Source
BibTeX
@phdthesis{daca2023predicting, title = {Predicting Planetary Rover Mobility in Reduced Gravity Using 1-g Experiments}, author = {Daca, Adriana}, journal = {Unpublished}, school = {Concordia University}, address = {Montreal, Quebec, Canada}, type = {PhD thesis}, month = {February}, year = {2023}, doi = {10.13140/rg.2.2.12718.28485}, abstract = {Traversing granular regolith, especially in reduced gravity environments, remains a potential challenge for wheeled rovers. Mitigating hazards for planetary rovers requires testing in representative environments, but direct Earth-based testing fails to account for the effect of reduced gravity on the soil itself. Here, experimental apparatus and techniques for reduced-gravity flight testing are used to systematically evaluate three existing Earth-based testing methods and develop guidelines for their use and interpretation: (i) reduced-weight testing, (ii) matching soil testing instrument response through soil simulant design, and (iii) granular scaling laws (GSL). \nExperimentation campaigns flying reduced-gravity parabolas, with soil and wheel both in lunar-g, have shown reductions in net traction of 20% or more and increases in sinkage of up to 40% compared to Earth-based testing methods (i) and (ii). Scaled-wheel testing, according to GSL (method iii) has shown better agreement with reduced-g tests (less than 10% error) and also tends to err on the side of conservative predictions. \nLimitations of GSL are investigated including a recently proposed cohesion constraint (that the wheel radius ratio must be the inverse of the gravity ratio) and the effects of wheel size and aspect ratio on GSL’s accuracy. It was found that the cohesion constraint can most likely be ignored for mildly cohesive soils such as lunar regolith. Limits on wheel sizes and aspect ratio variation are also proposed. \nThe application of GSL to planetary rover testing is demonstrated through two studies undertaken in collaboration with NASA’s Jet Propulsion Laboratory. One study compares wheel designs for a skid-steer lunar rover in single-wheel tests scaled by GSL, demonstrating that diagonal grousers improve turning performance without requiring larger wheels. The second study involves application of GSL to the design of two reconfigurable test platforms for evaluating steep-terrain mobility performance. \nAnother aspect of rover mobility testing—normal force control in single-wheel testbeds—is also investigated. An improved method for single-wheel testing, using a 4-bar mechanism, essentially eliminates normal force oscillations from frictional vertical sliders. \nFinally, guidelines for conducting and interpreting 1-g mobility tests for lunar rovers are presented, and potential avenues for future research are outlined.} } - Karpman, E. (2019). Discrete Element Modelling for Wheel-Soil Interaction and the Analysis of the Effect of Gravity
. Journal of Terramechanics. Source
BibTeX
@article{karpman2019discrete, title = {Discrete Element Modelling for Wheel-Soil Interaction and the Analysis of the Effect of Gravity}, author = {Karpman, Eric}, journal = {Journal of Terramechanics}, volume = {91}, pages = {139-153}, publisher = {Elsevier BV}, school = {McGill University}, address = {Montreal}, year = {2019}, doi = {10.1016/j.jterra.2020.06.002} } - Johnson, J. B., Kulchitsky, A. V., Duvoy, P., Iagnemma, K., Senatore, C., Arvidson, R. E. and Moore, J. (2015). Discrete element method simulations of Mars Exploration Rover wheel performance
. Astrobiology. Source
BibTeX
@article{johnson2015discrete, title = {Discrete element method simulations of Mars Exploration Rover wheel performance}, author = {Johnson, Jerome B. and Kulchitsky, Anton V. and Duvoy, Paul and Iagnemma, Karl and Senatore, Carmine and Arvidson, Raymond E. and Moore, Jeffery}, journal = {Astrobiology}, volume = {62}, pages = {31-40}, publisher = {Elsevier BV}, year = {2015}, doi = {10.1016/j.jterra.2015.02.004}, abstract = {Mars Exploration Rovers (MERs) experienced mobility problems during traverses. Three-dimensional discrete element method (DEM) simulations of MER wheel mobility tests for wheel slips of i = 0, 0.1, 0.3, 0.5, 0.7, 0.9, and 0.99 were done to examine high wheel slip mobility to improve the ARTEMIS MER traverse planning tool. Simulations of wheel drawbar pull and sinkage MIT data for i ⩽ 0.5 were used to determine DEM particle packing density (0.62) and contact friction (0.8) to represent the simulant used in mobility tests. The DEM simulations are in good agreement with MIT data for i = 0.5 and 0.7, with reasonable but less agreement at lower wheel slip. Three mobility stages include low slip ( i < 0.3) controlled by soil strength, intermediate slip ( i ∼ 0.3–0.6) controlled by residual soil strength, and high slip ( i > 0.6) controlled by residual soil strength and wheel sinkage depth. Equilibrium sinkage occurred for i < 0.9, but continuously increased for i = 0.99. Improved DEM simulation accuracy of low-slip mobility can be achieved using polyhedral particles, rather than tri-sphere particles, to represent soil. The DEM simulations of MER wheel mobility can improve ARTEMIS accuracy.} } - Ishigami, G., Miwa, A., Nagatani, K. and Yoshida, K. (2007). Terramechanics-based model for steering maneuver of planetary exploration rovers on loose soil
. Journal of Field Robotics, 3. Source
BibTeX
@article{ishigami2007terramechanics, title = {Terramechanics-based model for steering maneuver of planetary exploration rovers on loose soil}, author = {Ishigami, Genya and Miwa, Akiko and Nagatani, Keiji and Yoshida, Kazuya}, journal = {Journal of Field Robotics}, volume = {24}, number = {3}, pages = {233-250}, publisher = {Wiley}, year = {2007}, doi = {10.1002/rob.20187}, abstract = {Abstract This paper presents analytical models to investigate the steering maneuvers of planetary exploration rovers on loose soil. The models are based on wheel‐soil interaction mechanics, or terramechanics, with which the traction and disturbance forces of a wheel are evaluated for various slip conditions. These traction forces are decomposed into the longitudinal and lateral directions of the wheel. The latter component, termed the side force has a major influence in characterizing the steering maneuvers of the rover. In this paper, the wheel‐soil mechanics models are developed with particular attention to the side force and the validity of the model is confirmed by using a single‐wheel test bed. The motion profile of the entire rover is numerically evaluated by incorporating the wheel‐soil models into an articulated multibody model that describes the motion dynamics of the vehicle's body and chassis. Steering maneuvers are investigated under different steering angles by using a four‐wheel rover test bed on simulated lunar soil regolith simulant. The experimental results are compared with the simulation results using the corresponding model parameters. The proposed wheel‐and‐vehicle model demonstrates better accuracy in predicting steering maneuvers as compared to the conventional kinematics‐based model. © 2006 Wiley Periodicals, Inc.} } - Sohl, G. and Jain, A. (2005). Wheel-terrain contact modeling in the ROAMS planetary rover simulation
. International Conference on Multibody Systems, Nonlinear Dynamics, and Control, Parts A, B, and C. Source
BibTeX
@inproceedings{sohl2005wheel, title = {Wheel-terrain contact modeling in the ROAMS planetary rover simulation}, author = {Sohl, Garett and Jain, Abhinandan}, booktitle = {International Conference on Multibody Systems, Nonlinear Dynamics, and Control, Parts A, B, and C}, pages = {89-97}, publisher = {ASMEDC}, year = {2005}, doi = {10.1115/detc2005-85620}, abstract = {This paper describes wheel-terrain contact modeling in the ROAMS physics-based simulator for planetary surface exploration rover vehicles. ROAMS models a wide range of rover systems and provides a user interface to a simulated rover. The wheel-terrain interaction is of primary interest during rover motion over rough terrain. The wheel-terrain contact model must provide physically realistic behavior without being too computationally intensive for real-time simulation. Physically realistic behavior may be defined using empirical data and ROAMS provides mechanisms for tuning the contact model parameters to match this data. In cases where empirical data is non-existent or there are large amounts of uncertainty, ROAMS can be used to extrapolate a range of behaviors based on physical parameters. The ROAMS simulator can be used in stand-alone mode, for closed-loop simulation with on-board software or for operator-in-the-loop simulations.} } - Kern, J. M., Hurrell, J. M., Santra, S., Takehana, K., Uno, K. and Yoshida, K. (2025). Data-Driven Terramechanics Approach Towards a Realistic Real-Time Simulator for Lunar Rovers
. arXiv preprint. Source
BibTeX
@article{kern2026data, title = {Data-Driven Terramechanics Approach Towards a Realistic Real-Time Simulator for Lunar Rovers}, author = {Kern, Jakob M. and Hurrell, James M. and Santra, Shreya and Takehana, Keisuke and Uno, Kentaro and Yoshida, Kazuya}, journal = {arXiv preprint}, pages = {662-668}, year = {2025}, doi = {10.1109/isparo66239.2025.11436587}, abstract = {High-fidelity simulators for the lunar surface provide a digital environment for extensive testing of rover operations and mission planning. However, current simulators focus on either visual realism or physical accuracy, which limits their capability to replicate lunar conditions comprehensively. This work addresses that gap by combining high visual fidelity with realistic terrain interaction for a realistic representation of rovers on the lunar surface. Because direct simulation of wheel-soil interactions is computationally expensive, a data-driven approach was adopted, using regression models for slip and sinkage from data collected in both full-rover and single-wheel experiments and simulations. The resulting regression-based terramechanics model accurately reproduced steady-state and dynamic slip, as well as sinkage behavior, on flat terrain and slopes up to 20°, with validation against field test results. Additionally, improvements were made to enhance the realism of terrain deformation and wheel trace visualization. This method supports real-time applications that require physically plausible terrain response alongside high visual fidelity.} } - Bartlett, P., Wettergreen, D. and Whittaker, W. L. (2008). Design of the Scarab Rover for Mobility and Drilling in the Lunar Cold Traps
. International Symposium on Artificial Intelligence, Robotics and Automation in Space. Source
BibTeX
@inproceedings{bartlett2008design, title = {Design of the Scarab Rover for Mobility and Drilling in the Lunar Cold Traps}, author = {Bartlett, Paul and Wettergreen, David and Whittaker, William L.}, booktitle = {International Symposium on Artificial Intelligence, Robotics and Automation in Space}, address = {Los Angeles, California}, year = {2008}, url = {https://www.ri.cmu.edu/pub_files/2008/2/08isairas.scarab.bartlett.pdf} } - Bell, E. A., Kemmerer, B. W., Gelino, N. J., Sibille, L., Holmgren, G. M., Flowers, P. F. and Rao-Aourpally, V. (2025). Vibratory Plate Compaction of BP-1 and LHS-1 Utilizing the Planetary Automated Compaction Tool (PACT)
. NASA, 20250005172. Source
BibTeX
@techreport{bell2025vibratory, title = {Vibratory Plate Compaction of BP-1 and LHS-1 Utilizing the Planetary Automated Compaction Tool (PACT)}, author = {Bell, E. A. and Kemmerer, B. W. and Gelino, Nathan J. and Sibille, Laurent and Holmgren, G. M. and Flowers, P. F. and Rao-Aourpally, V.}, number = {20250005172}, institution = {NASA}, year = {2025}, url = {https://ntrs.nasa.gov/citations/20250005172}, abstract = {The Multifunctional End Effector for Regolith Construction, Acquisition, and Transfer (MEERCAT) is a robotic arm end effector developed by the Swamp Works Granular Mechanics and Regolith Operations (GMRO) lab [1]. This system has several capabilities including excavation, trenching, regolith size screening, compaction, and geotechnical property measurement. The NASA Tipping Point Project, Mason, led by Redwire Space, in partnership with the Swamp Works GMRO lab, has continued development and refinement of the PACT system’s compaction capabilities, specifically, under the new moniker Planetary Automated Compaction Tool (PACT). A test campaign in ambient laboratory conditions was conducted using Black Point-1 (BP-1) and Lunar Highlands-1 (LHS-1) simulants in the GMRO’s Big Bin test facility utilizing the Excavation Test Stand (ETS) 2-axis gantry. Along with this work a correlation curve was developed to estimate bulk surface compaction based on surface pocket penetrometer readings of penetration force into simulant. The tests revealed the PACT system to be capable of achieving 80% relative density (%RD) in BP-1 and LHS-1 using a dual-mass excentric mass motor. Testing showed that the Spot compaction method was more capable of compaction at depth (below 51 mm) than the Raster method. Several other conclusions were made including that higher static compaction pressure improved compaction at depth, and that longer surface contact times provided diminishing returns on compaction performance. A correlation between the ambient testing in LHS-1 performed as part of this test campaign and previous work performed in-vacuum conditions using LHS-1 is also shown over a test sample set.} } - Gaier, J. R. and Sechkar, E. A. (2007). Lunar Simulation in the Lunar Dust Adhesion Bell Jar
. AIAA Aerospace Sciences Meeting, NASA/TM-2007-214704. Source
BibTeX
@inproceedings{gaier2007lunar, title = {Lunar Simulation in the Lunar Dust Adhesion Bell Jar}, author = {Gaier, James R. and Sechkar, Edward A.}, booktitle = {AIAA Aerospace Sciences Meeting}, number = {NASA/TM-2007-214704}, institution = {NASA}, year = {2007}, doi = {10.2514/6.2007-963}, abstract = {The Lunar Dust Adhesion Bell Jar has been assembled at the NASA Glenn Research Center to provide a high fidelity lunar simulation facility to test the interactions of lunar dust and lunar dust simulant with candidate aerospace materials and coatings. It has a sophisticated design which enables it to treat dust in a way that will remove adsorbed gases and create a chemically reactive surface. It can simulate the vacuum, thermal, and radiation environments of the Moon, including proximate areas of illuminated heat and extremely cold shadow. It is expected to be a valuable tool in the development of dust repellant and cleaning technologies for lunar surface systems.} } - Jarvis, S. L., Vu, L. Q., Gupta, G., Benson, E., Kim, K. H., Rhodes, R. and Rajulu, S. L. (2023). Development of ARGOS (Active Response Gravity Offload System) Offloading Assessments and Methodology for Lunar EVA Simulations
. International Conference on Environmental Systems, 20230002430. Source
BibTeX
@inproceedings{jarvis2023development, title = {Development of ARGOS (Active Response Gravity Offload System) Offloading Assessments and Methodology for Lunar EVA Simulations}, author = {Jarvis, Sarah L. and Vu, Linh Q. and Gupta, Garima and Benson, Elizabeth and Kim, K. Han and Rhodes, Richard and Rajulu, Sudhakar L.}, booktitle = {International Conference on Environmental Systems}, number = {20230002430}, institution = {NASA}, address = {Calgary}, year = {2023}, url = {https://ntrs.nasa.gov/citations/20230002430}, abstract = {The Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) is an analog environment that can offload pressurized suited subjects for various reduced gravity simulations. The suit is suspended from a robotic overhead crane by a cable connected to the suit via a gimbal with an adjustable pivot point (i.e. offload attachment). There has been increased interest in providing planetary pressurized suited training at ARGOS in preparation for lunar missions. Determination of the appropriate gimbal pivot point location for a given subject is vital for a high-fidelity functional lunar simulation. Interactions between the pivot point location and human-spacesuit center of gravity (CG) can result in righting moments that may lead to artificially stable or unrealistically challenging configurations. Changing the pivot point location is time consuming and repeated adjustment can result in loss of valuable pressurized suited time. This paper aims to share knowledge obtained from the offloading characterization efforts during pressurized suited testing at ARGOS and document the ongoing process to define an appropriate pivot point location through iterative quantitative and qualitative assessments. Human-spacesuit CG locations for the ARGOS lunar simulation were estimated using a 3D body scan and density model combined with spacesuit hardware CAD and specifications. Early pilot testing of the gimbal revealed that setting the pivot point coincident with the modeled CG location was not always possible due to the current gimbal design, and small pivot point shifts had noticeable effects on subject stability. Fourteen subjects performed a series of CG-related tasks in the Exploration Extravehicular Mobility Unit (xEMU) to assess simulation characteristics. Through iterative testing, this task list evolved to streamline the process needed to efficiently identify a suitable pivot point for a given subject. The developed methodology will be critical for pivot point selection during astronaut training in the ARGOS environment.} } - Creager, C., Breckenridge, J., Johnson, K., Oravec, H., Moreland, S., Sobey, A. and McBryan, E. (2025). Best Practices for the Testing of Planetary Roving Vehicle Mobility Systems and Tires
. NASA, 20250003470. Source
BibTeX
@techreport{creager2025best, title = {Best Practices for the Testing of Planetary Roving Vehicle Mobility Systems and Tires}, author = {Creager, Colin and Breckenridge, John and Johnson, Kyle and Oravec, Heather and Moreland, Scott and Sobey, Alexander and McBryan, Emily}, number = {20250003470}, institution = {NASA}, year = {2025}, url = {https://ntrs.nasa.gov/citations/20250003470}, abstract = {NASA has an extensive history of conducting mobility testing on planetary tires, rovers, and mobility subsystems. This paper contains a summary of the best practices and lessons learned from past test approaches, as well as from relevant test methodologies external to NASA, with a focus on tires and mobility systems. It is intended to be a resource for future planetary rover developments. This document, which will be released in two phases, serves two objectives: 1) compile the existing knowledge of mobility related testing within NASA; and 2) identify major gaps in mobility related test needs and suggest potential paths forward. This first release of the document (early 2025) captures information based on the authors’ existing knowledge and an abbreviated literature review. A more thorough version will be released in late 2025 and will include more information on test methods external to NASA, as well as additional lessons learned through further investigations. The Lunar Terrain Vehicle (LTV) is used as case study to help identify major test needs; however, this document is intended to be applicable to a wide range of potential missions. Though no current mobility standards exist for the testing of planetary tires and mobility subsystems, future motive is to utilize the information from this whitepaper to guide the development of NASA mobility test standards.} } - Jehn, M., Just, G. H., Sargeant, H. M., Long-Fox, J. and Britt, D. T. (2025). Implications of Lunar Simulant Geotechnical Properties on Testbed Experimentation and Engineering Analysis
. Space and Planetary Resources. Source
BibTeX
@article{jehn2025implications, title = {Implications of Lunar Simulant Geotechnical Properties on Testbed Experimentation and Engineering Analysis}, author = {Jehn, Marcus and Just, Gabriele H. and Sargeant, Hannah M. and Long-Fox, Jared and Britt, Daniel T.}, journal = {Space and Planetary Resources}, volume = {1}, pages = {5}, year = {2025}, doi = {10.1007/s44461-025-00002-7}, abstract = {Understanding the mechanical behavior of lunar regolith simulants is crucial for progressing engineering analysis in surface infrastructure design and testbed evaluation. This study provides a detailed geotechnical characterization of the Colorado School of Mines Lunar Highlands Type-Testbed simulants, including a new highland-type lunar simulant integrated into the Mines Lunar Surface Simulator testbed. It includes the determination of key geotechnical properties such as particle size distribution, density, compressibility, cohesion, friction angle, and particle shape, using standardized ASTM testing procedures. Key findings show that while particle size distribution similarities exist among the simulants and actual lunar regolith, there are significant differences in density-dependent mechanical behaviors such as shear strength, compressibility, and deformation responses. These results emphasize the complexity of simulant fidelity and its impact on testbed experiments when simulating mid-Technology Readiness Level environments. Additionally, we emphasize the importance of density-specific testing for evaluating both geotechnical properties and simulant performance. This work presents the first comprehensive publication of the full geotechnical profile of Colorado School of Mines highland simulants and highlights the importance of using multiple parameters beyond just particle size distribution to evaluate simulant fidelity. Future research will concentrate on characterizing testbed variability and assessing properties across different density states to improve the application of lunar simulants in engineering analysis and testbed experimentation.} }