Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sensor performance”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Description of real-time Ada software implementation of a power system monitor for the Space Station Freedom PMAD DC testbed

The Ada language software development to perform the electrical system monitoring functions for the NASA Lewis Research Center's Power Management and Distribution (PMAD) DC testbed is described. The results of the effort to implement this monitor are presented. The PMAD DC testbed is a reduced-scale prototype of the electrical power system to be used in the Space Station Freedom. The power is controlled by smart switches known as power control components (or switchgear). The power control components are currently coordinated by five Compaq 382/20e computers connected through an 802.4 local area network. One of these computers is designated as the control node with the other four acting as subsidiary controllers. The subsidiary controllers are connected to the power control components with a Mil-Std-1553 network. An operator interface is supplied by adding a sixth computer. The power system monitor algorithm is comprised of several functions including: periodic data acquisition, data smoothing, system performance analysis, and status reporting. Data is collected from the switchgear sensors every 100 milliseconds, then passed through a 2 Hz digital filter. System performance analysis includes power interruption and overcurrent detection. The reporting mechanism notifies an operator of any abnormalities in the system. Once per second, the system monitor provides data to the control node for further processing, such as state estimation. The system monitor required a hardware time interrupt to activate the data acquisition function. The execution time of the code was optimized using an assembly language routine. The routine allows direct vectoring of the processor to Ada language procedures that perform periodic control activities. A summary of the advantages and side effects of this technique are discussed.

Ludwig, Kimberly↗
NASA NTRS1991

Description of real-time Ada software implementation of a power system monitor for the Space Station Freedom PMAD DC testbed

The authors describe the Ada language software developed to perform the electrical power system monitoring functions for the NASA Lewis Research Center's Power Management and Distribution (PMAD) DC testbed. The results of the effort to implement this monitor are presented. The PMAD DC testbed is a reduced-scale prototype of the electric power system to be used in Space Station Freedom. The power is controlled by smart switches known as power control components (or switchgear). The power control components are currently coordinated by five Compaq 386/20e computers connected through an 802.4 local area network. The power system monitor algorithm comprises several functions, including periodic data acquisition, data smoothing, system performance analysis, and status reporting. Data are collected from the switchgear sensors every 100 ms, then passed through a 2-Hz digital filter. System performance analysis includes power interruption and overcurrent detection. The system monitor required a hardware timer interrupt to activate the data acquisition function. The execution time of the code was optimized by using an assembly language routine. The routine allows direct vectoring of the processor to Ada language procedures that perform periodic control activities.

Ludwig, Kimberly↗
NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. An inverse estimation of the backshell and heatshield surface aeroheating was performed, using the data from the MEDLI2 Instrumented Sensor Plugs, a network of thermocouples embedded within the thermal protection system across the aeroshell. Monte Carlo analysis was conducted to assess the sensitivity of the surface heat rate, temperature, and heat load to uncertainties in thermocouple depth and material properties. In this paper, a variance decomposition method using Sobol indices was employed to understand the relative contributions of each uncertainty parameter. Performing this analysis using results from the inverse analysis tool FIAT_Opt was found to require incredibly high computation time, and thus machine learning models were trained and evaluated as a surrogate model for FIAT_Opt. This paper demonstrates that machine learning models can be an efficient, accurate alternative to state-of-the-art inverse analysis tools like FIAT_Opt, especially for computationally-expensive processes. Using these models, the sensitivity analysis showed that uncertainties in heat capacity and thermal conductivity were the main drivers for the overall uncertainty in peak reconstructed heating and heat load.

H S Alpert↗
NASA NTRS2016

Bluetooth(Registered Trademark) Heart Rate Monitors for Spaceflight

Heart rate monitoring is required during exercise for crewmembers aboard the International Space Station (ISS) and will be for future exploration missions. The cardiovascular system must be sufficiently stressed throughout a mission to maintain the ability to perform nominal and contingency/emergency tasks. High quality heart rate data is required to accurately determine the intensity of exercise performed by the crewmembers and show maintenance of VO2max. The quality of the data collected on ISS is subject to multiple limitations and is insufficient to meet current requirements. PURPOSE: To evaluate the performance of commercially available Bluetooth® heart rate monitors (BT_HRM) and their ability to provide high quality heart rate data to monitor crew health on board ISS and during future exploration missions. METHODS: Nineteen subjects completed 30 data collection sessions of various intensities on the treadmill and/or cycle. Subjects wore several BT_HRM technologies for each testing session. One electrode-based chest strap (CS) was worn, while one or more optical sensors (OS) was worn. Subjects were instrumented with a 12-lead ECG to compare the heart rate data from the Bluetooth sensors. Each BT_RHM data set was time matched to the ECG data and a +/-5bpm threshold was applied to the difference between the two data sets. Percent error was calculated based on the number of data points outside the threshold and the total number of data points. REULTS: The electrode-based chest straps performed better than the optical sensors. The best performing CS was CS1 (1.6%error), followed by CS4 (3.3%error), CS3 (6.4%error), and CS2 (9.2%error). The OS resulted in 10.4% error for OS1 and 14.9% error for OS2. CONCLUSIONS: The highest quality data came from CS1, unfortunately it has been discontinued by the manufacturer. The optical sensors have not been ruled out for use, but more investigation is needed to determine how to get the best quality data. CS2 will be used in an ISS Bluetooth validation study, because it simultaneously transmits Magnetic Pulse which is integrated with existing exercise hardware on ISS. The simultaneous data streams allow for beat to beat comparison between the current ISS standard and CS2.Upon Bluetooth(Registered Trademark) validation aboard ISS, down select of a new BT_HRM for operational use will be made.

Buxton, Roxanne E.↗
NASA NTRS2016

Bluetooth Heart Rate Monitors For Spaceflight

Heart rate monitoring is required for crewmembers during exercise aboard the International Space Station (ISS) and will be for future exploration missions. The cardiovascular system must be sufficiently stressed throughout a mission to maintain the ability to perform nominal and contingency/emergency tasks. High quality heart rate data are required to accurately determine the intensity of exercise performed by the crewmembers and show maintenance of VO2max. The quality of the data collected on ISS is subject to multiple limitations and is insufficient to meet current requirements. PURPOSE: To evaluate the performance of commercially available Bluetooth heart rate monitors (BT_HRM) and their ability to provide high quality heart rate data to monitor crew health aboard the ISS and during future exploration missions. METHODS: Nineteen subjects completed 30 data collection sessions of various intensities on the treadmill and/or cycle. Subjects wore several BT_HRM technologies for each testing session. One electrode-based chest strap (CS) was worn, while one or more optical sensors (OS) were worn. Subjects were instrumented with a 12-lead ECG to compare the heart rate data from the Bluetooth sensors. Each BT_HRM data set was time matched to the ECG data and a +/-5bpm threshold was applied to the difference between the 2 data sets. Percent error was calculated based on the number of data points outside the threshold and the total number of data points. RESULTS: The electrode-based chest straps performed better than the optical sensors. The best performing CS was CS1 (1.6% error), followed by CS4 (3.3% error), CS3 (6.4% error), and CS2 (9.2% error). The OS resulted in 10.4% error for OS1 and 14.9% error for OS2. CONCLUSIONS: The highest quality data came from CS1, but unfortunately it has been discontinued by the manufacturer. The optical sensors have not been ruled out for use, but more investigation is needed to determine how to obtain the best quality data. CS2 will be used in an ISS Bluetooth validation study, because it simultaneously transmits magnetic pulse that is integrated with existing exercise hardware on ISS. The simultaneous data streams allow for beat-to-beat comparison between the current ISS standard and CS2. Upon Bluetooth validation aboard ISS, the research team will down select a new BT_HRM for operational use.

Buxton, R. E.↗
NASA NTRS2012

Calibration of PCB-132 Sensors in a Shock Tube

While PCB-132 sensors have proven useful for measuring second-mode instability waves in many hypersonic wind tunnels, they are currently limited by their calibration. Until now, the factory calibration has been all that was available, which is a single-point calibration at an amplitude three orders of magnitude higher than a second-mode wave. In addition, little information has been available about the frequency response or spatial resolution of the sensors, which is important for measuring high-frequency instability waves. These shortcomings make it difficult to compare measurements at different conditions and between different sensors. If accurate quantitative measurements could be performed, comparisons of the growth and breakdown of instability waves could be made in different facilities, possibly leading to a method of predicting the amplitude at which the waves break down into turbulence, improving transition prediction. A method for calibrating the sensors is proposed using a newly-built shock tube at Purdue University. This shock tube, essentially a half-scale version of the 6-Inch shock tube at the Graduate Aerospace Laboratories at Caltech, has been designed to attain a moderate vacuum in the driven section. Low driven pressures should allow the creation of very weak, yet still relatively thin shock waves. It is expected that static pressure rises within the range of second-mode amplitudes should be possible. The shock tube has been designed to create clean, planar shock waves with a laminar boundary layer to allow for accurate calibrations. Stronger shock waves can be used to identify the frequency response of the sensors out to hundreds of kilohertz.

Berridge, Dennis C.↗
NASA NTRS2015

Chlorophyll Variability in the Oligotrophic Gyres: Mechanisms, Seasonality and Trends

A 16-year (1998-2013) analysis of trends and seasonal patterns was conducted for the 5 subtropical ocean gyres using chlorophyll-a (Chl-a) retrievals from ocean color satellite data, sea surface temperature (SST) obtained from optimally interpolated Advanced Very High Resolution Radiometer (AVHRR) data, and sea-level anomaly (SLA) from Aviso multi-sensor altimetry data. Trend analysis was also performed on mixed-layer data derived from gridded temperature and salinity profiles (1998-2010) from the Simple Ocean Data Assimilation (SODA) model. The Chl-a monthly composites were constructed from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) on Aqua using two different algorithms: the standard algorithm (STD) that has been in use since the start of the SeaWiFS mission in 1997, and a more recently developed Ocean Color Index (OCI) algorithm that is purported to provide improved accuracy in low chlorophyll waters such as the oligotrophic regions of the subtropical gyres. Trends were obtained for all gyres using both STD and OCI algorithms, which demonstrated generally consistent results. The North Pacific, Indian Ocean, North Atlantic and South Atlantic gyres showed significant downward trends in Chl-a, while the South Pacific gyre has a much weaker upward trend with no statistical significance. Time series of satellite-derived net primary production (NPP) showed downward trends for all the gyres, while all 5 gyres exhibited positive trends in SST and SLA. The seasonal variability of Chl-a in each gyre is tightly coupled to the variability in mixed layer depth (MLD) with peak values in winter in both hemispheres when vertical mixing is more vigorous, reaching depths approaching the nutricline (ZNO3, here defined as the depth of the 0.2 micron nitrate concentration). On a seasonal basis, Chl-a concentrations increase when the MLD approaches or is deeper than the nutricline depth, in agreement with the concept that vertical mixing is the major driving mechanism for phytoplankton photosynthesis in the interior of the gyres. In addition, MLD and SST seasonal changes are well correlated indicating that SST is a reasonable index of vertical mixing in the gyres. The combination of surface warming trends and biomass reduction over the 16-year period has the potential to reduce atmospheric CO2 uptake by the gyres and therefore influence the global carbon cycle.

Long-term trends↗
NASA NTRS2002

Multi-Image Registration for an Enhanced Vision System

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

Hines, Glenn↗
DOE OSTI2020

An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. Here, we designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with <0.4 m geolocation accuracy, <0.1 m altitude drift, and <1.5° error of the fiber optic from nadir position during scanning. Weekly seasonal campaigns reveal that SIF outperforms conventional VIs such as the normalized difference vegetation index (NDVI) for distinguishing plots with different crop yield potential, especially after canopy closure when NDVI tends to saturate. The UAS can capture the diurnal dynamics of SIF and PRI for both corn and soybean. At the seasonal scale, SIF acquired from the UAS correlates well with that from a fixed SIF tower system ( R 2 = 0.81), which measured the same target albeit with different footprints, demonstrating the capability of UAS in characterizing the seasonal progression of crop activity. In conclusion, our newly developed UAS provides high-quality SIF and hyperspectral reflectance, facilitating mechanistic understanding of the physiological control on photosynthesis dynamics. Our findings also imply that this UAS could enable extension of fixed tower-based systems to monitor multiple targets from diurnal to seasonal scales and improve monitoring of heterogeneous fields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Texture development in magnetostrictive Fe-Ga alloys processed by laser powder bed fusion

Iron-gallium (Fe-Ga, Galfenol) alloys are promising magnetostrictive materials for actuators, sensors, and energy harvesting, but their performance is highly sensitive to microstructure and texture. Additive manufacturing by laser powder bed fusion (LPBF) offers a pathway to engineer texture and integrate functional materials into complex geometries. Here, we fabricate Fe-Ga alloys (Fe 82.2 Ga 17.8 ) by LPBF of gas-atomized powders and systematically optimize laser power and scan speed to maximize density and control texture. Nearly full-density parts (up to 99.6 %) are achieved within a narrow processing window. Electron backscatter diffraction (EBSD) reveals a strong <100> fiber texture aligned with the build direction and columnar grains up to 1 mm long. Magnetostriction measurements show saturation magnetostriction of 190 ppm in the build direction. Correlating texture data with macroscopic magnetostriction, we estimate intrinsic magnetostriction constants (λ 100 = 228 ppm, λ 111 = 12 ppm), closely matching single crystal-derived values. These results demonstrate the critical interplay between processing, texture, and functional performance in additively manufactured Fe-Ga alloys and establish LPBF as a viable route for high-performance magnetostrictive materials.

Additive manufacturing↗
DOE OSTI2020

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Resolving electron and hole transport properties in semiconductor materials by constant light-induced magneto transport

The knowledge of minority and majority charge carrier properties enables controlling the performance of solar cells, transistors, detectors, sensors, and LEDs. Here, we developed the constant light induced magneto transport method which resolves electron and hole mobility, lifetime, diffusion coefficient and length, and quasi-Fermi level splitting. We demonstrate the implication of the constant light induced magneto transport for silicon and metal halide perovskite films. We resolve the transport properties of electrons and holes predicting the material’s effectiveness for solar cell application without making the full device. The accessibility of fourteen material parameters paves the way for in-depth exploration of causal mechanisms limiting the efficiency and functionality of material structures. To demonstrate broad applicability, we further characterized twelve materials with drift mobilities spanning from 10 –3 to 10 3 cm 2 V –1 s –1 and lifetimes varying between 10 –9 and 10 –3 seconds. The universality of our method its potential to advance optoelectronic devices in various technological fields.

14 SOLAR ENERGY↗
DOE OSTI2021

Relocating microseismicity from downhole monitoring of the Decatur CCS site using a modified double-difference algorithm

SUMMARY The injection of CO2 at the Decatur carbon capture and storage site has generated significant microseismic activity, which occurs in distinct spatial clusters up to approximately 2.2 km from the primary injection well. Accurate and precise event locations are vital for the characterization of the microseismicity to help understand the reservoir response to the CO2 injection, whilst enabling the identification of minor faults and fractures below the resolution of conventional active seismic imaging. However, microseismic monitoring of fluid injection sites, such as Decatur, is often performed using a network of borehole sensors often from a single well. While these downhole sensors have excellent detection capabilities, their poor azimuthal coverage limits the ability to precisely determine event locations. We have developed a modified double-difference relocation algorithm suitable for both 1-D and 3-D velocity models, and which incorporates differential back azimuth observations to allow the benefits of the original double-difference algorithm to be applicable to a downhole microseismic monitoring setting. Applying the modified double-difference algorithm to the microseismicity at Decatur, we have successfully relocated 4293 events. The relocation included over 59 million observations for 757 285 event pairs, split across seven geographic regions. Despite the majority of observations being recorded in only two boreholes, with an almost identical azimuthal coverage, the results have shown to be reliable with significantly reduced residuals and low uncertainties associated with the final locations. We have analysed the residuals in terms of their association with each geographic region, data type, station and individual events, to fully appreciate their influence in the inversion and the fit of the data to the final set of event locations. For each region, the relocated seismicity has become less diffuse with improved clustering, and with newly visible linear features often orientated in a NE–SW direction. These results show the potential improvements that can be made to microseismic event locations recorded by a borehole network with a limited and variable azimuthal distribution.

58 GEOSCIENCES↗
DOE OSTI2024

Convolutional Variational Autoencoder-based Unsupervised Learning for Power Systems Faults

Classification of power system event data is a growing need, particularly where non-protective relaying-based sensors are used to monitor grid performance. Given the high burden of obtaining event data with appropriate labeling, an unsupervised approach is highly valuable. This approach enables using event data without labeling, which is far easier to obtain. This paper presents an unsupervised learning method to classify and label transients observed in the distribution grid. A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data is used to train the CVAE that identifies different faults as different clusters in the latent space. The clusters are then used as the foundation model to categorize the real-world data.

Alam, Maksudul↗
DOE OSTI2022

Continuous Particle Monitoring and Removal for Molten Chloride CSP Systems

This report describes the technologies that were developed as part of the Continuous Particle Monitoring and Removal for Molten Chloride CSP Systems project that was funded by the EERE Solar Energy Technologies Office during FY2021. This project consisted of two main tasks: (1) the development electrical resistance tomography (ERT) sensors to provide particle sensing capabilities for CSP-relevant molten chloride salts, and (2) the development of vortex separation technologies to enable efficient removal of particles from the salt. Both of these tasks are crucial because, although the Gen3 CSP chloride heat transfer fluid is inexpensive and can achieve high temperatures, major issues with erosion corrosion and clogging can arise from the presence of MgO particles within the salt. The particle monitoring and removal technologies were both demonstrated over the course of this project. The ERT sensors were able to achieve their performance targets by providing accurate particle concentration measurements over a range from 0.0 to 8.0 wt%. The vortex separators were able to demonstrate separation of particles from molten salt streams, but the separation efficiencies were lower than the targeted level of 90%. With further development and deployment, these technologies will ultimately help to enable successful long-term operations of CSP systems that make use of high-temperature chloride salts.

14 SOLAR ENERGY↗
DOE OSTI2023

WIRE-21 Experiment Irradiation Conditions and In-Situ Data Collection

This report summarizes the in situ data collected during three cycles of irradiation (~75 days) of the Wireless Instrumented Removable Beryllium Experiment 2021 (WIRE-21) in the removable beryllium (RB) positions of the High Flux Isotope Reactor (HFIR). The experiment was designed primarily to evaluate the effects of high neutron flux and fluence on the performance of wireless temperature and pressure sensors being developed by Westinghouse Electric Company (WEC). WEC’s sensors could provide critical data regarding the evolution of centerline temperatures and pressurization due to fission gas release during fuel operation in light-water reactors (LWRs) or various advanced reactor applications. In addition to WEC’s wireless sensors, many other sensors were interrogated, including thermocouples, self-powered neutron detectors (SPNDs), distributed fiber optic temperature sensors, and passive neutron flux wires and silicon carbide thermometry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Scaling Containment on a Large Centrifuge

Containment science concerns the trapping or leakage of radioactive cavity gases from underground nuclear explosions (UNEs). The most physically relevant data for validation of containment science comes from legacy UNE testing or large field-scale chemical explosions. Field-scale tests can inform on the degree of residual stress imparted to host geology and possible formation of an accompanying gas-containing “stress cage”, for example, as a function of chemical explosion yield. However, field testing can be expensive, difficult to conduct, and challenging to instrument with limitations on data coverage (i.e., the number of boreholes; difficult coring through damage zones). Small-scale laboratory tests are typically simpler to conduct and more thoroughly characterize, but may not include the right scale of containment processes for stress-cage or chimney formation. This report presents the theory and fundamentals of large centrifuge physical modeling, including a history of explosive or similar testing relevant to containment science investigations on centrifuges. Subscale models with embedded chemical explosives in the enhanced gravity of a large centrifuge can represent hundreds of meters of depth and large explosions not otherwise attainable in the laboratory as based on scaling of length, energy, and other processes by the g-factor of the centrifuge (i.e., the number of times larger the centrifugal force is than the gravitational force on the Earth’s surface). The centrifuge uniquely joins the simplicity and exhaustiveness of laboratory-scale characterization with the physics of field-scale processes. This report is part of Sandia National Laboratories’ (SNL’s) effort to prepare for physical modeling with approximately one-meter tall geologic models of stress cage and/or chimney formation on its 29-foot [8.84 m] radius centrifuge with a load capacity of 1.6 million 𝑔-pounds [726 𝑔-ton]. The scaling relationships herein will inform model design decisions and performance requirements for in-flight sensors.

42 ENGINEERING↗