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At least 307 records · Page 17

Superelastic Ball Bearings: Materials and Design to Avoid Mounting and Dismounting Brinell Damage in an Inaccessible Press-Fit Application-: Design Approach - I

Ball bearings require proper fit and installation into machinery structures (onto shafts and into bearing housings) to ensure optimal performance. For some applications, both the inner and outer race must be mounted with an interference fit and care must be taken during assembly and disassembly to avoid placing heavy static loads between the balls and races otherwise Brinell dent type damage can occur. In this paper, a highly dent resistant superelastic alloy, 60NiTi, is considered for rolling element bearing applications that encounter excessive static axial loading during assembly or disassembly. A small (R8) ball bearing is designed for an application in which access to the bearing races to apply disassembly tools is precluded. First Principles analyses show that by careful selection of materials, raceway curvature and land geometry, a bearing can be designed that allows blind assembly and disassembly without incurring raceway damage due to ball denting. Though such blind assembly applications are uncommon, the availability of bearings with unusually high static load capability may enable more such applications with additional benefits, especially for miniature bearings.

tribology↗

Acquisition and Pointing for Mars Optical Access Link

Optical characteristics can potentially benefit "access" links at Mars when transmitting data from surface to orbiting assets because of the higher gain and modulation bandwidth, compared to radio frequency (RF). Furthermore, higher bits/kg/W can be realized with low mass and power optical systems, enabling the streaming of high definition imagery. In this paper we present a conceptual design for a low complexity, autonomous optical communications link for returning data at 50-200 Mb/s from the Martian surface and for lower forward data rates of 50 kb/s to the surface. The pointing control is simplified by widening the transmitted laser beams (0.5 - 2.0 mrad) for the short distance (400-1200 Km) links. Link acquisition is based on the orbiter transceiver (OT) "blind"-pointing a laser beam to illuminate the lander transceiver (LT) on the surface. The LT acquires the link with a spectrally-filtered wide-field-of-view camera and subsequently tracks the orbiter transceiver with a two-axis, stepper-motor-actuator, to send back a laser modulated with high-rate data to the orbiting asset. The system design also has a provision for the OT transitioning from blind-pointing to closed loop tracking once it acquires the signal from the lander transceiver. Results from successful ground-based demonstrations performed at JPL, in which the pointing rate required to track an orbiter was emulated by mounting both transceivers on rotating stages, and in which we transmitted live video and pseudo-random data streams, are presented.

Optical Communication↗

Superelastic Ball Bearings: Materials and Design to Avoid Mounting and Dismounting Brinell Damage in an Inaccessible Press-fit Application-: Detailed Analysis - II

Rolling element bearings utilized in precision rotating machines require proper alignment, preload, and interference fits to ensure overall optimum performance. Hence, careful attention must be given to bearing installation and disassembly procedures to ensure the above conditions are met. Usually, machines are designed in such a way that bearings can be pressed into housings or onto shafts through the races without loading the rolling elements. However, in some instances, either due to limited size or access, a bearing must be installed or removed in such a way that the load path travels through the rolling elements. This can cause high contact stresses between the rolling elements and the races and introduces the potential for Brinell denting of the races. This paper is a companion to the Part I paper by the authors that discusses material selection and the general design philosophy for the bearing. Here, a more in-depth treatment is given to the design of a dent-resistant bearing utilizing a superelastic alloy, 60NiTi, for the races. A common bearing analysis tool based on rigid body dynamics is used in combination with finite element simulations to design the superelastic bearing. The primary design constraints are prevention of denting and avoiding the balls riding over the edge of the race groove during a blind disassembly process where the load passes through the rolling elements. Through an iterative process, the resulting bearing geometry is tailored to improve axial static load capability compared to a deep-groove ball bearing of the same size. The results suggest that careful selection of materials and bearing geometry can enable blind disassembly without damage to the raceways, which is necessary in the current application (a compressor in the International Space Station Environmental Control and Life Support System), and results in potential design flexibility for other applications, especially small machines with miniature bearings.

metals↗

Gear Tooth Wear Detection Algorithm

Vibration-based condition indicators continue to be developed for Health Usage Monitoring of rotorcraft gearboxes. Testing performed at NASA Glenn Research Center have shown correlations between specific condition indicators and specific types of gear wear. To speed up the detection and analysis of gear teeth, an image detection program based on the Viola-Jones algorithm was trained to automatically detect spiral bevel gear wear pitting. The detector was tested using a training set of gear wear pictures and a blind set of gear wear pictures. The detector accuracy for the training set was 75 percent while the accuracy for the blind set was 15 percent. Further improvements on the accuracy of the detector are required but preliminary results have shown its ability to automatically detect gear tooth wear. The trained detector would be used to quickly evaluate a set of gear or pinion pictures for pits, spalls, or abrasive wear. The results could then be used to correlate with vibration or oil debris data. In general, the program could be retrained to detect features of interest from pictures of a component taken over a period of time.

Delgado, Irebert R.↗

Determination of Ballistic Limit for IM7/8552 Using Peridynamics

Significant testing is required to design and certify primary aircraft structure subject to High Energy Dynamic Impact (HEDI) events; current work under the NASA Advanced Composites Consortium (ACC) HEDI Project seeks to determine the state-of-the-art of dynamic fracture simulations for composite structures in these events. This paper discusses one of four Progressive Damage Analysis (PDA) methods selected for this project: peridynamics, through EMU implementation. A brief discussion of peridynamic theory is provided, followed by an outline of ballistic impact testing performed for model development and assessment. Detailed modeling approach and test-analysis correlation for a single open test case are presented, followed by the results of a series of blind predictions made prior to testing and test-analysis correlation performed with measured NASA test results. Specifically, we present simulation results for the ballistic limit (V50) of IM7/8552 composite panels ballistically tested with an impactor representative of a high-velocity fan-blade-out condition. In particular, force and displacement history and the damage state determined analytically are compared to measured results. Ultimately, peridynamics has the ability to predict damage patterns, impact force and deflections during a high energy dynamic impact event on composite panels of different layups using two different types of impactors. Blind predictions were promising and increased confidence in the model for impact simulation. There are open questions regarding the fidelity of the test fixture idealization in regards to stiffness and damping which will need to be addressed in future work.

Cuenca, Fernando↗

Using Intelligent Targeting to increase the science return of a Smart Ice Storm Hunting Radar

Smart Ice Cloud Sensing (SMICES) is a small-sat concept in which a radar intelligently targets ice storms based on information collected by a lookahead radiometer. Often space observations are performed by continuously collecting data from an instrument aimed at nadir (e.g. directly below the space platform). However, if the platform has the ability to assess science utility of features being overflown, an intelligent measurement scheme can improve science return. This can be achieved by controlling the on/off state of the instrument if it is not able to continuously operate (e.g. due to energy or thermal constraints), and by allowing the instrument to view off nadir if it has pointing capabilities.In the case of SMICES, power constraints and the rarity of storms means that with blind nadir targeting SMICES would collect a limited amount of ice storm radar data. The algorithms proposed acquire measurements to maximize acquired high interest storms while concurrently collecting a background sampling of all features. We use a cloud classification system to identify five different cloud types. Six algorithms ranging from “blind” to more selective are described and results from evaluation on a dataset of 13 ground swaths covering 72,399,600 km2 of data are presented. This data is from high quality science simulations that contain all five cloud types and multiple storms. When utilizing the radiometer’s lookahead and the full range of the radar the results show a 23.7x and 1.9x increase over the base algorithm in the most and second most important cloud types respectively.

Cooke, Caitlyn↗

Evaluating Differences Among Crop Models in Simulating Soybean in-Season Growth

Crop models are useful tools for simulating agricultural systems that require continued model development and testing to increase their robustness and improve how they describe our current understanding of processes. Coordinated and “blind” evaluation of multiple models using same protocols and experimental datasets provides unique opportunities to further improve models and enhance their reliability. For soybean [Glycine max (L.) Merr.], there has been limited coordinated multi-model evaluations for the simulation of in-season plant growth dynamics. We evaluated ten dynamic soybean crop models for their simulation of in-season plant growth using data from five experiments conducted in Argentina, Brazil, France, and USA. We evaluated models after a Blind (using only phenology data) and a Full calibration (with in-season and end-of-season variables). Calibration reduced model uncertainty by reducing standard bias for the simulation of in-season variables (biomass, leaf, pod, and stem weights, and leaf area index, LAI). However, we found that most models had difficulty in reproducing leaf growth dynamics, with normalized root mean squared error (nRMSE) of 56% for leaf weight and 43% for LAI (across locations and models after Full calibration). Models with different levels of complexity and experience were capable of simulating final seed yield at maturity with reasonable accuracy (nRMSE of 8–31% after Full calibration). However, the nRMSE for pod weight (of 17–64% after Full calibration) was two-fold larger than that of seed yield. Moreover, the models differed in how they simulated timing from sowing to beginning seed growth (47–93 days) and effective seed filling period (18–54 days), owing to model structural differences in defining the reproductive developmental stages. Overall, we identified the following processes that can benefit from further model improvement: leaf expansion and senescence, reproductive phenology, and partitioning to reproductive growth. Simulation of pod wall tissue and individual seed cohorts is another aspect that many models currently lack. Model improvement can benefit from high-temporal resolution experimental datasets that concurrently account for phenology, plant growth, and partitioning. Further, we recommend collecting reproductive phenology in the field consistent with actual dry matter allocation to organs in the models and collecting multiple observations of seed and pod weight to aid model improvement for simulation of seed growth and yield formation.

Agricultural Model Intercomparison and Improvement↗

Towards a Combined Low-Earth Orbit Lightning Climatology: Current Work and Assessing South Atlantic Anomaly Influence

This presentation discusses the current status and ongoing work towards a low-Earth orbit (LEO) lightning climatological product that includes both Lightning Imaging Sensors (LIS) and the Optical Transient Detector (OTD). The project builds upon the work by Cecil et al. (2014) to include the LIS on the International Space Station (ISS), featuring additional inter-instrumental comparisons to more accurately depict the unique capabilities of each instrument. A closer examination of the interference from the South Atlantic Anomaly (SAA) was also conducted on all three LEO sensors. The SAA is a region of the magnetosphere roughly spanning the south-central Atlantic wherein the inner Van Allen radiation belts are closer to Earth than anywhere else, subjecting spacecraft in LEO to significantly higher radiation flux levels. This radiation can produce interference with the LIS and OTD instruments, manifesting as non-lightning luminous events. While these events can be identified easily enough, they can occur in such quantities that they overwhelm the sensors’ processors and effectively ‘blind’ them. This is called the First-In First-Out (FIFO) buffer overflow, and this blinded time reduced the instruments’ view-time as a result. The FIFO overflow and view-time can reliably be used to track the SAA interference (Clark et al. 2024), which allows for the lightning counts attributable to the SAA to be assessed. The impact that the SAA had on the quality of observations from the LEO lightning instrumentation and the significance for the resulting climatological products was investigated. Substantial areas of interference were identified for all three instruments using the view-time and quality flags, each with a unique shape and temporal evolution. The temporal evolution and general region affected are of particular importance when constructing a climatological product, as there are notable reductions to view-time over prolonged periods across a lightning-rich region. However, a temporal element also makes isolating the subsequent impact on the lightning signal significantly more challenging. Lightning counts in this region are highly seasonal and exhibit inter-annual variability, which is compounded by the nature of LEO observations. This study includes preliminary analysis of the impact that the SAA has on the lightning counts given the notable impact shown in the metadata.

Austin G Clark↗

Feasibility Study of Millimeter Wave Radars For Safeguards Applications

Containment and surveillance are fundamental measures in nuclear safeguards. Techniques such as video surveillance and laser curtain for containment provide effective monitoring in areas where maintaining continuity of knowledge is required. These systems, however, can be susceptible to loss of monitoring capabilities under certain environmental conditions such as poor visibility (i.e. low light conditions, smoke, fog, etc.) or extended power loss past the duration that the backup power system is designed for. Brookhaven National Laboratory has been investigating the feasibility of millimeter waves (mmWave) as a new perimeter seal in which radio frequency waves in the range of 60-64 GHz are used to detect and monitor objects of interest. Signals in this frequency range are not susceptible to environmental conditions. For proof-of-concept tests, mmWave sensors from Texas Instruments (TI), specificallyIWR6843, are used in a test bed at BNL's Waste Management facility to simulate the operations at nuclear facilities. The unique design of TI mmWave sensors requires less memory and power consumption compared to counterpart systems. These devices are capable of exporting 3D point-cloud data, which is visualized graphically and compared to videos recorded at the same time to validate the performance of the mmWave sensor. A set of experiments were planned to test the feasibility of the mmWave in this application, including monitoring static containers in a storage area and detecting intrusions at the boundaries of the area. In addition, the experiments also identify potential blind spots relative to sensor position and utilize multiple operating sensors simultaneously to reduce or eliminate such blind spots. The optimal positioning of multiple sensors was determined for the experimental room configuration. In this paper, we will discuss the details of this novel perimeter sealing concept and present the test results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗

Online Alpha Monitoring of High Cs-137 Hanford and SRS High Level Waste with Tensioned Metastable Fluid Detectors

The Department of Energy’s Hanford and Savannah River Sites maintain millions of gallons of caustic supernate and salt high activity waste in their high-level waste (HLW) tank farm inventories. The Savannah River Site is currently treating this waste with a calixarene-based solvent extraction of Cs-137 to reduce these inventories. Hanford is employing an at-tank crystalline silico titanate (CST) based solid phase extraction methodology to reduce their liquid HLW inventories. Due to the high solubility of Cs-137 and the relative insolubility of the actinides in these caustic waste forms, the beta to alpha radioactivity ratio can often exceed six orders of magnitude in the feed solutions to these treatment processes. This unique characteristic leads to significant technical challenges in making rapid gross alpha measurements in the presence of the overwhelming beta, gamma, as well as dissolved sodium salt in these HLW matrices. Conventional radioanalytical techniques, such as liquid scintillation analysis or gas flow proportional counting require significant radiochemistry preparation prior to the radiometric measurements for gross alpha activity. These required pretreatments render these technologies untenable for rapid quantification of gross alpha activity that could be required to support on or at-line measurements ensuring a waste stream will meet regulatory requirements. The radiation measurement properties of Tensioned Metastable Fluid Detectors (TMFDs) have been studied by Purdue University’s Taleyarkhan research group for well over a decade. Fluids tensioned to the appropriate degree will rupture when struck by radiation, resulting in a measurable cavitation event. The negative pressure generating this tension can be adjusted by centrifugal rotation or by acoustic means in such a way that these cavitation events can be generated from alpha radiation but will not be generated by beta or gamma radiation. Purdue University and the Savannah River National Laboratory are currently collaborating to develop a gamma/beta blind, spectroscopic alpha measurement system based on the Tensioned Metastable Fluid Detector technology to provide a potential solution for performing rapid gross alpha measurements on these high gamma/beta sample matrices. Measurements using the Indirect Drive Acoustically Tensioned Metastable Fluid Detectors developed as part of this collaboration were performed with an alpha emitting radionuclide. Successful determination of gross alpha activity was observed, indicating a potential pathway for rapid gross alpha measurements in remote-handled shielded cells or in process situations requiring online alpha monitoring. Measurements using this system have been conducted on high beta activity solutions, demonstrating the beta blind capability of this system. Measurements are currently underway to test the system’s capability to measure gross alpha activity on Savannah River Site high level waste high Cs-137 samples that have been measured by the SRNL radiochemistry team. This work was supported by the DOE EM Technology Development program.

DiPrete, David [Savannah River National Laboratory↗

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. These inputs and outputs were used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems at the Brady Hot Springs Geothermal Site. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Brady Hot Springs Geothermal Site.

15 GEOTHERMAL ENERGY↗

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Desert Peak Geothermal Field.

15 GEOTHERMAL ENERGY↗

Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site.

15 GEOTHERMAL ENERGY↗

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Metal-semiconductor-metal structured p-i-n GaN/AlGaN ultrafast detectors for deep-UV photodetection

We report the productive outcome of the design, fabrication, and testing of a new class of GaN/AlGaN-based ultrafast, sensitive photodiodes for deep-UV solar blind photodetection. Pt was employed as the interdigitated metal electrode to establish that while a Schottky contact was formed at the metal/semiconductor heterojunction, it was the quantum wells in the p-i-n vertical structure that produced the diode characteristics of the detectors. The metal–semiconductor–metal design retained its ultrafast property as expected in the p-i-n structure because the spacing between the interdigitated fingers was asymmetrically implemented to optimize the photogenerated carriers’ transit time from the quantum well to the external circuitry. Also, the vertical p-i-n structure provided its renowned efficient photocarrier generation, which was significantly enhanced by the delta quantum well architecture of the vertical epitaxial structure. The active area of the device was 300 μm × 300 μm with 5-μm finger width, and asymmetric electrode spacing of 2 μm, 3 μm, and 5 μm. Here, the best device had peak responsivity of 3.5 A/W under 262-nm illumination with full width half maximum of 337.2-ps and 37.5-ps rise times when biased with 20 V.

efficient↗

Sparse and Random Sampling Techniques for High-Resolution, Full-Field, BSS-Based Structural Dynamics Identification from Video

Video-based techniques for identification of structural dynamics have the advantage that they are very inexpensive to deploy compared to conventional accelerometer or strain gauge techniques. When structural dynamics from video is accomplished using full-field, high-resolution analysis techniques utilizing algorithms on the pixel time series such as principal components analysis and solutions to blind source separation the added benefit of high-resolution, full-field modal identification is achieved. An important property of video of vibrating structures is that it is particularly sparse. Typically video of vibrating structures has a dimensionality consisting of many thousands or even millions of pixels and hundreds to thousands of frames. However the motion of the vibrating structure can be described using only a few mode shapes and their associated time series. As a result, emerging techniques for sparse and random sampling such as compressive sensing should be applicable to performing modal identification on video. This work presents how full-field, high-resolution, structural dynamics identification frameworks can be coupled with compressive sampling. The techniques described in this work are demonstrated to be able to recover mode shapes from experimental video of vibrating structures when 70% to 90% of the frames from a video captured in the conventional manner are removed.

47 OTHER INSTRUMENTATION↗

The relation of motion sickness to the spatial-temporal properties of velocity storage

Tilting the head in roll to or from the upright while rotating at a constant velocity (roll while rotating, RWR) alters the position of the semicircular canals relative to the axis of rotation. This produces vertical and horizontal nystagmus, disorientation, vertigo, and nausea. With recurrent exposure, subjects habituate and can make more head movements before experiencing overpowering motion sickness. We questioned whether promethazine lessened the vertigo or delayed the habituation, whether habituation of the vertigo was related to the central vestibular time constant, i.e., to the time constant of velocity storage, and whether the severity of the motion sickness was related to deviation of the axis of eye velocity from gravity. Sixteen subjects received promethazine and placebo in a double-blind, crossover study in two consecutive 4-day test series 1 month apart, termed series I and II. Horizontal and vertical eye movements were recorded with video-oculography while subjects performed roll head movements of approx. 45 degrees over 2 s to and from the upright position while being rotated at 138 degrees /s around a vertical axis. Motion sickness was scaled from 1 (no sickness) to an endpoint of 20, at which time the subject was too sick to continue or was about to vomit. Habituation was determined by the number of head movements that subjects made before reaching the maximum motion sickness score of 20. Head movements increased steadily in each session with repeated testing, and there was no difference between the number of head movements made by the promethazine and placebo groups. Horizontal and vertical angular vestibulo-ocular reflex (aVOR) time constants declined in each test, with the declines being closely correlated to the increase in the number of head movements. The strength of vertiginous sensation was associated with the amount of deviation of the axis of eye velocity from gravity; the larger the deviation of the eye velocity axis from gravity, the more severe the motion sickness. Thus, promethazine neither reduced the nausea associated with RWR, nor retarded or hastened habituation. The inverse relationship between the aVOR time constants and number of head movements to motion sickness, and the association of the severity of motion sickness with the extent, strength, and time of deviation of eye velocity from gravity supports the postulate that the spatiotemporal properties of velocity storage, which are processed between the nodulus and uvula of the vestibulocerebellum and the vestibular nuclei, are likely to represent the source of the conflict responsible for producing motion sickness.

NASA Discipline Neuroscience↗