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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗
NASA NTRS2010

Generation of Optical Combs in a WGM Resonator from a Bichromatic Pump

Optical combs generated by a monolithic resonator with Kerrmedium can be used in a number of applications, including orbital clocks and frequency standards of extremely high accuracy, such as astronomy, molecular spectroscopy, and the like. The main difficulty of this approach is the relatively high pump power that has to be used in such devices, causing undesired thermorefractive effects, as well as stimulated Raman scattering, and limiting the optical comb quality and utility. In order to overcome this problem, this innovation uses a different approach to excitation of the nonlinear oscillations in a Kerr-nonlinear whispering gallery mode (WGM) resonator and generation of the optical comb. By coupling to the resonator two optical pump frequencies instead of just one, the efficiency of the comb source can be increased considerably. It therefore can operate in a lowerpower regime where the undesirable effects are not present. This process does not have a power threshold; therefore, the new optical component can easily be made strong enough to generate further components, making the optical comb spread in a cascade fashion. Additionally, the comb spacing can be made in an arbitrary number of the resonator free spectral ranges (FSR). The experimental setup for this innovation used a fluorite resonator with OMEGA= 13.56 GHz. This material has very low dispersion at the wavelength of 1.5 microns, so the resonator spectrum around this wavelength is highly equidistant. Light was coupled in and out of the resonator using two optical fibers polished at the optimal coupling angle. The gap between the resonator and the fibers, affecting the light coupling and the resonator loading, was controlled by piezo positioners. The light from the input fiber that did not go into the resonator reflected off of its rim, and was collected by a photodetector. This enabled observation and measurement of the (absorption) spectrum of the resonator. The input fiber combined light from two lasers centered at around 1,560 nanometers. Both laser frequencies were simultaneously scanned around the selected WGMs of the same family. However, they were separated by one, two, three, or ten FSRs. This was achieved by fine-tuning each laser frequency offset until the selected resonances overlap on the oscilloscope screen. The resonator quality factor Q = 7 x 10(exp 7) was relatively low to increase the linewidth and, therefore, the duty cycle of both lasers simultaneously coupled into their WGMs. The optical spectrum analyzer (OSA) connected to the output fiber was continuously acquiring data, asynchronously with the laser scan. The instrument was set to retain the peak power values; therefore, a trace recorded for a sufficiently long period of time reflected the situation with both lasers maximally coupled to the WGMs.

Strekalov, Dmitry V.↗
NASA NTRS2006

Phase Sensor for Aligning a Segmented Telescope Mirror

A phase sensor has been developed for use in aligning a segmented telescope mirror to within a fraction of a wavelength in piston. (As used here, piston signifies displacement of a mirror segment along the optical axis of the telescope.) Such precise alignment is necessary in order to realize the full benefit of the large aperture achievable through segmentation. This phase sensor is achromatic. It is based on two-wavelength shearing interferometry, and can be modified to utilize an extended or broad-band (e.g., white) light source. The sensor optics include a ruled diffraction grating and an imaging lens. The sensor can measure the piston shift between segments as well as aberrations of the segments. It can measure the surface error of an individual segment, making it possible to compensate for the error with optimal amount(s) of piston and/or tilt. The precise capture range of the sensor depends partly on the telescope design; the largest relative piston shifts measurable by use of this sensor are of the order of 100 m. The accuracy of the sensor also depends partly on the telescope design; in general, the accuracy is sufficient to enable alignment to within approximately half a wavelength. The interferometric image is digitized and processed by a simple algorithm in real time, and the output of the algorithm can be used to maintain alignment in real time, even in the presence of atmospheric turbulence. The sensor is robust. Through calibration, it can be made insensitive to (and, hence, tolerant of) misalignments and aberrations of its own optics, most aberrations of the telescope as a whole (in contradistinction to aberrations of individual segments), and most aberrations introduced by atmospheric turbulence

Stahl, Philip↗
NASA NTRS2003

Interferometer for Measuring Displacement to Within 20 pm

An optical heterodyne interferometer that can be used to measure linear displacements with an error <=20 pm has been developed. The remarkable accuracy of this interferometer is achieved through a design that includes (1) a wavefront split that reduces (relative to amplitude splits used in other interferometers) self interference and (2) a common-optical-path configuration that affords common-mode cancellation of the interference effects of thermal-expansion changes in optical-path lengths. The most popular method of displacement- measuring interferometry involves two beams, the polarizations of which are meant to be kept orthogonal upstream of the final interference location, where the difference between the phases of the two beams is measured. Polarization leakages (deviations from the desired perfect orthogonality) contaminate the phase measurement with periodic nonlinear errors. In commercial interferometers, these phase-measurement errors result in displacement errors in the approximate range of 1 to 10 nm. Moreover, because prior interferometers lack compensation for thermal-expansion changes in optical-path lengths, they are subject to additional displacement errors characterized by a temperature sensitivity of about 100 nm/K. Because the present interferometer does not utilize polarization in the separation and combination of the two interfering beams and because of the common-mode cancellation of thermal-expansion effects, the periodic nonlinear errors and the sensitivity to temperature changes are much smaller than in other interferometers

Zhao, Feng↗
NASA NTRS2011

Fluorescence Excitation Models of Ammonia and Amidogen Radical (NH2) in Comets: Application to Comet C/2004 Q2 (Machholz)

Ammonia is a major reservoir of nitrogen atoms in cometary materials. However, detections of ammonia in comets are rare, with several achieved at radio wavelengths. A few more detections were obtained through near-infrared observations (around the 3 m wavelength region), but moderate relative velocity shifts are required to separate emission lines of cometary ammonia from telluric absorption lines in the 3 micron wavelength region. On the other hand, the amidogen radical (NH2 -- a photodissociation product of ammonia in the coma) also shows rovibrational emission lines in the 3 micron wavelength region. Thus, gas production rates for ammonia can be determined from the rovibrational emission lines of ammonia (directly) and amidogen radical (indirectly) simultaneously in the near-infrared. In this article, we present new fluorescence excitation models for cometary ammonia and amidogen radical in the near-infrared, and we apply these models to the near-infrared high-dispersion spectra of comet C/2004 Q2 (Machholz) to determine the mixing ratio of ammonia to water in the comet. Based on direct detection of NH3 lines, the mixing ratio of NH3/H2O is 0.46% +/- 0.03% in C/2004 Q2 (Machholz), in agreement with other results. The mixing ratio of ammonia determined from the NH2 observations (0.31% -- 0.79%) is consistent but has relatively larger error, owing to uncertainty in the photodissociation rates of ammonia. At the present level of accuracy, we confirm that NH3 could be the sole parent of NH2 in this comet.

Kawakita, Hideyo↗
NASA NTRS2010

Precise Orbit Determination for LEO Spacecraft Using GNSS Tracking Data from Multiple Antennas

To support various applications, certain Earth-orbiting spacecrafts (e.g., SRTM, COSMIC) use multiple GNSS antennas to provide tracking data for precise orbit determination (POD). POD using GNSS tracking data from multiple antennas poses some special technical issues compared to the typical single-antenna approach. In this paper, we investigate some of these issues using both real and simulated data. Recommendations are provided for POD with multiple GNSS antennas and for antenna configuration design. The observability of satellite position with multiple antennas data is compared against single antenna case. The impact of differential clock (line biases) and line-of-sight (up, along-track, and cross-track) on kinematic and reduced-dynamic POD is evaluated. The accuracy of monitoring the stability of the spacecraft structure by simultaneously performing POD of the spacecraft and relative positioning of the multiple antennas is also investigated.

Kuang, Da↗
NASA NTRS2010

Preliminary Design of the Guidance, Navigation, and Control System of the Altair Lunar Lander

Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. This paper provides an overview of a preliminary design of the GN&C system of the Lunar Lander Altair. Key functions performed by the GN&C system in various mission phases will first be described. A set of placeholder GN&C sensors that is needed to support these functions is next described. To meet Crew safety requirements, there must be high degrees of redundancy in the selected sensor configuration. Two sets of thrusters, one on the Ascent Module (AM) and the other on the Descent Module (DM), will be used by the GN&C system. The DM thrusters will be used, among other purposes, to perform course correction burns during the Trans-lunar Coast. The AM thrusters will be used, among other purposes, to perform precise angular and translational controls of the ascent module in order to dock the ascent module with Orion. Navigation is the process of measurement and control of the spacecraft's "state" (both the position and velocity vectors of the spacecraft). Tracking data from the Earth-Based Ground System (tracking antennas) as well as data from onboard optical sensors will be used to estimate the vehicle state. A driving navigation requirement is to land Altair on the Moon with a landing accuracy that is better than 1 km (radial 95%). Preliminary performance of the Altair GN&C design, relative to this and other navigation requirements, will be given. Guidance is the onboard process that uses the estimated state vector, crew inputs, and pre-computed reference trajectories to guide both the rotational and the translational motions of the spacecraft during powered flight phases. Design objectives of reference trajectories for various mission phases vary. For example, the reference trajectory for the descent "approach" phase (the last 3-4 minutes before touchdown) will sacrifice fuel utilization efficiency in order to provide landing site visibility for both the crew and the terrain hazard detection sensor system. One output of Guidance is the steering angle commands sent to the 2 degree-of-freedom (dof) gimbal actuation system of the descent engine. The engine gimbal actuation system is controlled by a Thrust Vector Control algorithm that is designed taking into account the large quantities of sloshing liquids in tanks mounted on Altair. In this early design phase of Altair, the GN&C system is described only briefly in this paper and the emphasis is on the GN&C architecture (that is still evolving). Multiple companion papers will provide details that are related to navigation, optical navigation, guidance, fuel sloshing, rendezvous and docking, machine-pilot interactions, and others. The similarities and differences of GN&C designs for Lunar and Mars landers are briefly compared.

Lee, Allan Y.↗
NASA NTRS2016

Submillimeter and Far-Infrared Dielectric Properties of Thin Films

The complex dielectric function enables the study of a material's refractive and absorptive properties and provides information on a material's potential for practical application. Commonly employed line shape profile functions from the literature are briefly surveyed and their suitability for representation of dielectric material properties are discussed. An analysis approach to derive a material's complex dielectric function from observed transmittance spectra in the far-infrared and submillimeter regimes is presented. The underlying model employed satisfies the requirements set by the Kramers-Kronig relations. The dielectric function parameters derived from this approach typically reproduce the observed transmittance spectra with an accuracy of less than 4%.

Cataldo, Giuseppe↗
NASA NTRS2017

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Subpixel↗
NASA NTRS2019

Satellite Salinity Observing System: Recent Discoveries and the Way Forward

Advances in L-band microwave satellite radiometry in the past decade, pioneered by ESA's SMOS and NASA's Aquarius and SMAP missions, have demonstrated an unprecedented capability to observe global sea surface salinity (SSS) from space. Measurements from these missions are the only means to probe the very-near surface salinity (top cm), providing a unique monitoring capability for the interfacial exchanges of water between the atmosphere and the upper-ocean, and delivering a wealth of information on various salinity processes in the ocean, linkages with the climate and water cycle, including land-sea connections, and providing constraints for ocean prediction models. The satellite SSS data are complimentary to the existing in situ systems such as Argo that provide accurate depiction of large-scale salinity variability in the open ocean but under-sample mesoscale variability, coastal oceans and marginal seas, and energetic regions such as boundary currents and fronts. In particular, salinity remote sensing has proven valuable to systematically monitor the open oceans as well as coastal regions up to approximately 40 km from the coasts. This is critical to addressing societally relevant topics, such as land-sea linkages, coastal-open ocean exchanges, research in the carbon cycle, near-surface mixing, and air-sea exchange of gas and mass. In this paper, we provide a community perspective on the major achievements of satellite SSS for the aforementioned topics, the unique capability of satellite salinity observing system and its complementarity with other platforms, uncertainty characteristics of satellite SSS, and measurement versus sampling errors in relation to in situ salinity measurements. We also discuss the need for technological innovations to improve the accuracy, resolution, and coverage of satellite SSS, and the way forward to both continue and enhance salinity remote sensing as part of the integrated Earth Observing System in order to address societal needs.

Vinogradova, Nadya↗
NASA NTRS2019

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗
NASA NTRSDate not supplied

New Global Ocean Color Sensor: OCI on PACE

- OCI will provide TOA radiances at ~1km spatial resolution, from 340nm (315nm?) to 2260nm, hyperspectral from 340nm to 890nm, 2 day global coverage - OCI will continue and enhance NASA’s earth system data records for ocean color (heritage sensors: SeaWiFS, MODIS, VIIRS) - OCI flight unit is close to being ready for testing (planned for March 2022 to September 2022) - OCI ETU (Engineering Test Unit) completed testing summer 2021, results look promising (see next presentation) - On-orbit calibration will combine successful trending approaches from previous sensors (2 solar diffusers, QVD, lunar gain trending, spectral trending) - New calibration approaches for OCI: large QVD, dim diffuser for linearity trending, lunar hysteresis trending - OCI will be characterized prelaunch with an ambitious goal of 0.5% relative uncertainty; absolute uncertainty will be about 2% (before vicarious calibration); expected on-orbit gain trending accuracy is 0.2% or better - More info on PACE and OCI can be found at https://pace.oceansciences.org/

radiometer↗
NASA NTRSDate not supplied

Feasibility of using Low-Cost COTS Sensors for Particulate Monitoring in Space Missions

Real-time measurement of particles suspended in the spacecraft cabin is of great importance to verify that maximum allowable dust concentrations are not exceeded. This is primarily to protect astronaut health, but also has implications for dust-sensitive equipment. Recently, there is growing interest in low-cost commercial off-the-shelf (COTS) particle sensors by air quality researchers for their ability to map concentrations of airborne particulate matter in various terrestrial settings. In addition to low cost (< $2,000), the compact size and minimal weight of these sensors make them a potential choice for space missions. The detection mechanism for these aerosol sensors is typically measurement of light scattered by particles as they flow through a sensing volume. The amount of scattered light for detection depends on the particle size, shape, density, and refractive index of the particle material. Ideally, particle instruments should be calibrated with reference instruments for each different type of aerosol measurement. In this study we review multiple parameters that may impact the performance of state-of-the-art low-cost aerosol sensors. Environmental factors such as temperature, relative humidity, low ambient pressure, radiation and charge environment, partial-gravity and microgravity can affect the accuracy of particle measurements. Characteristics of the dust aerosols including particle size distribution, aerosol composition, refractive index, morphology and concentration levels also affect the measurement accuracy. Finally, we look at these parameters and issues with respect to an example COTS low-cost aerosol sensor. Instrument performance specifications are evaluated, and experiments are performed to measure real-time concentrations of Arizona Road Dust (a terrestrial reference test dust) and lunar dust simulant in a laboratory chamber. Overall, this study provides insight for evaluating spacecraft particulate monitoring technologies and raises questions to be answered before incorporating low-cost COTS sensors in future space missions to dusty destinations.

lunar dust↗
NASA NTRS2022

Local Scale (3-M) Soil Moisture Mapping Using SMAP and Planet Superdove

A capability for mapping meter-level resolution soil moisture with frequent temporal sampling over large regions is essential for quantifying local-scale environmental heterogeneity and eco-hydrologic behavior. However, available surface soil moisture (SSM) products generally involve much coarser grain sizes ranging from 30 m to several 10s of kilometers. Hence a new method is proposed to estimate 3-m resolution SSM using a combination of multi-sensor fusion, machine- learning (ML) and Cumulative Distribution Function (CDF) matching approaches. This method established favorable SSM correspondence between 3-m pixels and overlying 9-km grid cells from overlapping Planet SuperDove (PSD) observations and NASA Soil Moisture Active-Passive (SMAP) mission products. The resulting 3-m SSM predictions showed improved accuracy by reducing ab- solute bias and RMSE by ~0.01 cm3/cm3 over the original SMAP data in relation to in-situ soil moisture measurements for the Australian Yanco region, while preserving the high sampling frequency (1-3 day global revisit) and sensitivity to surface wetness (R 0.865) from SMAP. Heterogeneous soil moisture distributions varying with vegetation biomass gradients and irrigation regimes were generally captured within a selected study area. Further algorithm refinement and implementation for regional applications will allow for improvement in water resources management, precision agriculture, and disaster forecasts and responses.

soil moisture↗
NASA NTRSDate not supplied

A Machine Learning Approach for the Remote Sensing Retrieval of Oil Spills from Polarimetric Measurements

The Fresnel laws of specular reflection directly connect remote sensing observations of light polarization within the sunglint region to the ocean surface refractive index. This parameter is instrumental to identify areas affected by oil, or any other floating substance capable of modifying the refractive index of pure seawater. In preparation for the NASA Plankton, Aerosol, ocean Ecosystem (PACE) mission, we are developing an advanced retrieval scheme that exploits such measurements to deliver the refractive index as an operational product. The original method was developed based on observations of the airborne Research Scanning Polarimeter. Here we present several aspects related to the extension of this technique to the PACE HARP-2 sensor (especially regarding the projected accuracy), and discuss preliminary results obtained by applying neural-network trainings to look-up tables produced with the forward radiative transfer code, with the goal of improving the computational performance. Success in the final implementation will guarantee a version of the retrieval algorithm suitable to fast-response needs and disaster management.

machine learning↗
NASA NTRSDate not supplied

Evaluation of Markerless Motion Capture for Monitoring Sensorimotor Performance

BACKGROUND Astronauts returning from long-duration exposure to microgravity frequently exhibit alterations in sensorimotor function leading to postural imbalance, impaired locomotion, and operational challenges to manual control. Mission duration and individual responses often influence both the severity of performance decrements and the variability in adaptation timelines. Postflight disruptions during functional tasks are often detected through body-worn inertial measurement unit (IMU) devices. While IMU sensors are relatively compact, the long-term wear may lead to discomfort, displacement of the sensors on the body, and restrictions in movement or crew behavior. Although IMU data offers valuable insights from a research standpoint, interpreting changes in pre- and post-flight measures can be difficult for crew support personnel beyond the research domain, which can hinder the application for medical assessments and rehabilitation. Finally, the availability of inertial sensors in-flight is limited. There is a need for unobtrusive monitoring tools to improve our ability to monitor adaptation following gravitational transitions in various postflight evaluations and rehabilitation settings. Markerless motion capture (MMC) is an evolving unobtrusive technology that builds upon decades of research with marker-based motion capture systems to provide 3D human pose estimation from multiple synchronized 2D camera views using deep learning algorithms. Markerless technology can revolutionize how data is captured pre- and post-flight and potentially in-flight during intravehicular activity by enabling pose estimation of multiple crew members from onboard camera hardware. METHODS The following presents the initial evaluation of a state-of-the-art commercial-off-the-shelf MMC system, Theia Markerless, compared to IMU devices during various ground-based functional tasks and environmental conditions. The featured functional tasks include assessments from Human Research Program (HRP) funded studies such as Sensorimotor Standard Measures and Sensorimotor Assessments. Synchronous data collected using both motion capture and IMUs are analyzed for six male and female subjects of varying anthropometry. The analysis includes limited assessments of clothing, capture volume configurations, and the tool's sensitivity to detecting performance changes after a spaceflight analog centrifuge exposure. The development of visualization tools to enhance the application of the pose estimation output is also presented. RESULTS Initial results demonstrate comparable root mean square error (RMSE) to existing literature evaluating markerless and marker-based motion capture systems. Considering the relative functional range of motion of the cervical spine, normalized error values for the markerless system’s accuracy of the head was 0.032 in pitch, 0.025 in roll, and 0.018 in yaw plane of motion across a subset of functional tasks. The raw RMSE values were 3.49, 2.25, and 2.81 degrees respectively. For the torso, results suggest normalized errors of 0.469 in pitch, 0.191 in roll, and 0.307 in yaw planes of motion and raw RMSE values of 3.52, 1.53, and 3.07 degrees respectively. The data suggests the functional demands of a particular task influences the estimation accuracy of the MMC system where more dynamic motion and cases where subjects are not upright may introduce diminished tracking accuracy. DISCUSSION The following work lays the foundation for future implementations leveraging markerless motion capture to assess the time course of recovery and provide insight for rehabilitation protocols to enhance crew readiness for the resumption of daily activities. These tools offer effective methods for anonymizing sensitive crew data, facilitating numerous applications across research, medical, and rehabilitation groups. Collaborations with the Anthropometry and Biomechanics Facility will provide further comparisons of the Markerless system to a marker-based system. ACKNOWLEDGEMENT</ This work is supported by NASA’s Exploration Systems Development Mission Directorate Mars Campaign Office Crew Health Countermeasures.

Hannah M. Weiss↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to sub-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models: Preprint

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to inter-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of said approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating two different clipping correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons will be performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The models can improve accuracy up to 3% in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

clipping↗