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At least 235 records · Page 13

New Gear Transmission Error Measurement System Designed

The prime source of vibration and noise in a gear system is the transmission error between the meshing gears. Transmission error is caused by manufacturing inaccuracy, mounting errors, and elastic deflections under load. Gear designers often attempt to compensate for transmission error by modifying gear teeth. This is done traditionally by a rough "rule of thumb" or more recently under the guidance of an analytical code. In order for a designer to have confidence in a code, the code must be validated through experiment. NASA Glenn Research Center contracted with the Design Unit of the University of Newcastle in England for a system to measure the transmission error of spur and helical test gears in the NASA Gear Noise Rig. The new system measures transmission error optically by means of light beams directed by lenses and prisms through gratings mounted on the gear shafts. The amount of light that passes through both gratings is directly proportional to the transmission error of the gears. A photodetector circuit converts the light to an analog electrical signal. To increase accuracy and reduce "noise" due to transverse vibration, there are parallel light paths at the top and bottom of the gears. The two signals are subtracted via differential amplifiers in the electronics package. The output of the system is 40 mV/mm, giving a resolution in the time domain of better than 0.1 mm, and discrimination in the frequency domain of better than 0.01 mm. The new system will be used to validate gear analytical codes and to investigate mechanisms that produce vibration and noise in parallel axis gears.

Oswald, Fred B.↗

Gear Transmission Error Measurement System Made Operational

A system directly measuring the transmission error between the meshing spur or helical gears was installed at the NASA Glenn Research Center and made operational in August 2001. This system employs light beams directed by lenses and prisms through gratings mounted on the two gear shafts. The amount of light that passes through both gratings is directly proportional to the transmission error of the gears. The device is capable of resolution better than 0.1 mm (one thousandth the thickness of a human hair). The measured transmission error can be displayed in a "map" that shows how the transmission error varies with the gear rotation or it can be converted to spectra to show the components at the meshing frequencies. Accurate transmission error data will help researchers better understand the mechanisms that cause gear noise and vibration and will lead to The Design Unit at the University of Newcastle in England specifically designed the new system for NASA. It is the only device in the United States that can measure dynamic transmission error at high rotational speeds. The new system will be used to develop new techniques to reduce dynamic transmission error along with the resulting noise and vibration of aeronautical transmissions.

Oswald, Fred B.↗

Application of Parallel Adjoint-Based Error Estimation and Anisotropic Grid Adaptation for Three-Dimensional Aerospace Configurations

This paper demonstrates the extension of error estimation and adaptation methods to parallel computations enabling larger, more realistic aerospace applications and the quantification of discretization errors for complex 3-D solutions. Results were shown for an inviscid sonic-boom prediction about a double-cone configuration and a wing/body segmented leading edge (SLE) configuration where the output function of the adjoint was pressure integrated over a part of the cylinder in the near field. After multiple cycles of error estimation and surface/field adaptation, a significant improvement in the inviscid solution for the sonic boom signature of the double cone was observed. Although the double-cone adaptation was initiated from a very coarse mesh, the near-field pressure signature from the final adapted mesh compared very well with the wind-tunnel data which illustrates that the adjoint-based error estimation and adaptation process requires no a priori refinement of the mesh. Similarly, the near-field pressure signature for the SLE wing/body sonic boom configuration showed a significant improvement from the initial coarse mesh to the final adapted mesh in comparison with the wind tunnel results. Error estimation and field adaptation results were also presented for the viscous transonic drag prediction of the DLR-F6 wing/body configuration, and results were compared to a series of globally refined meshes. Two of these globally refined meshes were used as a starting point for the error estimation and field-adaptation process where the output function for the adjoint was the total drag. The field-adapted results showed an improvement in the prediction of the drag in comparison with the finest globally refined mesh and a reduction in the estimate of the remaining drag error. The adjoint-based adaptation parameter showed a need for increased resolution in the surface of the wing/body as well as a need for wake resolution downstream of the fuselage and wing trailing edge in order to achieve the requested drag tolerance. Although further adaptation was required to meet the requested tolerance, no further cycles were computed in order to avoid large discrepancies between the surface mesh spacing and the refined field spacing.

Lee-Rausch, E. M.↗

CORRELATED ERRORS IN EARTH POINTING MISSIONS

Two different Earth-pointing missions dealing with attitude control and dynamics changes illustrate concerns with correlated error sources and coupled effects that can occur. On the OrbView-2 (OV-2) spacecraft, the assumption of a nearly-inertially-fixed momentum axis was called into question when a residual dipole bias apparently changed magnitude. The possibility that alignment adjustments and/or sensor calibration errors may compensate for actual motions of the spacecraft is discussed, and uncertainties in the dynamics are considered. Particular consideration is given to basic orbit frequency and twice orbit frequency effects and their high correlation over the short science observation data span. On the Tropical Rainfall Measuring Mission (TRMM) spacecraft, the switch to a contingency Kalman filter control mode created changes in the pointing error patterns. Results from independent checks on the TRMM attitude using science instrument data are reported, and bias shifts and error correlations are discussed. Various orbit frequency effects are common with the flight geometry for Earth pointing instruments. In both dual-spin momentum stabilized spacecraft (like OV-2) and three axis stabilized spacecraft with gyros (like TRMM under Kalman filter control), changes in the initial attitude state propagate into orbit frequency variations in attitude and some sensor measurements. At the same time, orbit frequency measurement effects can arise from dynamics assumptions, environment variations, attitude sensor calibrations, or ephemeris errors. Also, constant environment torques for dual spin spacecraft have similar effects to gyro biases on three axis stabilized spacecraft, effectively shifting the one-revolution-per-orbit (1-RPO) body rotation axis. Highly correlated effects can create a risk for estimation errors particularly when a mission switches an operating mode or changes its normal flight environment. Some error effects will not be obvious from attitude sensor measurement residuals, so some independent checks using imaging sensors are essential and derived science instrument attitude measurements can prove quite valuable in assessing the attitude accuracy.

Steve Bilanow↗

Analyzing Software Requirements Errors in Safety-Critical, Embedded Systems

This paper analyzes the root causes of safety-related software errors in safety-critical, embedded systems. The results show that software errors identified as potentially hazardous to the system tend to be produced by different error mechanisms than non- safety-related software errors. Safety-related software errors are shown to arise most commonly from (1) discrepancies between the documented requirements specifications and the requirements needed for correct functioning of the system and (2) misunderstandings of the software's interface with the rest of the system. The paper uses these results to identify methods by which requirements errors can be prevented. The goal is to reduce safety-related software errors and to enhance the safety of complex, embedded systems.

Lutz, Robyn R.↗

FDDI network test adaptor error injection circuit

An apparatus for injecting errors into a FDDI token ring network is disclosed. The error injection scheme operates by fooling a FORMAC into thinking it sent a real frame of data. This is done by using two RAM buffers. The RAM buffer normally accessed by the RBC/DPC becomes a SHADOW RAM during error injection operation. A dummy frame is loaded into the shadow RAM in order to fool the FORMAC. This data is just like the data that would be used if sending a normal frame, with the restriction that it must be shorter than the error injection data. The other buffer, the error injection RAM, contains the error injection frame. The error injection data is sent out to the media by switching a multiplexor. When the FORMAC is done transmitting the data, the multiplexor is switched back to the normal mode. Thus, the FORMAC is unaware of what happened and the token ring remains operational.

Eckenrode, Thomas↗

Measuring Cyclic Error in Laser Heterodyne Interferometers

An improved method and apparatus have been devised for measuring cyclic errors in the readouts of laser heterodyne interferometers that are configured and operated as displacement gauges. The cyclic errors arise as a consequence of mixing of spurious optical and electrical signals in beam launchers that are subsystems of such interferometers. The conventional approach to measurement of cyclic error involves phase measurements and yields values precise to within about 10 pm over air optical paths at laser wavelengths in the visible and near infrared. The present approach, which involves amplitude measurements instead of phase measurements, yields values precise to about .0.1 microns . about 100 times the precision of the conventional approach. In a displacement gauge of the type of interest here, the laser heterodyne interferometer is used to measure any change in distance along an optical axis between two corner-cube retroreflectors. One of the corner-cube retroreflectors is mounted on a piezoelectric transducer (see figure), which is used to introduce a low-frequency periodic displacement that can be measured by the gauges. The transducer is excited at a frequency of 9 Hz by a triangular waveform to generate a 9-Hz triangular-wave displacement having an amplitude of 25 microns. The displacement gives rise to both amplitude and phase modulation of the heterodyne signals in the gauges. The modulation includes cyclic error components, and the magnitude of the cyclic-error component of the phase modulation is what one needs to measure in order to determine the magnitude of the cyclic displacement error. The precision attainable in the conventional (phase measurement) approach to measuring cyclic error is limited because the phase measurements are af-

Ryan, Daniel↗

Reflector Surface Error Compensation in Dual-Reflector Antennas

By probing the field on a small subreflector at a minimal number of points, the main reflector surface errors can be obtained and subsequently used to design a phase-correction subreflector that can compensate for main reflector errors. The compensating phase-error profile across the subreflector can be achieved either by a surface deformation or by the use of an array of elements such as patch antennas that can cause a phase shift between the incoming and outgoing fields. The second option is of primary interest here, but the methodology can be applied to either case. The patch array is most easily implemented on a planar surface. Therefore, the example of a flat subreflector and a parabolic main reflector (a Newtonian dual reflector system) is considered in this work. The subreflector is assumed to be a reflector array covered with patch elements. The phase variation on a subreflector can be detected by a small number of receiving patch elements (probes). By probing the phase change at these few selected positions on the subreflector, the phase error over the entire surface can be recovered and used to change the phase of all the patch elements covering the subreflector plane to compensate for main reflector errors. This is accomplished by using a version of sampling theorem on the circular aperture. The sampling is performed on the phase-error function on the circular aperture of the main reflector by a method developed using Zernike polynomials. This method is based upon and extended from a theory previously proposed and applied to reflector aperture integration. This sampling method provides for an exact retrieval of the coefficients of up to certain orders in the expansion of the phase function, from values on a specifically calculated set of points in radial and azimuthal directions in the polar coordinate system, on the circular reflector aperture. The corresponding points on the subreflector are then obtained and, by probing the fields at these points, a set of phase values is determined that is then transferred back to the main reflector aperture for recovering the phase function. Once this function is recovered, the corresponding phase function on the subreflector is calculated and used to compensate for main reflector surface errors. In going back and forth between sub and main reflectors, geometrical (ray) optics is employed, which even though it ignores edge diffraction and other effects, is shown to be accurate for phase recovery.

Jamnejad, Vahraz↗

Impact of Non-Gaussian Error Volumes on Conjunction Assessment Risk Analysis

An understanding of how an initially Gaussian error volume becomes non-Gaussian over time is an important consideration for space-vehicle conjunction assessment. Traditional assumptions applied to the error volume artificially suppress the true non-Gaussian nature of the space-vehicle position uncertainties. For typical conjunction assessment objects, representation of the error volume by a state error covariance matrix in a Cartesian reference frame is a more significant limitation than is the assumption of linearized dynamics for propagating the error volume. In this study, the impact of each assumption is examined and isolated for each point in the volume. Limitations arising from representing the error volume in a Cartesian reference frame is corrected by employing a Monte Carlo approach to probability of collision (Pc), using equinoctial samples from the Cartesian position covariance at the time of closest approach (TCA) between the pair of space objects. A set of actual, higher risk (Pc >= 10 (exp -4)+) conjunction events in various low-Earth orbits using Monte Carlo methods are analyzed. The impact of non-Gaussian error volumes on Pc for these cases is minimal, even when the deviation from a Gaussian distribution is significant.

Ghrist, Richard W.↗

Bayes Error Rate Estimation Using Classifier Ensembles

The Bayes error rate gives a statistical lower bound on the error achievable for a given classification problem and the associated choice of features. By reliably estimating th is rate, one can assess the usefulness of the feature set that is being used for classification. Moreover, by comparing the accuracy achieved by a given classifier with the Bayes rate, one can quantify how effective that classifier is. Classical approaches for estimating or finding bounds for the Bayes error, in general, yield rather weak results for small sample sizes; unless the problem has some simple characteristics, such as Gaussian class-conditional likelihoods. This article shows how the outputs of a classifier ensemble can be used to provide reliable and easily obtainable estimates of the Bayes error with negligible extra computation. Three methods of varying sophistication are described. First, we present a framework that estimates the Bayes error when multiple classifiers, each providing an estimate of the a posteriori class probabilities, a recombined through averaging. Second, we bolster this approach by adding an information theoretic measure of output correlation to the estimate. Finally, we discuss a more general method that just looks at the class labels indicated by ensem ble members and provides error estimates based on the disagreements among classifiers. The methods are illustrated for artificial data, a difficult four-class problem involving underwater acoustic data, and two problems from the Problem benchmarks. For data sets with known Bayes error, the combiner-based methods introduced in this article outperform existing methods. The estimates obtained by the proposed methods also seem quite reliable for the real-life data sets for which the true Bayes rates are unknown.

Tumer, Kagan↗

Towards the 1 mm/y Stability of the Radial Orbit Error at Regional Scales

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS, SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West "order-1" pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Precision Orbit Determination (POD)↗

Application of Exactly Linearized Error Transport Equations to AIAA CFD Prediction Workshops

The computational fluid dynamics (CFD) prediction workshops sponsored by the AIAA have created invaluable opportunities in which to discuss the predictive capabilities of CFD in areas in which it has struggled, e.g., cruise drag, high-lift, and sonic boom pre diction. While there are many factors that contribute to disagreement between simulated and experimental results, such as modeling or discretization error, quantifying the errors contained in a simulation is important for those who make decisions based on the computational results. The linearized error transport equations (ETE) combined with a truncation error estimate is a method to quantify one source of errors. The ETE are implemented with a complex-step method to provide an exact linearization with minimal source code modifications to CFD and multidisciplinary analysis methods. The equivalency of adjoint and linearized ETE functional error correction is demonstrated. Uniformly refined grids from a series of AIAA prediction workshops demonstrate the utility of ETE for multidisciplinary analysis with a connection between estimated discretization error and (resolved or under-resolved) flow features.

Derlaga, Joseph M.↗

CME Velocity and Acceleration Error Estimates Using the Bootstrap Method

The bootstrap method is used to determine errors of basic attributes of coronal mass ejections (CMEs) visually identified in images obtained by the Solar and Heliospheric Observatory (SOHO) mission's Large Angle and Spectrometric Coronagraph (LASCO) instruments. The basic parameters of CMEs are stored, among others, in a database known as the SOHO/LASCO CME catalog and are widely employed for many research studies. The basic attributes of CMEs (e.g. velocity and acceleration) are obtained from manually generated height-time plots. The subjective nature of manual measurements introduces random errors that are difficult to quantify. In many studies the impact of such measurement errors is overlooked. In this study we present a new possibility to estimate measurements errors in the basic attributes of CMEs. This approach is a computer-intensive method because it requires repeating the original data analysis procedure several times using replicate datasets. This is also commonly called the bootstrap method in the literature. We show that the bootstrap approach can be used to estimate the errors of the basic attributes of CMEs having moderately large numbers of height-time measurements. The velocity errors are in the vast majority small and depend mostly on the number of height-time points measured for a particular event. In the case of acceleration, the errors are significant, and for more than half of all CMEs, they are larger than the acceleration itself.

Michalek, Grzegorz↗

Observation Error Specification for Near-Surface Soil Moisture Assimilation: Does It Matter?

The observation error variances assumed in the data assimilation (DA) of remotely sensed near-surface soil moisture observations are known to have unrealistic spatial patterns. The temporal variability in the errors is also typically neglected. Soil moisture errors cannot be directly calculated at large scales, and the globally distributed errors are unknown. We apply several approaches to estimating the observation errors (R matrix) for near-surface soil moisture DA experiments, to establish whether the assumed errors are important to the DA performance, and hence whether uncertainty in the observation error specification is a likely source of uncertainty in soil moisture DA output.

Draper, Clara↗

Addressing Human Error in International Space Station Flight Control Teams: Advances in Ground Training for Science Operators

In flight control, as with any human in the loop system, operator error is an inevitable reality. On the International Space Station (ISS) where crew time and physical resources are precious and often irreplaceable, operator errors can result in significant, irreversible consequences. Flight controllers at the Payload Operations Integration Center (POIC) located at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama know this reality well. At the POIC, operator errors can be caused by a variety of factors, from poor hardware or software design to environmental factors such as time pressure or fatigue. The most difficult errors to address, however, are those which result from ineffective teamwork.Academic research in teamwork has resulted in the identification of many factors which make cross-functional teaming difficult, including leadership, trust building, and communication challenges. These factors, especially when combined with the challenging environmental factors flight control teams must contend with daily, make the goal of minimizing operator errors in payload operations challenging to achieve. To address such teamwork errors, trainers at the POIC have drawn best practices from high reliability industries such as commercial aviation, healthcare, and nuclear power plants, as well as from our sister ISS control center in Houston, Texas, to develop and institute a new training program focused specifically on teamwork skills.This training program, called the Team Skills Curriculum, is based on the concept of Crew Resource Management (CRM) which was developed by NASA in the 1970s for the commercial aviation industry in response to a series of aviation disasters resulting from ineffective teamwork. CRM was later tailored by the Johnson Space Center (JSC) for use in astronaut and flight control training. The result, called Space Flight Resource Management (SFRM) was formally introduced into manned spaceflight training in the late 90s. SFRM has evolved over the years, but the focus has remained on helping operators develop the skills needed to work as part of an effective team. Using these concepts as well as the latest research in cross-functional teaming and data on specific errors occurring at the POIC, trainers in the integrated flight control training branch created a custom training program for both new and certified payload operations specialists.

Harris, Samantha S.↗

Error Sources and Mitigation Strategies for Thermocouples Integrated in Flexible Thermal Protection System Materials

Brief Presenter Biography:Ruth Miller is an aer-ospace systems engineer in the Entry Systems and Ve-hicle Development Branch at NASA Ames Research Center.Introduction:The flexible thermal protection sys-tem (FTPS) on NASA’s Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) vehicle will be in-strumented with thermocouples (TCs) to measure the in-depth thermal response during entry into Earth’s atmos-phere[1, 2]. Accurate flight temperature measurements are critical for verifying vehicle performance during the flight test and reducing uncertainties in the thermal models.However,the deployable nature of inflatable decelerator technology presents challengesfor integrat-ing TCs, specifically the TCsneed to be compactableand cannot damage the FTPSnor the inflatable structure(IS).Unlike traditional rigid aeroshells, routing TCsthrough the thickness of the FTPS could cause signifi-cant damage during packing of the deployable aeroshellbecause the different layers may shift small amounts in relation to each other imparting strain on the TCsand FTPS materials. The LOFTID TCleads are routed from the measurement location back to the data acquisition system in the vehicle centerbody within the same FTPS layer that they are monitoring the temperature. This ap-proach eliminates the need to put holes in the FTPS lay-ers,butas a consequence,the insulated TCleads travel for an appreciable distance through a region that will expose them to high temperaturesand large thermal gra-dients.LOFTID’s TCswere baselined to be commercially available Type K TCswith a binder impregnated glass braid insulation. These TCswere chosen because they had been used successfully on IRVE-3 and in ground-based arc jet testing. Additionally, these TCsdid notdamage the FTPS nor IS during packing and deploy-ment testing. However, the glass braid insulation is only rated to a maximum continuous use temperature of 482ºC. For reference, the duration of the heat pulse on the LOFTID vehicle is on the order of minutes and themaximum predicted temperaturebeneaththe outermost FTPS layersis 1350ºC.Ground-based testing in a tube furnace at NASA Ames Research Centerwas conducted to determine if the baseline TCsrouted through FTPS samples would survive and provide accurate temperature measure-mentsat LOFTID flight-relevant temperatures[3].The test results showed large measurement errors occurred beginning at approximately 400°C due to conductive deposits on the TCinsulation electrically shorting the TCleads.The conductive deposits and thus electrical shorting weredetermined to be caused by twoerror sources:1.The organic binder on the TCinsulation carbon-izingin a high temperature, low oxygen envi-ronment2.Decomposition products from the FTPSperme-atingthe braided TC insulationFurther testing in the tube furnace demonstrated that heat cleaning the TCinsulation effectivelyremovedthe organic binder andeliminatedthe first error source.The second error sourcewas shown to be mitigated by the addition of amica wraparound each individual TCleadtoact as an impermeable barrier.To understand the applicability of theground-based tube furnace test results to flight,anarc jet testseriesat Boeing’s Large Core Arc Tunnel (LCAT) facilitywas conducted[4].The error sourcesand mitigation strate-giesidentified in the tube furnace testing were substan-tiatedin the arc jet testing.However, the arc jet testing also revealed three new error sources:1.Glass TCinsulation meltingwhich resultsin electrical shorting of the TCeither through di-rect contact between the two leads or through the electrically conductive FTPS materials2.TCwire meltingwhich results in a noisy and/or open-loop TCresponse3.Type K TCwire green-rotwhich results in large calibration errors Scope of the Presentation:This presentation will include a brief discussion onthe effect of electrical shorting on the output of a TC(i.e. how to identify elec-trical shorting in TCdataand what the associated erroris).The tube furnace and arc jet test resultswill be dis-cussedand the solutions LOFTID is implementing to mitigate the error sourcesidentified in the tube furnace and arc jet testingwill be presented.Additionally, futureresearch and development work to eliminateTCerror sourcesfor future missionswill be recommended.

R A Miller↗

Quantifying Errors in 3D CME Parameters Derived from Synthetic Data Using White-Light Reconstruction Techniques

Current efforts in space weather forecasting of CMEs have been focused on predicting their arrival time and magnetic structure. To make these predictions, methods have been developed to derive the true CME speed, size, position, and mass, among others. Difficulties in determining the input parameters for CME forecasting models arise from the lack of direct measurements of the coronal magnetic fields and uncertainties in estimating the CME 3D geometric and kinematic parameters after eruption. White-light coronagraph images are usually employed by a variety of CME reconstruction techniques that assume more or less complex geometries. This is the first study from our International Space Science Institute (ISSI) team “Understanding Our Capabilities in Observing and Modeling Coronal Mass Ejections”, in which we explore how subjectivity affects the 3D CME parameters that are obtained from the Graduated Cylindrical Shell (GCS) reconstruction technique, which is widely used in CME research. To be able to quantify such uncertainties, the “true” values that are being fitted should be known, which are impossible to derive from observational data. We have designed two different synthetic scenarios where the “true” geometric parameters are known in order to quantify such uncertainties for the first time. We explore this by using two sets of synthetic data: 1) Using the ray-tracing option from the GCS model software itself, and 2) Using 3D magnetohydrodynamic (MHD) simulation data from the Magnetohydrodynamic Algorithm outside a Sphere code. Our experiment includes different viewing configurations using single and multiple viewpoints. CME reconstructions using a single viewpoint had the largest errors and error ranges overall for both synthetic GCS and simulated MHD white-light data. As the number of viewpoints increased from one to two, the errors decreased by approximately 4° in latitude, 22° in longitude, 14° in tilt, and 10° in half-angle. Our results quantitatively show the critical need for at least two viewpoints to be able to reduce the uncertainty in deriving CME parameters. We did not find a significant decrease in errors when going from two to three viewpoints for our specific hypothetical three spacecraft scenario using synthetic GCS white-light data. As we expected, considering all configurations and numbers of viewpoints, the mean absolute errors in the measured CME parameters are generally significantly higher in the case of the simulated MHD white-light data compared to those from the synthetic white-light images generated by the GCS model. We found the following CME parameter error bars as a starting point for quantifying the minimum error in CME parameters from white-light reconstructions: Δθ (latitude)=6° +2° -3° , Δϕ (longitude)=11° +18° -6° , Δγ (tilt)=25° +8° -7° , Δx (half-angle)=10° +12° -6° , Δh (height)=0.6 +1.2 -0.4 R ⨀ , and Δκ (ratio)=0.1 +0.03 -0.02 .

Coronal mass ejections↗

Quantifying Errors in 3D CME Parameters Derived From Synthetic Data Using White-Light Reconstruction Techniques

Current efforts in space weather forecasting of CMEs have been focused on predicting their arrival time and magnetic structure. To make these predictions, methods have been developed to derive the true CME speed, size, position, and mass, among others. Difficulties in determining the input parameters for CME forecasting models arise from the lack of direct measurements of the coronal magnetic fields and uncertainties in estimating the CME 3D geometric and kinematic parameters after eruption. White-light coronagraph images are usually employed by a variety of CME reconstruction techniques that assume more or less complex geometries. This is the first study from our International Space Science Institute (ISSI) team “Understanding Our Capabilities in Observing and Modeling Coronal Mass Ejections”, in which we explore how subjectivity affects the 3D CME parameters that are obtained from the Graduated Cylindrical Shell (GCS) reconstruction technique, which is widely used in CME research. To be able to quantify such uncertainties, the “true” values that are being fitted should be known, which are impossible to derive from observational data. We have designed two different synthetic scenarios where the “true” geometric parameters are known in order to quantify such uncertainties for the first time. We explore this by using two sets of synthetic data: 1) Using the ray-tracing option from the GCS model software itself, and 2) Using 3D magnetohydrodynamic (MHD) simulation data from the Magnetohydrodynamic Algorithm outside a Sphere code. Our experiment includes different viewing configurations using single and multiple viewpoints. CME reconstructions using a single viewpoint had the largest errors and error ranges overall for both synthetic GCS and simulated MHD white-light data. As the number of viewpoints increased from one to two, the errors decreased by approximately 4° in latitude, 22° in longitude, 14° in tilt, and 10° in half-angle. Our results quantitatively show the critical need for at least two viewpoints to be able to reduce the uncertainty in deriving CME parameters. We did not find a significant decrease in errors when going from two to three viewpoints for our specific hypothetical three spacecraft scenario using synthetic GCS white-light data. As we expected, considering all configurations and numbers of viewpoints, the mean absolute errors in the measured CME parameters are generally significantly higher in the case of the simulated MHD white-light data compared to those from the synthetic white-light images generated by the GCS model. We found the following CME parameter error bars as a starting point for quantifying the minimum error in CME parameters from white-light reconstructions: Δθ (latitude)=6° +2° -3° , Δϕ (longitude)=11° +18° -6° , Δγ (tilt)=25° +8° -7° , Δx (half-angle)=10° +12° -6° , Δh (height)=0.6 +1.2 -0.4 R ⨀ , and Δκ (ratio)=0.1 +0.03 -0.02 .

Coronal mass ejections↗