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At least 217 records · Page 12

Continued Discussion of Failure Mode Modeling and Overall Component Reliability: Are the Data Missing or Censored?

This paper is the continuation of a paper presented at the 13th Probabilistic Safety Assessment and Management Conference, in which a methodology of modeling failure modes of complex components was presented; see Paulos and Smith (2016). This methodology is not particularly helpful in the space industry where there is a lack of failure data, but is more helpful in industries that see a lot of component repairs and improvements, such as in the aircraft or automotive industries. The previous paper demonstrated how the typical approach of treating failure modes as being exponential in nature may yield optimistic predictions when estimating how improvements to components will perform in the future. It is more accurate to model the failure modes as a race in time; unfortunately, this does not give a closed-form solution. This paper uses simulation to solve for the model of the world, and the results compared to the standard methodology of treating the failure modes as being exponential random failures. The standard method is shown to have optimistic predictions, which will lead to prediction errors when failure modes are removed or “fixed.” The failure mode methodology presented in the first paper treated the data as being censored when the test stopped. In this paper, we will compare the results from treating the data as both censored and missing.

Smith, Curtis↗

Comparison of Prediction Modeling Methodologies for Aeroacoustic Characterization of Hovering sUAS Rotors

This work compared artificial neural network and multivariate orthogonal function modeling methodologies for the prediction and characterization of isolated hovering sUAS rotor aerodynamics and aeroacoustics. Design of Experiments was used to create input feature spaces over 9 input features: the number of rotor blades, rotor size, rotor speed, the amount of blade twist, blade taper ratio, tip chord length, collective pitch, airfoil camber, and airfoil thickness. CAMRAD~II and AARON were executed at the points defined by the input feature space to predict aerodynamic and aeroacoustic quantities. These predicted aerodynamic and aeroacoustic data were then used to generate artificial neural networks and polynomial response surface models. The two prediction model methodologies were evaluated over test data previously unseen by the models, which showed good prediction capabilities for both model types, with slightly lower prediction error for the artificial neural networks. A characterization study was performed, which showed that input features correspondent to the spanwise sectional blade lift and drag were the most significant factors to the aerodynamic thrust and power, respectively. It was also shown that the aeroacoustic quantities were highly dependent on variations in rotor speed and size, which affect the Doppler factor for tonal noise and the spanwise Reynolds number for broadband noise.

Christopher S Thurman↗

Copula-based Method to Generate Consistent Surface Pressures Under Uncertainty

This paper establishes a method to create surface pressure databases that allow for uncertainty quantification. Aerodynamic databases are critical products for launch vehicles and other aeronautical systems, and surface pressure databases are one such database that constains large quantities of data. The focus of this work is the relationship between the integrated force and moment data base and the surface pressure database. In particular, the work attempts to provide a method that maintains consistency between these two databases when accounting for uncertainty. The integrated force and moment database and surface pressure databases are constructed from CFD data which is high-density but low-trust. However, the force and moment database will often also include data from high-trust but low-density sources such as from wind tunnel experiments. This means that the quantified uncertainty of the force and moment database is higher quality as it includes this high fidelity wind tunnel data. This motivates the idea to use the force and moment database uncertainty when constructing the surface pressure database uncertainty. The method utilizes the statistical idea of a copula in order to generate surface pressures that match with uncertain integrated force and moment distributions as well as being consistent with known CFD data. This statistical consistency is quantified by using the Maximum Mean Discrepancy two-sample test. The predictive error of the method is also approximated using leave-one-out error estimation and the good overall performance of the method is presented using probability boxes in a simulated uncertainty scenario.

SLS↗

Long Term Mean Local Time of the Ascending Node Prediction

Significant error has been observed in the long term prediction of the Mean Local Time of the Ascending Node on the Aqua spacecraft. This error of approximately 90 seconds over a two year prediction is a complication in planning and timing of maneuvers for all members of the Earth Observing System Afternoon Constellation, which use Aqua's MLTAN as the reference for their inclination maneuvers. It was determined that the source of the prediction error was the lack of a solid Earth tide model in the operational force models. The Love Model of the solid Earth tide potential was used to derive analytic corrections to the inclination and right ascension of the ascending node of Aqua's Sun-synchronous orbit. Additionally, it was determined that the resonance between the Sun and orbit plane of the Sun-synchronous orbit is the primary driver of this error. The analytic corrections have been added to the operational force models for the Aqua spacecraft reducing the two-year 90-second error to less than 7 seconds.

McKinley, David P.↗

Dynamical predictability in a simple general circulation model - Average error growth

Average predictability and error growth in a simple realistic two-level general circulation model (GCM) were investigated using a series of Monte Carlo experiments for fixed external forcing (perpetual winter in the Northern Hemisphere). It was found that, for realistic initial errors, the dependence of the limit of dynamic predictability on total wavenumber was similar to that found for the ECMWF model for the 1980/1981 winter conditions, with the lowest wavenumbers showing significant skill for forecast ranges of more than 1 month. On the other hand, for very small amplitude errors distributed according to the climate spectrum, the total error growth was superexponential, reaching a maximum growth rate (2-day doubling time) in about 1 week. A simple empirical model of error variance, which involved two broad wavenumber bands and incorporating a 3/2 power saturation term, was found to provide an excellent fit to the GCM error growth behavior.

Schubert, Siegfried D.↗

Trajectory Prediction Accuracy and Error Sources for Regional Jet Descents: Results of a 2010 Flight Trial at Denver International Airport using SkyWest Revenue Flights - Part II

The Efficient Descent Advisor (EDA) controller automation tool generates trajectory-based speed, path, and altitude-profile advisories to facilitate efficient, continuous descents into congested terminal airspace. While prior field trials have assessed the trajectory prediction accuracy for large jet (i.e., Boeing and Airbus) types, smaller (i.e., regional and business) jet types present unique challenges involving different descent procedures and Flight Management System (FMS) capabilities. This paper quantifies the trajectory prediction accuracy for small jet revenue flight descents based on SkyWest Canadair Regional Jet 200, 700, and 900 aircraft arrivals to Denver in the fall of 2010. Post flight test data analysis and SkyWest pilot interviews uncovered unexpected variation between flight crews due to different interpretations of (1) which fixed flight path angle (FPA) to fly based on the flight trial procedure and (2) how to fly the descent to achieve the target FPA. Pilot reports were used to select a subset of flights where pilots indicated an FPA according to the flight trial procedure to remove the unexpected variation due to (1) to focus on (2). Results for the subset for en-route descents, from prior to top of descent to the meter fix 30 to 130 nmi downstream, indicate that aircraft arrived to the meter fix six seconds early with about a twelve second standard deviation. Large FPA errors up to one degree relative to the EDA flight trial procedure were detected after the flight trial as a characteristic of the unexpected variation. It is recommended that quantitative validation be performed during future flight trials so that experimental procedures can be adjusted if unexpected results are detected.

Field Test Results↗

Effects of modeling errors on trajectory predictions in air traffic control automation

Air traffic control automation synthesizes aircraft trajectories for the generation of advisories. Trajectory computation employs models of aircraft performances and weather conditions. In contrast, actual trajectories are flown in real aircraft under actual conditions. Since synthetic trajectories are used in landing scheduling and conflict probing, it is very important to understand the differences between computed trajectories and actual trajectories. This paper examines the effects of aircraft modeling errors on the accuracy of trajectory predictions in air traffic control automation. Three-dimensional point-mass aircraft equations of motion are assumed to be able to generate actual aircraft flight paths. Modeling errors are described as uncertain parameters or uncertain input functions. Pilot or autopilot feedback actions are expressed as equality constraints to satisfy control objectives. A typical trajectory is defined by a series of flight segments with different control objectives for each flight segment and conditions that define segment transitions. A constrained linearization approach is used to analyze trajectory differences caused by various modeling errors by developing a linear time varying system that describes the trajectory errors, with expressions to transfer the trajectory errors across moving segment transitions. A numerical example is presented for a complete commercial aircraft descent trajectory consisting of several flight segments.

Jackson, Michael R. C.↗

Formulation of a General Technique for Predicting Pneumatic Attenuation Errors in Airborne Pressure Sensing Devices

Presented is a mathematical model derived from the Navier-Stokes equations of momentum and continuity, which may be accurately used to predict the behavior of conventionally mounted pneumatic sensing systems subject to arbitrary pressure inputs. Numerical techniques for solving the general model are developed. Both step and frequency response lab tests were performed. These data are compared with solutions of the mathematical model and show excellent agreement. The procedures used to obtain the lab data are described. In-flight step and frequency response data were obtained. Comparisons with numerical solutions of the math model show good agreement. Procedures used to obtain the flight data are described. Difficulties encountered with obtaining the flight data are discussed.

Whitmore, Stephen A.↗

Formulaton of a general technique for predicting pneumatic attenuation errors in airborne pressure sensing devices

Presented is a mathematical model, derived from the Navier-Stokes equations of momentum and continuity, which may be accurately used to predict the behavior of conventionally mounted pneumatic sensing systems subject to arbitrary pressure inputs. Numerical techniques for solving the general model are developed. Both step and frequency response lab tests were performed. These data are compared against solutions of the mathematical model. The comparisons show excellent agreement. The procedures used to obtain the lab data are described. In-flight step and frequency response data were obtained. Comparisons with numerical solutions of the mathematical model show good agreement. Procedures used to obtain the flight data are described. Difficulties encountered with obtaining the flight data are discussed.

Whitmore, Stephen A.↗

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

Hemsch, Michael J.↗

Effect of accuracy of wind power prediction on power system operator

This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

Schlueter, R. A.↗

A model for the prediction of latent errors using data obtained during the development process

A model implemented in a program that runs on the IBM PC for estimating the latent (or post ship) content of a body of software upon its initial release to the user is presented. The model employs the count of errors discovered at one or more of the error discovery processes during development, such as a design inspection, as the input data for a process which provides estimates of the total life-time (injected) error content and of the latent (or post ship) error content--the errors remaining a delivery. The model presented presumes that these activities cover all of the opportunities during the software development process for error discovery (and removal).

Gaffney, J. E., Jr.↗

NASA Lewis Stirling engine computer code evaluation

In support of the U.S. Department of Energy's Stirling Engine Highway Vehicle Systems program, the NASA Lewis Stirling engine performance code was evaluated by comparing code predictions without engine-specific calibration factors to GPU-3, P-40, and RE-1000 Stirling engine test data. The error in predicting power output was -11 percent for the P-40 and 12 percent for the Re-1000 at design conditions and 16 percent for the GPU-3 at near-design conditions (2000 rpm engine speed versus 3000 rpm at design). The efficiency and heat input predictions showed better agreement with engine test data than did the power predictions. Concerning all data points, the error in predicting the GPU-3 brake power was significantly larger than for the other engines and was mainly a result of inaccuracy in predicting the pressure phase angle. Analysis into this pressure phase angle prediction error suggested that improvements to the cylinder hysteresis loss model could have a significant effect on overall Stirling engine performance predictions.

Sullivan, Timothy J.↗

Closing the Seasonal Ocean Surface Temperature Balance in the Eastern Tropical Oceans from Remote Sensing and Model Reanalyses

Residual forcing necessary to close the MLTB on seasonal time scales are largest in regions of strongest surface heat flux forcing. Identifying the dominant source of error - surface heat flux error, mixed layer depth estimation, ocean dynamical forcing - remains a challenge in the eastern tropical oceans where ocean processes are very active. Improved sub-surface observations are necessary to better constrain errors. 1. Mixed layer depth evolution is critical to the seasonal evolution of mixed layer temperatures. It determines the inertia of the mixed layer, and scales the sensitivity of the MLTB to errors in surface heat flux and ocean dynamical forcing. This role produces timing impacts for errors in SST prediction. 2. Errors in the MLTB are larger than the historical 10Wm-2 target accuracy. In some regions, a larger accuracy can be tolerated if the goal is to resolve the seasonal SST cycle.

Roberts, J. Brent↗

CPO Prediction: Accuracy Assessment and Impact on UT1 Intensive Results

The UT1 Intensive results heavily depend on the celestial pole offset (CPO) model used during data processing. Since accurate CPO values are available with a delay of two to four weeks, CPO predictions are necessarily applied to the UT1 Intensive data analysis, and errors in the predictions can influence the operational UT1 accuracy. In this paper we assess the real accuracy of CPO prediction using the actual IERS and PUL predictions made in 2007-2009. Also, results of operational processing were analyzed to investigate the actual impact of EOP prediction errors on the rapid UT1 results. It was found that the impact of CPO prediction errors is at a level of several microseconds, whereas the impact of the inaccuracy in the polar motion prediction may be about one order of magnitude larger for ultra-rapid UT1 results. The situation can be amended if the IERS Rapid solution will be updated more frequently.

Malkin, Zinovy↗

Small error dynamics and the predictability of atmospheric flows

In this paper, linear small-error theory is applied to the study of weather predictability. A simple baroclinic shear model and a barotropic channel model with a localized jet are used as examples. It is shown that increase in error on synoptic forecast time scales is controlled by rapidly growing perturbations that are not of normal mode form. Unpredictable regimes are not necessarily associated with larger exponential growth rates than are relatively more predictable regimes. Model problems illustrating baroclinic and barotropic dynamics suggest that asymptotic measures of divergence in phase space, while applicable in the limit of infinite time, may not be appropriate over time intervals addressed by present synoptic forecast.

Farrell, Brian F.↗