Stochastic modelling of remotely manned systems
Digital simulation models of remotely manned vehicles are discussed and recommendations for statistical validation of all the models are considered.
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Digital simulation models of remotely manned vehicles are discussed and recommendations for statistical validation of all the models are considered.
A new approach to flying qualities specification and evaluation is presented which coordinates current research in the areas of pilot ratings, pilot-aircraft modeling techniques, and simulation and flight test procedures. A time-domain pilot model is described which can model discontinuous and nonlinear pilot behavior in conjunction with completely general time-varying nonlinear aircraft models to simulate discrete maneuvers. This pilot-aircraft model is applied to an existing set of in-flight simulation data, and calculates tracking error and time-on-target statistics for step target tracking that directly relate to the reported pilot comments and ratings. Predicted step target tracking data for eighteen F-5E flight conditions are presented, and the use of the method for control system design is demonstrated using the YF-17.
The small scale wind velocity perturbations in vertical wind profiles at Cape Kennedy, Florida were analyzed in order to derive information for simulations of space shuttle ascent through the perturbed atmosphere. The available statistical data does not permit specification of various aspects of idealized singularities and wavelike perturbations with a reasonable degree of confidence. The information developed as a result of the analysis described in Section 3 of this report is suitable for the further development of idealized models. The term perturbation is used instead of the more common term, gust. According to the conventional approach, a gust profile is calculated by applying a high pass digital filter to a Jimsphere profile; all the speeds in the filtered profile are defined as gusts. The high pass filtered profile is defined as a residual profile and the maximum residual in the vicinity of a specified reference height is defined as the gust. Gusts defined in this manner represent the perturbation peaks. A detailed discussion of the calculation of residual profiles and gusts is given. The meteorological coordinate system, the data sample, and Jimsphere profiles are also described. Recommendations and conclusions are presented.
A method, suggested by Leith (1975), which employed stochastic-dynamic forecasts obtained from a general circulation model in such a way as to satisfy the definition of climatic noise, was used to validate assumptions accounting for the effects of external influences in estimating the climatic noise. Two assumptions were investigated: (1) that the weather fluctuations can be represented as a Markov process, and (2) that changing external conditions do not influence the atmosphere's statistical properties on short time scales. The general circulation model's simulation of the daily weather fluctuations was generated by performing integrations with prescribed climatological boundary conditions for random initial atmospheric states, with resulting dynamical forecasts providing an ensemble of simulated data for the autoregressive modeling of weather fluctuations. To estimate the climatic noise from the observational data (consisting of hourly values of sea level pressure and surface temperature at 54 U.S. stations for the month of January for the years 1949-1975) use of the short time-scale assumption is made. The simulated and observed data were found not to be consistent with either white noise or a Markov process of weather fluctuations. Good agreement was found between the results of the hypothetical testing of the simulated and the observed surface temperatures; and only partial support was found for the short time-scale assumption, i.e., for sea level pressure.
This paper presents a composite model of a moving (3-D) image especially useful for the sequential image processing and encoding. A non-linear predictor based on the composite model is described. The performance of this predictor is used as a measure of the validity of the model for a real image source. The minimization of a total mean square prediction error provides an inequality which determines a condition for the profitable use of the composite model and can serve as a decision device for the selection of the number of subsources within the model. The paper also describes statistical properties of the prediction error and contains results of computer simulation of two non-linear predictors in the case of perfect classification between subsources.
The scope of a critical in-flight event (CIFE) with emphasis on pilot management of available resources is described. Detailed scenarios for both full mission simulation and written testing of pilot responses to CIFE's, and statistical relationships among pilot characteristics and observed responses are developed. A model developed to described pilot response to CIFE and an analysis of professional fight crews compliance with specified operating procedures and the relationships with in-flight errors are included.
The critical elements of an autonomous video rendezvous and docking system were built and used successfully in a physical laboratory simulation. The laboratory system demonstrated that a small, inexpensive electronic package and a flight computer of modest size can analyze television images to derive guidance information for spacecraft. In the ultimate application, the system would use a docking aid consisting of three flashing lights mounted on a passive target spacecraft. Television imagery of the docking aid would be processed aboard an active chase vehicle to derive relative positions and attitudes of the two spacecraft. The demonstration system used scale models of the target spacecraft with working docking aids. A television camera mounted on a 6 degree of freedom (DOF) simulator provided imagery of the target to simulate observations from the chase vehicle. A hardware video processor extracted statistics from the imagery, from which a computer quickly computed position and attitude. Computer software known as a Kalman filter derived velocity information from position measurements.
Statistical method avoids excessive computer time. Technique involves simplified Monte Carlo simulation of system with randomly chosen parameters and comparison of tolerance extremes of several of worst-case situations found. Resulting combination of tolerance extremes then used in detailed analysis - one that makes use of full complex nonlinear model capable of accurate simulations.
A transmitter operating at 869.525 MHz was twice carried by a stratospheric balloon to an altitude of about 40 km. A motor vehicle was driven within the line-of-sight from the transmitter. Measurements of the received signal strength were made every 1/8 wavelength for an overall travelling distance of about seven hundred kilometers. This scenario was to simulate a satellite system providing mobile communications to rural areas. The statistics of the sampled field, consisting of a combination of direct wave, specular reflection and diffuse components, are presented as a function of elevation angle. Parameters such as type of road driven (mostly 2 lane) or type of landscape (rolling to flat) and vegetation (pine and mixed forest) encountered are described where possible. The power distribution function for all the data, at elevation angles from 10 to 35 degrees, is 1 dB below the free space mean at the 50% level, 7 dB below at the 90% level, and 18 dB below at the 99% level. In the elevation angle range of 30 to 35 degrees the corresponding values were found to be .5, 1.2, and 4.5 dB. The conditional fade duration and level crossing rate distribution functions are also presented. The former shows some dependence on the threshold level, the latter almost none.
The purpose of this work is to develop computationally efficient methodologies for assessing the effects of randomness in loads, material properties, and other aspects of a problem by a finite element analysis. The resulting group of methods is called probabilistic finite elements (PFEM). The overall objective of this work is to develop methodologies whereby the lifetime of a component can be predicted, accounting for the variability in the material and geometry of the component, the loads, and other aspects of the environment; and the range of response expected in a particular scenario can be presented to the analyst in addition to the response itself. Emphasis has been placed on methods which are not statistical in character; that is, they do not involve Monte Carlo simulations. The reason for this choice of direction is that Monte Carlo simulations of complex nonlinear response require a tremendous amount of computation. The focus of efforts so far has been on nonlinear structural dynamics. However, in the continuation of this project, emphasis will be shifted to probabilistic fracture mechanics so that the effect of randomness in crack geometry and material properties can be studied interactively with the effect of random load and environment.
The diversity of paleomagnetic records of geomagnetic reversals now available indicate that the field configuration during transitions cannot be adequately described by simple zonal or standing field models. A new model described here is based on statistical properties inferred from the present field and is capable of simulating field transitions like those observed. Some insight is obtained into what one can hope to learn from paleomagnetic records. In particular, it is crucial that the effects of smoothing in the remanence acquisition process be separated from true geomagnetic field behavior. This might enable us to determine the time constants associated with the dominant field configuration during a reversal.
Simulation of atmospheric turbulence as seen by a rotating blade element involves treatment of cyclostationary processes. Conventional filtering techniques do not lend themselves well to the generation of such turbulence sample functions as are required in rotorcraft flight dynamics simulation codes. A method to generate sample functions containing second order statistics of mean and covariance is presented. Compared to ensemble averaging involving excessive computer time, the novelty is to exploit cycloergodicity and thereby, replace ensemble averaging by averaging over a single path sample function of long duration. The method is validated by comparing its covariance results with the analytical and ensemble averaged results for a widely used 1-D turbulence approximation.
A new algorithm is developed for inflight magnetometer bias determination without knowledge of the attitude. This algorithm combines the fast convergence of a heuristic algorithm currently in use with the correct treatment of the statistics and without discarding data. The algorithm performance is examined using simulated data and compared with previous algorithms.
Using 100 years of global temperature anomaly data, we have performed a singluar value decomposition of temperature variations in narrow frequency bands to isolate coherent spatio-temporal modes of global climate variability. Statistical significance is determined from confidence limits obtained by Monte Carlo simulations. Secular variance is dominated by a globally coherent trend; with nearly all grid points warming in phase at varying amplitude. A smaller, but significant, share of the secular variance corresponds to a pattern dominated by warming and subsequent cooling in the high latitude North Atlantic with a roughly centennial timescale. Spatial patterns associated with significant peaks in variance within a broad period range from 2.8 to 5.7 years exhibit characteristic El Nino-Southern Oscillation (ENSO) patterns. A recent transition to a regime of higher ENSO frequency is suggested by our analysis. An interdecadal mode in the 15-to-18 years period and a mode centered at 7-to-8 years period both exhibit predominantly a North Atlantic Oscillation (NAO) temperature pattern. A potentially significant decadal mode centered on 11-to-12 years period also exhibits an NAO temperature pattern and may be modulated by the century-scale North Atlantic variability.
A topic of current practical interest is the accurate characterization of the synoptic-scale atmospheric state from wind profiler and radiosonde network observations. We have examined several related and commonly applied objective analysis techniques for performing this characterization and considered their associated level of uncertainty both from a theoretical and a practical standpoint. A case study is presented where two wind profiler triangles with nearly identical centroids and no common vertices produced strikingly different results during a 43-h period. We conclude that the uncertainty in objectively analyzed quantities can easily be as large as the expected synoptic-scale signal. In order to quantify the statistical precision of the algorithms, we conducted a realistic observing system simulation experiment using output from a mesoscale model. A simple parameterization for estimating the uncertainty in horizontal gradient quantities in terms of known errors in the objectively analyzed wind components and temperature is developed from these results.
Tropical Atlantic SST shows a (statistically well-defined) decadal time scale in a 104-year simulation of unforced variability by a coupled general circulation model (CGCM). The SST anomalies superficially resemble observed Tropical Atlantic variability (TAV), and are associated with changes in the atmospheric circulation. Brazilian rainfall is modulated with a decadal time scale, along with the strength of the Atlantic trade winds, which are associated with variations in evaporation and the net surface heat flux. However, in contrast to observed tropical Atlantic variability, the trade winds damp the associated anomalies in ocean temperature, indicating a negative feedback. Tropical SST anomalies in the CGCM, though opposed by the surface heat flux, are advected in from the Southern Hemisphere mid-latitudes. These variations modulate the strength of the thermohaline circulation (THC): warm, salty anomalies at the equator sink drawing cold, fresh mid-latitude water. Upon reaching the equator, the latter inhibit vertical overturning and advection from higher latitudes, which allows warm, salty anomalies to reform, returning the cycle to its original state. Thus, the cycle results from advection of density anomalies and the effect of these anomalies upon the rate of vertical overturning and surface advection. This decadal modulation of Tropical Atlantic SST and the thermohaline circulation is correlated with ocean heat transport to the Northern Hemisphere high latitudes and Norwegian Sea SST. Because of the central role of equatorial convection, we question whether this mechanism is present in the current climate, although we speculate that it may have operated in palaeo times, depending upon the stability of the tropical water column.
Remote sensing observations, such as those from AURA, are necessary to understand the role of cirrus in determining the radiative and humidity budgets of the upper troposphere. Using these measurements quantitatively requires comparisons with in situ measurements that have previously been validated. However, a direct comparison of remote and in situ measurements is difficult due to the requirement that the spatial and temporal overlap be sufficient in order to guarantee that both instruments are measuring the same air parcel. A difficult as this might be for gas phase intercomparisons, cloud inhomogeneities significantly exacerbate the problem for cloud ice water content measurements. The CRYSTAL-FACE mission provided an opportunity to assess how well such intercomparisons can be performed and to establish flight plans that will be necessary for validation of future satellite instruments. During CRYSTAL-FACE, remote and in situ instruments were placed on different aircraft (NASA's ER-2 and WB-59, and the two planes flew in tandem so that the in situ payload flew in the field of view of the remote instruments. We show here that, even with this type of careful flight planning, it is not always possible to guarantee that remote and in situ instruments are viewing the same air parcel. We use ice water data derived from the in situ Harvard Total Water (HV-TW) instrument, and the remote Goddard Cloud Radar System (CRS) and show that agreement between HV-TW and CRS is a strong function of the horizontal separation and the time delay between the aircraft transects. We also use a cloud model to simulate possible trajectories through a cloud and evaluate the use of statistical analysis in determining the agreement between the two instruments. This type of analysis should guide flight planning for future intercomparison efforts, whether for aircraft or satellite-borne instrumentation.
Chemical and cellular parameters were measured in human subjects before and after exposure to a decompression schedule involving 8 h of oxygen prebreathing. The exposure was designed to simulate space-flight extravehicular activity (EVA) for 6 h. Several statistically significant changes in blood parameters were observed following the exposure: increases in calcium, magnesium, osmolality, low-density lipoprotein cholesterol, monocytes, and prothrombin time, and decreases in chloride, creatine phosphokinase and eosinophils. The changes, however, were small in magnitude and blood factor levels remained within normal clinical ranges. Thus, the decompression profile used in this study is not likely to result in blood changes that would pose a threat to astronauts during EVA.