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A family of upper bounds to error probabilities of coded systems on the additive white Gaussian noise channel was recently proposed by Divsalar.
This paper computes the probabilities that the near-Sun flyby mission, Fire, might be bombarded by high energy protons from solar-activity related proton acceleration lying beneath Fire's perihelion altitude of three solar radii.
Using a fast-flow reactor coupled to a quadrupole mass spectrometer, the heterogeneous reactions of C1ONO2 + HCl and HOCl + HCl as well as hydrolysis of N2O5 and C1ONO2 were investigated on liquid sulfuric acid, with particular emphasis on the effect of incorporation of HNO3 on the reaction probabilities.
We are interested in the problem of finding good codes for the Gaussian channel at low signal-to-noise ratio, and in estimating as accurately as possible their probability of error.
When a photo is detected by a Geiger-mode avalanche photo-diode (GMAPD), the detector is rendered inactive, or blocked, for a certain period of time. In this paper we derive the blocking probability for a GMAPD whose input is either an unmodulated, Benoulli modulated or pulse-position-modulated Poisson process.
Beyond the classic modes of carrier modulation by varying amplitude (AM), phase (PM), or frequency (FM), we extend the modulation domain of an analog carrier signal to include a class of general modulations which are distinguished by their probability density function histogram. Separate waveform states are easily created by varying the pdf of the transmitted waveform. Individual waveform states are assignable as proxies for digital one's or zero's. At the receiver, these states are easily detected by accumulating sampled waveform statistics and performing periodic pattern matching, correlation, or statistical filtering. No fundamental physical laws are broken in the detection process. We show how a typical modulation scheme would work in the digital domain and suggest how to build an analog version. We propose that clever variations of the modulating waveform (and thus the histogram) can provide simple steganographic encoding.
We have undertaken new critical assessments and tabulations of the transition probabilities of important lines of these spectra. For Fe I and Fe II, we have carried out a complete re-assessment and update, and we have relied almost exclusively on the literature of the last 15 years. Our updates for C I, C II and N I, N II primarily address the persistent lower transitions as well as a greatly expanded number of forbidden lines (M1, M2, and E2). For these transitions, sophisticated multiconfiguration Hartree-Fock (MCHF) calculations have been recently carried out, which have yielded data considerably improved and often appreciably different from our 1996 NIST compilation.
Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.
This report describes the work done by the Applied Meteorology Unit (AMU) to update the lightning probability forecast equations developed in Phase I. In the time since the Phase I equations were developed, new ideas regarding certain predictors were formulated and a desire to make the tool more automated was expressed by 45 WS forecasters. Five modifications were made to the data: 1) increased the period of record from 15 to 17 years, 2) modified the valid area to match the lighting warning areas, 3) added the 1000 UTC CCAFS sounding to the other soundings in determining the flow regime, 4) used a different smoothing function for the daily climatology, and 5) determined the optimal relative humidity (RH) layer to use as a predictor. The new equations outperformed the Phase I equations in several tests, and improved the skill of the forecast over the Phase I equations by 8%. A graphical user interface (GUI) was created in the Meteorological Interactive Data Display System (MIDDS) that gathers the predictor values for the equations automatically. The GUI was transitioned to operations in May 2007 for the 2007 warm season.
There are numerous types of differentiated meteorites, but most represent either the crusts or cores of their parent asteroids. Ureilites, olivine-pyroxene-graphite rocks, are exceptions; they are mantle restites [1]. Dunite is expected to be a common mantle lithology in differentiated asteroids. In particular, models of the eucrite parent asteroid contain large volumes of dunite mantle [2-4]. Yet dunites are very rare among meteorites, and none are known associated with the howardite, eucrite, diogenite (HED) suite. Spectroscopic measurements of 4 Vesta, the probable HED parent asteroid, show one region with an olivine signature [5] although the surface is dominated by basaltic and orthopyroxenitic material equated with eucrites and diogenites [6]. One might expect that a small number of dunitic or olivine-rich meteorites might be delivered along with the HED suite. The 46 gram meteoritic dunite MIL 03443 (Fig. 1) was recovered from the Miller Range ice field of Antarctica. This meteorite was tentatively classified as a mesosiderite because large, dunitic clasts are found in this type of meteorite, but it was noted that MIL 03443 could represent a dunite sample of the HED suite [7]. Here I will present a preliminary petrologic study of two thin sections of this meteorite.
This viewgraph presentation reviews some of the problems that are encountered by designers of Non-Destructive Examination (NDE) have in determining the probability of detection. According to the author "[the] NDE community should not blindly accept statistical results due to lack of knowledge." This is an attempt to bridge the gap between people doing NDE, and statisticians.
Collision risk assessment metrics, such as the probability of collision calculation, are based largely on assumptions about the interaction of two objects during their close approach. Specifically, the approach to probabilistic risk assessment can be performed more easily if the relative trajectories of the two close approach objects are assumed to be linear during the encounter. It is shown in this analysis that one factor in determining linearity is the relative velocity of the two encountering bodies, in that the assumption of linearity breaks down at low relative approach velocities. The first part of this analysis is the determination of the relative velocity threshold below which the assumption of linearity becomes invalid. The second part is a statistical study of conjunction interactions between representative asset spacecraft and the associated debris field environment to determine the likelihood of encountering a low relative velocity close approach. This analysis is performed for both the LEO and GEO orbit regimes. Both parts comment on the resulting effects to collision risk assessment operations.
The objective of the task is to investigate the effect of liquid penetrant sensitivity level on probability of crack detection (POD). NASA-STD-5009 currently requires the use of only sensitivity level 4 liquid penetrants. This requirement is based on the fact that the data generated in the NTIAC Nondestructive Evaluation (NDE) Capabilities Data Book was produced using only sensitivity level 4 penetrants. Many NDE contractors supporting NASA Centers routinely use sensitivity level 3 penetrants. Because of the new NASA-STD-5009 requirement, these contractors will have to either shift to sensitivity level 4 penetrants or perform formal POD demonstration tests to qualify their existing process.
The ongoing Mars Science Laboratory (MSL) Propellant Tank Penetrant Nondestructive Evaluation (NDE) Probability of Detection (POD) Assessment (NESC activity) has surfaced several issues associated with liquid penetrant POD demonstration testing. This presentation lists factors that may influence the transferability of POD demonstration tests. Initial testing will address the liquid penetrant inspection technique. Some of the factors to be considered in this task are crack aspect ratio, the extent of the crack opening, the material and the distance between the inspection surface and the inspector's eye.
A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.
Loss of Crew (LOC) and Loss of Mission (LOM) are two key requirements the Constellation Program (CxP) measure against. To date, one of the top risk drivers for both LOC and LOM has been Orion's Crew Exploration Vehicle (CEV) Parachute Assembly System (CPAS). Even though the Orion CPAS is one of the top risk drivers of CxP, it has been very difficult to obtain any relevant data to accurately quantify the risk. At first glance, it would seem that a parachute system would be very reliable given the track record of Apollo and Soyuz. Given the success of those two programs, the amount of data is considered to be statistically insignificant. However, due to CxP having LOC/LOM as key design requirements, it was necessary for Orion to generate a valid prior to begin the Risk Informed Design process. To do so, the Safety & Mission Assurance (S&MA) Space Shuttle & Exploration Analysis Section generated an initial failure probability for Orion to use in preparation for the Orion Systems Requirements Review (SRR).
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the twodimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and threedimensional charting gives a visual confirmation of the relationship between causes and their controls
The AMU created new logistic regression equations in an effort to increase the skill of the Objective Lightning Forecast Tool developed in Phase II (Lambert 2007). One equation was created for each of five sub-seasons based on the daily lightning climatology instead of by month as was done in Phase II. The assumption was that these equations would capture the physical attributes that contribute to thunderstorm formation more so than monthly equations. However, the SS values in Section 5.3.2 showed that the Phase III equations had worse skill than the Phase II equations and, therefore, will not be transitioned into operations. The current Objective Lightning Forecast Tool developed in Phase II will continue to be used operationally in MIDDS. Three warm seasons were added to the Phase II dataset to increase the POR from 17 to 20 years (1989-2008), and data for October were included since the daily climatology showed lightning occurrence extending into that month. None of the three methods tested to determine the start of the subseason in each individual year were able to discern the start dates with consistent accuracy. Therefore, the start dates were determined by the daily climatology shown in Figure 10 and were the same in every year. The procedures used to create the predictors and develop the equations were identical to those in Phase II. The equations were made up of one to three predictors. TI and the flow regime probabilities were the top predictors followed by 1-day persistence, then VT and Ll. Each equation outperformed four other forecast methods by 7-57% using the verification dataset, but the new equations were outperformed by the Phase II equations in every sub-season. The reason for the degradation may be due to the fact that the same sub-season start dates were used in every year. It is likely there was overlap of sub-season days at the beginning and end of each defined sub-season in each individual year, which could very well affect equation performance.