A statistical study of normal load factor just prior to ground contact for five light airplanes
Statistical analysis of normal load factor just prior to touchdown for light aircraft
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Statistical analysis of normal load factor just prior to touchdown for light aircraft
A new method for measurement of elemental analysis by nuclear magnetic resonance (NMR) of unknown samples is discussed in this report as a quick and robust means to measure elemental ratios without the use of internal or external calibration standards. The determination of elemental ratios was done by normalizing the signal intensities by the frequency dependent quality factor (Q) and the gyromagnetic ratios (γ) for each measured nucleus. The correction for the frequency dependence was found by characterizing the output signal of the probe as a function of the quality factor (Q) and the frequency, and the correction for γ was discussed in a previous study. A Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence was used for evaluation of the relative signal intensities, which allows for derivation of elemental ratios, and was correspondingly used to simultaneously measure the T 2 * of samples for an added parameter for more accurate identification of unknown samples.
The generalized singular value decomposition (GSVD) is a valuable tool that has many applications in computational science. However, computing the GSVD for large-scale problems is challenging. Motivated by applications in hyper-differential sensitivity analysis (HDSA), in this work we propose new randomized algorithms for computing the GSVD which use randomized subspace iteration and weighted QR factorization. Detailed error analysis is given which provides insight into the accuracy of the algorithms and the choice of the algorithmic parameters. We demonstrate the performance of our algorithms on test matrices and a large-scale model problem where HDSA is used to study subsurface flow.
An analysis of the factors affecting the cost effectiveness of space shuttle operations is presented. The subjects discussed are: (1)payload data bank, (2) program risk analysis, (3)navigation satellite program, and (4) reusable launch systems.
Increasing development of wind and solar generation in the power sector can create economic opportunities for the deployment of water electrolyzers that produce hydrogen. Temporal variation in the marginal cost of energy in future decarbonized grids can make it favorable for electrolyzers to dispatchably ramp hydrogen production up and down in response to low- and high-cost times. Using this strategy, low-cost hydrogen production is enabled by electrolyzers that are low-capital cost and tolerant to frequent on/off cycling. Ramping down hydrogen production to a designated turndown ratio can avoid performance degradation caused by on/off cycling by not shutting the electrolyzer completely off. This comes with a slight cost penalty which can be minimized if the turndown ratio is low (i.e., the system ramps down hydrogen production to close to zero). These results suggest that electrolyzers integrated into future power systems are likely to benefit from the ability to ramp operation up and down quickly and operate in a standby mode. This analysis forms a basis for comparative tradeoffs between electrolyzer capital cost, operating strategy, and system durability and demonstrates the importance of considering all three factors in technoeconomic analysis.
The phenomenon of high velocity, crash landing of spacecraft on the surface of a planet is analyzed as a potential mechanism for the release of encapsulated microbial burden. One of the key factors in this analysis is the extent of fracturing of the spacecraft material. From theoretical considerations it is postulated that the degree of fracturing depends upon such factors as the impact velocity experienced, the physical properties of the surface and of the spacecraft material, the angle of incidence with the surface, and the prevailing atmospheric conditions. Of these, the impact velocity is generally felt to be the dominant factor in the determination of the extent of fracturing.
Modem long-haul aircraft can fly up to 16 continuous hours and provide a 24-hour, global capability. Extra (augmented) flight crew are available on long flights to allow planned rest periods, on a rotating basis, away from the flight deck in onboard crew rest facilities (2 bunks). A NASA/FAA study is under-way to examine the quantity and quality of sleep obtained in long-haul aircraft bunks and the factors that promote or interfere with that sleep. The first phase of the study involved a retrospective survey, followed by a second phase field study to collect standard polysomnographic data during inflight bunk sleep periods. A summary of the Phase I survey results are reported here. A multi-part 54-question retrospective survey was completed by 1,404 flight crew (37% return rate) at three different major US air carriers flying B747-100, 200, 400, and MD- 11 long-haul aircraft. The questions examined demographics, quantity and quality of sleep at home and in onboard bunks, factors that promote or interfere with sleep, and effects on subsequent performance and alertness. Flight crew reported a mean bunk sleep latency of 39.4 mins (SD=28.3 mins) (n=1,276) and a mean total sleep time of 2.2 hrs (SD=1.3 hrs) (n=603). (Different flight lengths could affect overall time available for sleep.) Crew rated 25 factors for their interference or promotion of bunk sleep. Figure I portrays the average ratings for each factor across all three carriers. A principal components analysis of the 25 factors revealed three areas that promoted bunk sleep: physiological (e.g., readiness for sleep), physical environment (e.g., bunk size, privacy), and personal comfort (e.g., blankets, pillows). Five areas were identified that interfered with sleep: environmental disturbance (e.g., background noise, turbulence), luminosity (e.g., lighting), personal disturbances (e.g., bathroom trips, random thoughts), environmental discomfort (e.g., low humidity, cold), and interpersonal disturbances (e.g., bunk partner).
Utilizing historical data from the U.S. nuclear test program and freely available barometric pressure data, we performed an analytical barometric-pumping efficiency analysis to determine factors resulting in late-time radionuclide gas seeps from underground nuclear explosions. In this work, we considered 16 underground nuclear explosions with similar geology and test setup, of which five resulted in the measurement of late-time radionuclide gas concentrations at the ground surface. Additionally, the factors we considered include barometric frequency and amplitude, depth of burial, air-filled porosity, intact-rock permeability, fracture aperture, and fracture spacing. The analysis indicates that the best discriminators of late-time radionuclide gas seeps for these explosions are barometric frequency and amplitude and air-filled porosity. While geologic information on fracture aperture and spacing is not available for these explosions, the sensitivity of barometric-pumping efficiency to fracture aperture indicates that it would likely also be a good discriminator.
Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. In this paper, how we have developed one of the HUNTER modules, the individual module for evaluating performance shaping factors (PSFs), is introduced. The PSF refers to any factor that influences human performance such as workload or complexity. It has been used for highlighting human errors and adjusting the error probabilities in the existing HRA. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, which is the representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also design the individual module composed of the two functions: 1) the PSF qualification function that automatically or manually evaluates a PSF level, and 2) the PSF quantification function that dynamically or statically determines the PSF multiplier values and integrate them to adjust human error probabilities (HEPs). How each function works with the SPAR-H PSFs and how the PSFs adjust the HEPs are investigated through literature and discussed in this paper.
The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. This paper explores how we developed one of the HUNTER modules: namely, the Individual module for evaluating performance shaping factors (PSFs). A PSF is any factor that influences human performance (e.g., workload or complexity). In the existing HRA, they are used to highlight human errors and adjust error probabilities. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, a representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed the human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also designed the Individual module to consist of two functions: (1) the PSF qualification function for automatically or manually evaluating PSF levels, and (2) the PSF quantification function for dynamically or statically determining PSF multiplier values and integrating them to adjust human error probabilities (HEPs). How each function works in regard to the SPAR-H PSFs, and how the PSFs serve to adjust the HEPs, were investigated via literature review and are discussed in this paper.
Techniques have been developed for the extraction and characterization of absorption features from visible and infrared reflectance spectra and an expert system has been designed, implemented, and successfully tested that allows automated identification of minerals based on their spectral characteristics. A suite of laboratory spectra of common minerals was analyzed and the absorption band characteristics tabulated and used to develop a generalized knowledge base for analysis of the reflectance spectra. A tree hierarchy was designed to emulate the decision process followed by an experienced analyst for analysis of laboratory and field reflectance spectra and aircraft imaging spectrometer spectra. Good results were obtained with the expert system for all three types of spectra, with the critical factor in the analysis being the signal-to-noise ratio of the spectral data.
The purpose is to provide and overview of human factors issues that impact the effectiveness of user interfaces to automated scheduling tools. The following methods are employed: (1) a survey of planning and scheduling tools; (2) the identification and analysis of human factors issues; (3) the development of design guidelines based on human factors literature; and (4) the generation of display concepts to illustrate guidelines.
Volume 5 is Appendix C, Auxiliary Shuttle Risk Analyses, and contains the following reports: Probabilistic Risk Assessment of Space Shuttle Phase 1 - Space Shuttle Catastrophic Failure Frequency Final Report; Risk Analysis Applied to the Space Shuttle Main Engine - Demonstration Project for the Main Combustion Chamber Risk Assessment; An Investigation of the Risk Implications of Space Shuttle Solid Rocket Booster Chamber Pressure Excursions; Safety of the Thermal Protection System of the Space Shuttle Orbiter - Quantitative Analysis and Organizational Factors; Space Shuttle Main Propulsion Pressurization System Probabilistic Risk Assessment, Final Report; and Space Shuttle Probabilistic Risk Assessment Proof-of-Concept Study - Auxiliary Power Unit and Hydraulic Power Unit Analysis Report.
Drought is a water deficit state caused by large-scale climate change that cannot be avoided by a water resource management system. Water scarcity refers to the unsustainable utilization of water resources over a long time, which is the result of water management policies. However, water deficits caused by drought and water scarcity often occur simultaneously and are indistinguishable. This study proposes a model-based simulation framework that can quantitatively distinguish natural factors (drought) from human factors (water scarcity) in a hydrological system. The simulation was applied to the Zhangweinan Canal Basin, based on the runoff sequences from 1950 to 2004. The results show that the runoff curve number, soil depth, soil available water, soil evaporation compensation coefficient, base runoff α coefficient and the maximum canopy interception have the highest sensitivity to runoff, and that the calibrated and validated SWAT model can effectively simulate the runoff process in the Zhangweinan Canal Basin and similar areas. Abrupt changes in human activities in 1975 and water scarcity led to the disappearance of the summer peak runoff period in both wet and dry years. Human factors are the main reason for the change in the hydrological system in the study area; the runoff loss caused by human factors is four times that caused by natural factors according to the proposed variable threshold. This study proposes a model-based simulation framework that can help water resource managers to distinguish the effects of drought and water scarcity in water-stressed areas and adjust management accordingly.
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 oxidizing capacity of the troposphere is controlled, to a large extent, by the abundance of hydroxyl radical (OH). The global mean concentration of OH, [OH]GLOBAL, inferred from measurements of methyl chloroform, has remained relatively constant during the past several decades, despite rising levels of CH4 that should have led to a steady decline. Here we examine other factors that may have affected [OH]GLOBAL, such as the overhead burden of stratospheric O3 and tropospheric H2O, using global OH fields from the GEOS-CHEM Chemistry-Climate Model. Our analysis suggests these factors may have contributed a positive trend to [OH]GLOBAL large enough to counter the decrease due to CH4.
The objective of this analysis is to process Lincoln Laboratory Doppler radar data obtained during FLOWS testing at Huntsville, Alabama, in the summer of 1986, to characterize windshear events. The processing includes plotting velocity and F-factor profiles, histogram analysis to summarize statistics, and correlation analysis to demonstrate any correlation between different data fields.
The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation; the failure to increase capacity at the same rate as the growth in demand results in unreliable service and systemic delay. This report describes the results of an analysis of airline strategic decision-making that affects geographic access, economic access, and airline finances, extending the analysis of these factors using historic data (from Part 1 of the report). The Airline Schedule Optimization Model (ASOM) was used to evaluate how exogenous factors (passenger demand, airline operating costs, and airport capacity limits) affect geographic access (markets-served, scheduled flights, aircraft size), economic access (airfares), airline finances (profit), and air transportation efficiency (aircraft size). This analysis captures the impact of the implementation of airport capacity limits, as well as the effect of increased hedged fuel prices, which serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed; also incorporated are demand elasticity curves based on historical data that provide information about how passenger demand is affected by airfare changes.