Calibrating Expert Assessments of Advanced Aerospace Technology Adoption Impact

This dissertation describes the development of expert judgment calibration methodology as part of elicitation of the expert judgments to assist in the task of quantifying parameter uncertainty for proposed new aerospace vehicles. From previous work, it has been shown that experts in the field of aerospace systems design and development can provide valuable input into the sizing and conceptual design of future space launch vehicles employing advanced technology. In particular (and of specific interest in this case), assessment of operations and support cost implications of adopting proposed new technology is frequently asked of the experts. Often the input consisting of estimates and opinions is imprecise and may be offered with less than a high degree of confidence in its efficacy. Since the sizing and design of advanced space or launch vehicles must ultimately have costs attached to them (for subsequent program advocacy and tradeoff studies), the lack of precision in parameter estimates will be detrimental to the development of viable cost models to support the advocacy and tradeoffs. It is postulated that a system, which could accurately apply a measure of calibration to the imprecise and/or low-confidence estimates of the surveyed experts, would greatly enhance the derived parametric data. The development of such a calibration aid has been the thrust of this effort. Bayesian network methodology, augmented by uncertainty modeling and aggregation techniques, among others, were employed in the tool construction. Appropriate survey questionnaire instruments were compiled for use in acquiring the experts\u27 input; the responses served as input to a test case for validation of the resulting calibration model. Application of the derived techniques were applied as part of a larger expert assessment elicitation and aggregation study. Results of this research show that calibration of expert judgments, particularly for far-term events, appears to be possible. Suggestions for refinement and extension of the development are presented

(Un)anticipated Technological Change in an Endogenous Growth Model

This paper examines numerically the impact of a negative exogenous shock to marginal productivity (such as ecological government regulation that becomes effective at some point in time) in an endogenous finite-time growth model with sluggish reallocation of human capital. The policy can be anticipated or unanticipated by firms, and it can also be announced but not implemented. It turns out that these frictions have a very strong long-run effect on output, consumption and on the optimal allocation of capital and labor in particular. The qualitative properties relate to homogenous labor models with positive productivity shocks. The problem is thus to maximize a function of a continuous system, where the system is subject to frictions and stepwise changes; for such a problem the application of calculus of variations necessary conditions is problematic. A numerical optimization method, which has had much success on qualitatively similar problems in engineering, has been employed.two-sector endogenous growth model; unanticipated and anticipated technological change; frictions in reallocation of human capital; Runge-Kutta parallel shooting algorithm

An Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated, which can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on hypothetical missions to Mercury, the main asteroid belt, and Pluto

Analysis of General Aviation Instructional Loss of Control Accidents

Although student pilots spend many hours practicing maneuvers to improve airmanship and prevent accidents, almost one half of all general aviation aircraft accidents occur during flight training. Among these, loss of control is the most commonly cited causal factor, and the most common first occurrence in a chain of causal events. This project answers the following question: Can an analysis of National Transportation Safety Board (NTSB) accident reports identify the role of secondary causal factors or reasons involved in general aviation loss of control accidents that involve instructional flights? The analysis focuses on five factors as they each relate to loss of control events: causal factors, phase and location of flight, student and instructor experience, procedural errors, and meteorological conditions. In addition, common occurrences were analyzed to determine trends involved with accident chains of events, and a chi-square test was completed for student and instructor experience as well as accident locations in order to gather insight and support recommendations regarding instructional loss of control accidents in general aviation. The study revealed at least two significant findings: (1) the number of student flight hours accumulated correlates to accident location; and (2) the chain of events in an accident can be an important piece of information in determining causes of an aircraft accident

Application and Analysis of Bounded-Impulse Trajectory Models with Analytic Gradients

In the companion paper, analytic methods were presented for computing the Jacobian entries for two-sided direct shooting trajectory models that utilize the bounded-impulse approximation. In this paper we discuss practical implementation considerations. Efficient computation of the mathematical components required to compute the partials is discussed and a guiding numerical example is provided for validation purposes. A solar electric power model suitable for preliminary mission design is presented, including a method for handling thruster cut-off events that result in non-smooth derivatives. The challenges associated with incorporating the SPICE ephemeris system into an optimization framework are discussed and an alternative is presented that results in smooth time partials. Application problems illustrate the benefits of employing analytic Jacobian calculations vs. using the method of finite differences. The importance of accurately modeling hardware and operational constraints at the preliminary design stage, and the benefits of using an analytic Jacobian in a solver that combines the monotonic basin hopping heuristic method with a local gradient search are also explored

Analytic Gradient Computation for Bounded-Impulse Trajectory Models Using Two-Sided Shooting

Many optimization methods require accurate partial derivative information in order to ensure efficient, robust, and accurate convergence. This work outlines analytic methods for computing the problem Jacobian for two different bounded-impulse spacecraft trajectory models solved using two-sided shooting. The specific two-body Keplerian propagation method used by both of these models is described. Methods for incorporating realistic operational constraints and hardware models at the preliminary stage of a trajectory design effort are also demonstrated and the analytic methods derived are tested for accuracy using automatic differentiation. A companion paper will solve several relevant problems that show the utility of employing analytic derivatives, i.e. compared to using derivatives found using finite differences

Genotyping of Plasmodium falciparum infections by PCR: a comparative multicentre study

Genetic diversity of malaria parasites represents a major issue in understanding several aspects of malaria infection and disease. Genotyping of Plasmodium falciparum infections with polymerase chain reaction (PCR)-based methods has therefore been introduced in epidemiological studies. Polymorphic regions of the msp1, msp2 and glurp genes are the most frequently used markers for genotyping, but methods may differ. A multicentre study was therefore conducted to evaluate the comparability of results from different laboratories when the same samples were analysed. Analyses of laboratory-cloned lines revealed high specificity but varying sensitivity. Detection of low-density clones was hampered in multiclonal infections. Analyses of isolates from Tanzania and Papua New Guinea revealed similar positivity rates with the same allelic types identified. The number of alleles detected per isolate, however, varied systematically between the laboratories especially at high parasite densities. When the analyses were repeated within the laboratories, high agreement was found in getting positive or negative results but with a random variation in the number of alleles detected. The msp2 locus appeared to be the most informative single marker for analyses of multiplicity of infection. Genotyping by PCR is a powerful tool for studies on genetic diversity of P. falciparum but this study has revealed limitations in comparing results on multiplicity of infection derived from different laboratories and emphasizes the need for highly standardized laboratory protocol

Regular breakfast consumption and type 2 diabetes risk markers in 9- to 10-year-old children in the child heart and health study in England (CHASE): a cross-sectional analysis.

BACKGROUND: Regular breakfast consumption may protect against type 2 diabetes risk in adults but little is known about its influence on type 2 diabetes risk markers in children. We investigated the associations between breakfast consumption (frequency and content) and risk markers for type 2 diabetes (particularly insulin resistance and glycaemia) and cardiovascular disease in children. METHODS AND FINDINGS: We conducted a cross-sectional study of 4,116 UK primary school children aged 9-10 years. Participants provided information on breakfast frequency, had measurements of body composition, and gave fasting blood samples for measurements of blood lipids, insulin, glucose, and glycated haemoglobin (HbA1c). A subgroup of 2,004 children also completed a 24-hour dietary recall. Among 4,116 children studied, 3,056 (74%) ate breakfast daily, 450 (11%) most days, 372 (9%) some days, and 238 (6%) not usually. Graded associations between breakfast frequency and risk markers were observed; children who reported not usually having breakfast had higher fasting insulin (percent difference 26.4%, 95% CI 16.6%-37.0%), insulin resistance (percent difference 26.7%, 95% CI 17.0%-37.2%), HbA1c (percent difference 1.2%, 95% CI 0.4%-2.0%), glucose (percent difference 1.0%, 95% CI 0.0%-2.0%), and urate (percent difference 6%, 95% CI 3%-10%) than those who reported having breakfast daily; these differences were little affected by adjustment for adiposity, socioeconomic status, and physical activity levels. When the higher levels of triglyceride, systolic blood pressure, and C-reactive protein for those who usually did not eat breakfast relative to those who ate breakfast daily were adjusted for adiposity, the differences were no longer significant. Children eating a high fibre cereal breakfast had lower insulin resistance than those eating other breakfast types (p for heterogeneity <0.01). Differences in nutrient intakes between breakfast frequency groups did not account for the differences in type 2 diabetes markers. CONCLUSIONS: Children who ate breakfast daily, particularly a high fibre cereal breakfast, had a more favourable type 2 diabetes risk profile. Trials are needed to quantify the protective effect of breakfast on emerging type 2 diabetes risk. Please see later in the article for the Editors' Summary

Developmental Toxicity of Nicotine: A Transdisciplinary Synthesis and Implications for Emerging Tobacco Products

While the health risks associated with adult cigarette smoking have been well described, effects of nicotine exposure during periods of developmental vulnerability are often overlooked. Using MEDLINE and PubMed literature searches, books, reports and expert opinion, a transdisciplinary group of scientists reviewed human and animal research on the health effects of exposure to nicotine during pregnancy and adolescence. A synthesis of this research supports that nicotine contributes critically to adverse effects of gestational tobacco exposure, including reduced pulmonary function, auditory processing defects, impaired infant cardiorespiratory function, and may contribute to cognitive and behavioral deficits in later life. Nicotine exposure during adolescence is associated with deficits in working memory, attention, and auditory processing, as well as increased impulsivity and anxiety. Finally, recent animal studies suggest that nicotine has a priming effect that increases addiction liability for other drugs. The evidence that nicotine adversely affects fetal and adolescent development is sufficient to warrant public health measures to protect pregnant women, children, and adolescents from nicotine exposure