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Determining the Most Influencing Medical Conditions in MEDPRAT’s SIN Directed Graph

INTRODUCTION: The Susceptibility Inference Network (SIN) is a network of medical conditions, part of the Medical Extensible Probabilistic Risk Assessment Tool (MEDPRAT) developed by NASA to assess human health and medical risk to space exploration missions. The SIN is subject matter expert informed and acts as a prototype that provides relationships and dependencies between events modeled by MEDPRAT. Each vertex in the SIN has a weight which evaluates the severity of having the condition regardless of the progression from or to that condition. In this presentation, we consider two statistics to measure that stand alone risk: Quality Time Lost (QTL) and Loss of Crew Life (LOCL). Our goal is to identify the medical conditions that contribute the most to crew members QTL and LOCL risks due to progression of conditions in the network. We investigate how different computation parameters result in different condition rankings and address the choice of parameters that allows appropriate interventions to ensure space mission success. METHODS: The Katz score, one of many centrality measures created for ranking purposes in network analysis, takes into account all possible walks through the network, penalizing each additional step in a walk by a factor α called the Katz parameter. The literature does not provide specific values for the choice of α. We derive an analytical relationship between α and the maximum path length which has influence on the Katz score and ranking. Based on the probability of progression of each condition in the SIN, we identify that maximum path length of interest and calculate α that is then used in the Katz formula to rank the conditions in the SIN. RESULTS AND CONCLUSION: The effective probabilities of the SIN matrix generally fall below 10−6, which is below the level of the least influencing condition in the set. This corresponds to the probability of at most six consecutive progressions of a condition. Consequently, we calculate the Katz Parameter α and get 0.32. We rank the medical conditions and find that Acute Radiation Symptom is the condition the most prone to contribute to quality time loss due to progression.

risk analysis↗

NASA NTRS2007

Stress Rupture Life Reliability Measures for Composite Overwrapped Pressure Vessels

Composite Overwrapped Pressure Vessels (COPVs) are often used for storing pressurant gases onboard spacecraft. Kevlar (DuPont), glass, carbon and other more recent fibers have all been used as overwraps. Due to the fact that overwraps are subjected to sustained loads for an extended period during a mission, stress rupture failure is a major concern. It is therefore important to ascertain the reliability of these vessels by analysis, since the testing of each flight design cannot be completed on a practical time scale. The present paper examines specifically a Weibull statistics based stress rupture model and considers the various uncertainties associated with the model parameters. The paper also examines several reliability estimate measures that would be of use for the purpose of recertification and for qualifying flight worthiness of these vessels. Specifically, deterministic values for a point estimate, mean estimate and 90/95 percent confidence estimates of the reliability are all examined for a typical flight quality vessel under constant stress. The mean and the 90/95 percent confidence estimates are computed using Monte-Carlo simulation techniques by assuming distribution statistics of model parameters based also on simulation and on the available data, especially the sample sizes represented in the data. The data for the stress rupture model are obtained from the Lawrence Livermore National Laboratories (LLNL) stress rupture testing program, carried out for the past 35 years. Deterministic as well as probabilistic sensitivities are examined.

Murthy, Pappu L. N.↗

NASA NTRS2006

Hard and Soft Constraints in Reliability-Based Design Optimization

This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.

Crespo, L.uis G.↗

NASA NTRS2023

A Confidence-Based Approach to Including Survivors in a Probabilistic TID Failure Assessment

A probabilistic total ionizing dose (TID) failure assessment is extended to include survivor data, enabling the bounding of failure probability to a desired confidence level (CL) without failure data. The extension provides an avenue for analyzing microelectronics tested for TID without reaching a failure mode, a scenario often encountered by missions utilizing commercial-off-the-shelf (COTS) technologies. Using the type-I censored likelihood formulation and a realistic upper bound on expected device performance, the failure probability space is bounded by confidence contours within the context of a variable environment. The framework accommodates any type of distribution assumed for the part failure or the environment under consideration. Furthermore, the framework can be utilized pre-emptively to plan future device TID tests, minimizing costs while meeting survival requirements. Heritage data may also be used as survivors to further minimize testing costs when parts are from the same lot, but the amount of constraint derived from heritage is limited. Altogether, the framework enables a formal, mathematically rigorous analysis of radiation tolerant devices tested to a maximum dose, as well as flight heritage, in a hardness assurance methodology.

confidence↗

NASA NTRS1998

Deterministic and Probabilistic Creep and Creep Rupture Enhancement to CARES/Creep: Multiaxial Creep Life Prediction of Ceramic Structures Using Continuum Damage Mechanics and the Finite Element Method

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep ripture criterion However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of stress, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of this methodology and the CARES/Creep program.

Jadaan, Osama M.↗

NASA NTRS2004

Modelling and Analysis of a Regenerative Fuel Cell Propulsion System for a High Altitude Long Endurance UAV

In the search to bridge current gaps in surveillance and communication technologies, a new type of, aircraft is currently undergoing design. The idea of a High Altitude Long Endurance (HALE) aircraft is already a few decades old, but has only recently become realizable. A relay and collector of information at altitudes of 65,000 feet and higher could greatly improve standards of data exchange, homeland security, and research of the air, land and sea. NASA, as a major force in propulsion research, is exploring methods of powering an autonomous aircraft for days, weeks, or even months without refueling. Such a task requires not only high energy density, but also the ability to make use of renewable energy sources to regenerate power. Hydrogen is one of the most energy dense fuels available. Fuel cells make use of hydrogen by harnessing the energy released as it combines with oxygen to produce electricity and water. Fuel cells are envisioned to occupy future propulsion systems in cooperation with solar cells where the photovoltaic arrays harness sunlight into power which can electrolize the water byproduct into reusable hydrogen and oxygen. Modeling this type of system requires adequate assumptions of support hardware and daily transients in operation. The performance of a regenerative fuel cell propulsion system lies in the flight characteristics (altitude, density, temperature, latitude, etc.). Each subsystem is defined by many parameters which can be varied across wide ranges. Statistical and probabilistic analyses bring forward a wealth of information that can be utilized in the design process. This is necessary since the required technologies are relatively young and barely, if yet, capable. Once the modeling is complete, a design space exploration of this highly constrained scenario can be utilized to find the optimal design. The model will become an interactive environment with which experiments and tests can be run. When linked

Simpson, Mike B.↗

NASA NTRS2016

Human Reliability Assessments: Using the Past (Shuttle) to Predict the Future (Orion)

NASA (National Aeronautics and Space Administration) Johnson Space Center (JSC) Safety and Mission Assurance (S&MA) uses two human reliability analysis (HRA) methodologies. The first is a simplified method which is based on how much time is available to complete the action, with consideration included for environmental and personal factors that could influence the human's reliability. This method is expected to provide a conservative value or placeholder as a preliminary estimate. This preliminary estimate or screening value is used to determine which placeholder needs a more detailed assessment. The second methodology is used to develop a more detailed human reliability assessment on the performance of critical human actions. This assessment needs to consider more than the time available, this would include factors such as: the importance of the action, the context, environmental factors, potential human stresses, previous experience, training, physical design interfaces, available procedures/checklists and internal human stresses. The more detailed assessment is expected to be more realistic than that based primarily on time available. When performing an HRA on a system or process that has an operational history, we have information specific to the task based on this history and experience. In the case of a Probabilistic Risk Assessment (PRA) that is based on a new design and has no operational history, providing a "reasonable" assessment of potential crew actions becomes more challenging. In order to determine what is expected of future operational parameters, the experience from individuals who had relevant experience and were familiar with the system and process previously implemented by NASA was used to provide the "best" available data. Personnel from Flight Operations, Flight Directors, Launch Test Directors, Control Room Console Operators and Astronauts were all interviewed to provide a comprehensive picture of previous NASA operations. Verification of the assumptions and expectations expressed in the assessments will be needed when the procedures, flight rules and operational requirements are developed and then finalized.

DeMott, Diana↗

NASA NTRS2017

Human Reliability Assessments: Using the Past (Shuttle) to Predict the Future (Orion)

NASA (National Aeronautics and Space Administration) Johnson Space Center (JSC) Safety and Mission Assurance (S&MA) uses two human reliability analysis (HRA) methodologies. The first is a simplified method which is based on how much time is available to complete the action, with consideration included for environmental and personal factors that could influence the human's reliability. This method is expected to provide a conservative value or placeholder as a preliminary estimate. This preliminary estimate or screening value is used to determine which placeholder needs a more detailed assessment. The second methodology is used to develop a more detailed human reliability assessment on the performance of critical human actions. This assessment needs to consider more than the time available, this would include factors such as: the importance of the action, the context, environmental factors, potential human stresses, previous experience, training, physical design interfaces, available procedures/checklists and internal human stresses. The more detailed assessment is expected to be more realistic than that based primarily on time available. When performing an HRA on a system or process that has an operational history, we have information specific to the task based on this history and experience. In the case of a Probabilistic Risk Assessment (PRA) that is based on a new design and has no operational history, providing a "reasonable" assessment of potential crew actions becomes more challenging. To determine what is expected of future operational parameters, the experience from individuals who had relevant experience and were familiar with the system and process previously implemented by NASA was used to provide the "best" available data. Personnel from Flight Operations, Flight Directors, Launch Test Directors, Control Room Console Operators, and Astronauts were all interviewed to provide a comprehensive picture of previous NASA operations. Verification of the assumptions and expectations expressed in the assessments will be needed when the procedures, flight rules, and operational requirements are developed and then finalized.

DeMott, Diana L.↗

NASA NTRS2015

Probabilistic Risk Assessment for Astronaut Post Flight Bone Fracture

Introduction: Space flight potentially reduces the loading that bone can resist before fracture. This reduction in bone integrity may result from a combination of factors, the most common reported as reduction in astronaut BMD. Although evaluating the condition of bones continues to be a critical aspect of understanding space flight fracture risk, defining the loading regime, whether on earth, in microgravity, or in reduced gravity on a planetary surface, remains a significant component of estimating the fracture risks to astronauts. This presentation summarizes the concepts, development, and application of NASA's Bone Fracture Risk Module (BFxRM) to understanding pre-, post, and in mission astronaut bone fracture risk. The overview includes an assessment of contributing factors utilized in the BFxRM and illustrates how new information, such as biomechanics of space suit design or better understanding of post flight activities may influence astronaut fracture risk. Opportunities for the bone mineral research community to contribute to future model development are also discussed. Methods: To investigate the conditions in which spaceflight induced changes to bone plays a critical role in post-flight fracture probability, we implement a modified version of the NASA Bone Fracture Risk Model (BFxRM). Modifications included incorporation of variations in physiological characteristics, post-flight recovery rate, and variations in lateral fall conditions within the probabilistic simulation parameter space. The modeled fracture probability estimates for different loading scenarios at preflight and at 0 and 365 days post-flight time periods are compared. Results: For simple lateral side falls, mean post-flight fracture probability is elevated over mean preflight fracture probability due to spaceflight induced BMD loss and is not fully recovered at 365 days post-flight. In the case of more energetic falls, such as from elevated heights or with the addition of lateral movement, the contribution of space flight quality changes is much less clear, indicating more granular assessments, such as Finite Element modeling, may be needed to further assess the risks in these scenarios.

Risk Analysis↗

NASA NTRS2014

An Integrated Reliability and Physics-Based Risk Modeling Approach for Assessing Human Spaceflight Systems

This paper presents an integrated reliability and physics-based risk modeling approach for assessing human spaceflight systems. The approach is demonstrated using an example, end-to-end risk assessment of a generic-crewed space transportation system during a reference mission to the International Space Station. The behavior of the system is modeled using analysis techniques from multiple disciplines in order to properly capture the dynamic time- and state- dependent consequences of failures encountered in different mission phases. We discuss how to combine traditional reliability analyses with Monte Carlo simulation methods and physics-based engineering models to produce loss-of- mission and loss-of-crew risk estimates supporting risk-based decision-making and requirement verification. This approach facilitates risk-informed design by providing more realistic representation of system failures and interactions; identifying key risk-driving sensitivities, dependencies, and assumptions; and tracking multiple figures of merit within a single, responsive assessment framework that can readily incorporate evolving design information throughout system development.

Risk assessment↗

NASA NTRS1997

Lessons learned studying design issues for lunar and Mars settlements

In a study of lunar and Mars settlement concepts, an analysis was made of fundamental design assumptions in five technical areas against a model list of occupational and environmental health concerns. The technical areas included the proposed science projects to be supported, habitat and construction issues, closed ecosystem issues, the "MMM" issues (mining, material processing, and manufacturing), and the human elements of physiology, behavior, and mission approach. Four major lessons were learned. First it is possible to relate public health concerns to complex technological development in a proactive design mode, which has the potential for long-term cost savings. Second, it became very apparent that prior to committing any nation or international group to spending the billions to start and complete a lunar settlement, over the next century, that a significantly different approach must be taken from those previously proposed, to solve the closed ecosystem and "MMM" problems. Third, it also appears that the health concerns and technology issues to be addressed for human exploration into space are fundamentally those to be solved for human habitation of the Earth (as a closed ecosystem) in the 21st century. Finally, it is proposed that ecosystem design modeling must develop new tools, based on probabilistic models as a step up from closed circuit models.

Life Support Systems↗

NASA NTRS2005

Gesture Based Control and EMG Decomposition

This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.

Wheeler, Kevin R.↗

NASA NTRS2003

A Study of the Impact of Variations on Aerodynamic Flow in Gas Turbine Engines via Monte-Carlo Simulations

The unsteady compressible inviscid flow is characterized by the conservations of mass, momentum, and energy; or simply the Euler equations. In this paper, a study of the subsonic one-dimensional Euler equations with local preconditioning is presented with a modal analysis approach. Specifically, this study investigates the behavior of airflow in a gas turbine engine using the specified conditions at the inflow and outflow boundaries of the compressor, combustion chamber, and turbine, under the impact of variations in pressure, velocity, temperature, and density at low Mach numbers. Two main questions that motivate this research are: 1) Is there any aerodynamic problem with the existing gas turbine engines that could impact aircraft performance? 2) If yes, what aspect of a gas turbine engine could be improved via design to alleviate that impact and to optimize aircraft performance. This paper presents an initial attempt to the flow behavior in terms (perturbation) using simulation outputs from a customer-deck model obtained from Pratt&Whitney, (i.e., pressure, temperature, velocity, density) about their mean states at the inflow and outflow boundaries of the compressor, combustion chamber, and turbine. Flow behavior is analyzed for the high pressure compressor and combustion chamber employing the conditions on their left and right boundaries. In the same fashion, similar analyses are carried out for the high and low-pressure turbines. In each case, the eigenfrequencies that are obtained for different boundary conditions are examined closely based on their probabilistic distributions, a result of a Monte Carlo 10,000-sample simulation. Furthermore, the characteristic waves and eave response are analyzed and contrasted among different cases, with and without preconditioners. The results reveal the existence of flow instabilities due to the combined effect of variations and excessive pressures; which are clearly the case in the combustion chamber and high-pressure turbine. Finally a discussion is presented on potential impacts of the instabilities and what can be improved via design to alleviate them for a better aircraft performance.

Ngo, Khiem Viet↗

NASA NTRS2017

Medical Optimization Network for Space Telemedicine Resources

INTRODUCTION: Long-duration missions beyond low Earth orbit introduce new constraints to the space medical system such as the inability to evacuate to Earth, communication delays, and limitations in clinical skillsets. NASA recognizes the need to improve capabilities for autonomous care on such missions. As the medical system is developed, it is important to have an ability to evaluate the trade space of what resources will be most important. The Medical Optimization Network for Space Telemedicine Resources was developed for this reason, and is now a system to gauge the relative importance of medical resources in addressing medical conditions. METHODS: A list of medical conditions of potential concern for an exploration mission was referenced from the Integrated Medical Model, a probabilistic model designed to quantify in-flight medical risk. The diagnostic and treatment modalities required to address best and worst-case scenarios of each medical condition, at the terrestrial standard of care, were entered into a database. This list included tangible assets (e.g. medications) and intangible assets (e.g. clinical skills to perform a procedure). A team of physicians working within the Exploration Medical Capability Element of NASA's Human Research Program ranked each of the items listed according to its criticality. Data was then obtained from the IMM for the probability of occurrence of the medical conditions, including a breakdown of best case and worst case, during a Mars reference mission. The probability of occurrence information and criticality for each resource were taken into account during analytics performed using Tableau software. RESULTS: A database and weighting system to evaluate all the diagnostic and treatment modalities was created by combining the probability of condition occurrence data with the criticalities assigned by the physician team. DISCUSSION: Exploration Medical Capabilities research at NASA is focused on providing a medical system to support crew medical needs in the context of a Mars mission. MONSTR is a novel approach to performing a quantitative risk analysis that will assess the relative value of individual resources needed for the diagnosis and treatment of various medical conditions. It will provide the operational and research communities at NASA with information to support informed decisions regarding areas of research investment, future crew training, and medical supplies manifested as part of the exploration medical system.

Shah, R. V.↗

NASA NTRS2000

Intermediate Temperature Stress Rupture of Woven SiC Fiber, BN Interphase, SiC Matrix Composites in Air

Tensile stress-rupture experiments were performed on woven Hi-Nicalon reinforced SiC matrix composites with BN interphases in air. Modal acoustic emission (AE) was used to monitor the damage accumulation in the composites during the tests and microstructural analysis was performed to determine the amount of matrix cracking that occurred for each sample. Fiber fractograph), was also performed for individual fiber failures at the specimen fracture surface to determine the strengths at which fibers failed. The rupture strengths were significantly worse than what would have been expected front the inherent degradation of the fibers themselves when subjected to similar rupture conditions. At higher applied stresses the rate of rupture "?as larger than at lower applied stresses. It was observed that the change in rupture rate corresponded to the onset of through-thickness cracking in the composites themselves. The primary cause of the sen,ere degradation was the ease with which fibers would bond to one another at their closest separation distances, less than 100 nanometers, when exposed to the environment. The near fiber-to-fiber contact in the woven tows enabled premature fiber failure over large areas of matrix cracks due to the stress-concentrations created b), fibers bonded to one another after one or a few fibers fail. i.e. the loss of global load sharing. An@, improvement in fiber-to-fiber separation of this composite system should result in improved stress- rupture properties. A model was den,eloped in order to predict the rupture life-time for these composites based on the probabilistic nature of indin,idual fiber failure at temperature. the matrix cracking state during the rupture test, and the rate of oxidation into a matrix crack. Also incorporated into the model were estimates of the stress-concentration that would occur between the outer rim of fibers in a load-bearing bundle and the unbridged region of a matrix crack after Xia et al. For the lower stresses, this source of stress-concentration was the likely cause for initial fiber failure that would trigger catastrophic failure of the composite.

Morscher, Gregory N.↗

NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗

NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗

NASA NTRS2004

Impact of Variations on 1-D Flow in Gas Turbine Engines via Monte Carlo Simulations

The unsteady compressible inviscid flow is characterized by the conservations of mass, momentum, and energy; or simply the Euler equations. In this paper, a study of the subsonic one-dimensional Euler equations with local preconditioning is presented using a modal analysis approach. Specifically, this study investigates the behavior of airflow in a gas turbine engine using the specified conditions at the inflow and outflow boundaries of the compressor, combustion chamber, and turbine, to determine the impact of variations in pressure, velocity, temperature, and density at low Mach numbers. Two main questions motivate this research: 1) Is there any aerodynamic problem with the existing gas turbine engines that could impact aircraft performance? 2) If yes, what aspect of a gas turbine engine could be improved via design to alleviate that impact and to optimize aircraft performance? This paper presents an initial attempt to model the flow behavior in terms of their eigenfrequencies subject to the assumption of the uncertainty or variation (perturbation). The flow behavior is explored using simulation outputs from a customer-deck model obtained from Pratt & Whitney. Variations of the main variables (i.e., pressure, temperature, velocity, density) about their mean states at the inflow and outflow boundaries of the compressor, combustion chamber, and turbine are modeled. Flow behavior is analyzed for the high-pressure compressor and combustion chamber utilizing the conditions on their left and right boundaries. In the same fashion, similar analyses are carried out for the high-pressure and low-pressure turbines. In each case, the eigenfrequencies that are obtained for different boundary conditions are examined closely based on their probabilistic distributions, a result of a Monte Carlo 10,000 sample simulation. Furthermore, the characteristic waves and wave response are analyzed and contrasted among different cases, with and without preconditioners. The results reveal the existence of flow instabilities due to the combined effect of variations and excessive pressures in the case of the combustion chamber and high-pressure turbine. Finally, a discussion is presented on potential impacts of the instabilities and what can be improved via design to alleviate them for a better aircraft performance.

Ngo, Khiem Viet↗