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At least 271 records · Page 15

Model Calibration for Cancer Risk Projections According to Uncertain Data

This paper presents forward and inverse formulations for the calibration of computational models according to uncertain data. Uncertainty in the data might be caused by a poor metrology system, measurement noise, missing or uncontrollable input variables, or by the inability to directly measure the inputs and/or outputs of interest. The forward approach performs the calibration in the space of the model’s output thereby requiring repeated model simulations. Conversely, the inverse approach leverages an ensemble of solutions to an inverse problem in order to perform the calibration in the space of the model’s parameters. As such, the computational demands of the inverse approach are considerably lower. These strategies are applied to the calibration of a radiation model that in-forms cancer risk projections for future deep space missions.

uncertainty quantification↗

Wind Tunnel Tests on Autorotation and the "Flat Spin."

This report deals with the autorotational characteristics of certain differing wing systems as determined from wind tunnel tests made at the Langley Memorial Aeronautical Laboratory. The investigation was confined to autorotation about a fixed axis in the plane of symmetry and parallel to the wind direction. Analysis of the tests leads to the following conclusions: autorotation below 30 degree angle of attack is governed chiefly by wing profile, and above that angle by wing arrangement. The strip method of autorotation analysis gives uncertain results between maximum C subscript L and 35 degrees. The polar curve of a wing system, and to a lower degree of accuracy the polar of a complete airplane model are sufficient for direct determination of the limits of rotary instability, subject to strip method limitations. The results of the investigation indicate that in free flight a monoplane is incapable of flat spinning, whereas an unstaggered biplane has inherent flat-spinning tendencies. The difficulty of maintaining equilibrium in stalled flight is due primarily to rotary instability, a rapid change from stability to instability occurring as the angle of maximum lift is exceeded. (author)

Knight, Montgomery↗

Control of a Serpentine Robot for Inspection Tasks

This paper presents a simple and robust kinematic control scheme for the JPL serpentine robot system. The proposed strategy is developed using the dampened-least-squares/configuration control methodology, and permits the considerable dexterity of the JPL serpentine robot to be effectively utilized for maneuvering in the congested and uncertain workspaces often encountered in inspection tasks. Computer simulation results are given for the 20 degree-of-freedom (DOF) manipulator system obtained by mounting the twelve DOF serpentine robot at the end-effector of an eight DOF Robotics Research arm/lathe-bed system. These simulations demonstrate that the proposed approach provides an effective method of controlling this complex system.

robotics simulations kinematic control serpentine ↗

Microgravity Isolation Control System Design Via High-Order Sliding Mode Control

Vibration isolation control system design for a microgravity experiment mount is considered. The controller design based on dynamic sliding manifold (DSM) technique is proposed to attenuate the accelerations transmitted to an isolated experiment mount either from a vibrating base or directly generated by the experiment, as well as to stabilize the internal dynamics of this nonminimum phase plant. An auxiliary DSM is employed to maintain the high-order sliding mode on the primary sliding manifold in the presence of uncertain actuator dynamics of second order. The primary DSM is designed for the closed-loop system in sliding mode to be a filter with given characteristics with respect to the input external disturbances.

Shkolnikov, Ilya↗

Mission Concept for a Europa Lander

A NASA HQ-directed study team led by the Jet Propulsion Laboratory (JPL) with partners including Applied Physics Lab, Marshall Space Flight Center, Goddard Space Flight Center, Langley Research Center and Sandia National Laboratory has recently presented a mission concept for a Europa Lander that would search for bio-signatures and signs of life in the near-subsurface of the Jovian moon. The mission would follow the Europa Clipper multiple-flyby mission, planned for launch in June of 2022, which would provide reconnaissance imagery and other data to the Lander for use in selecting a scientifically compelling site and certifying it for engineering safety. The Europa Lander concept accommodates the Model Payload identified by the Europa Lander Science Definition Team (SDT) and documented in the Europa Lander Study 2016 Report released in February of 2017. The currently envisioned Europa Lander would launch on an SLS Block 1B as early as October of 2025 into a VEGA trajectory, arriving in the Jovian system as early as July of 2030. The baseline design of the integrated flight system includes a dedicated Carrier and Relay Stage, a Deorbit Vehicle composed of a Deorbit Stage consisting of a solid rocket motor (SRM), an MSL-like sky-crane Descent Stage, and a Lander which accommodates the instrument suite. The Lander would be powered by primary batteries over a 20-day surface mission. The science goals envisioned by the SDT require five samples taken from a depth of 10cm, a depth chosen to ensure minimal radiation processing of the potential biomarkers. Mission challenges include the large launch mass, unknown terrain topography, surface composition and materials properties, the high radiation environment, and complying with stringent planetary protection requirements. The mission concept uses a strategy of early risk reduction and overlapping requirements to provide robustness to harsh and uncertain environments. Early risk reduction efforts are aimed at maturing technologies associated with the sampling system, the intelligent landing system, high specific energy batteries, low mass and power motor controllers, and a thermal sterilization system.

Dooley, Jennifer↗

On the Diversity of Planetary Systems

Models of planet formation and of the orbital stability of planetary systems are described and used to discuss possible characteristics of undiscovered planetary systems. Modern theories of star and planet formation, which are based upon observations of the Solar System and of young stars and their environments, predict that rocky planets should form in orbit about most single stars. It is uncertain whether or not gas giant planet formation is common, because most protoplanetary disks may dissipate before solid planetary cores can grow large enough to gravitationally trap substantial quantities of gas. A potential hazard to planetary systems is radial decay of planetary orbits resulting from interactions with material within the disk. Planets more massive than Earth have the potential to decay the fastest, and may be able to sweep up smaller planets in their path. The implications of the giant planets found in recent radial velocity searches for the abundances of habitable planets are discussed.

Lissauer, Jack J.↗

The Birth of Planetary Systems

Models of planet formation and of the orbital stability of planetary systems are described and used to discuss possible characteristics of undiscovered planetary systems. Modern theories of star and planet formation, which are based upon observations of the Solar System and of young stars and their environments, predict that rocky planets should form in orbit about most single stars. It is uncertain whether or not gas giant planet formation is common, because most protoplanetary disks may dissipate before solid planetary cores can grow large- enough to gravitationally trap substantial quantities of gas. Another potential hazard to planetary systems is radial decay of planetary orbits resulting from interactions with material within the disk. Planets more massive than Earth have the potential to decay the fastest, and may be able to sweep up smaller planets in their path. The implications of the giant planets found in recent radial velocity searches for the abundances of habitable planets are discussed.

Lissauer, Jack J.↗

Simulation and Analysis of Technology and Operational Procedures to Reduce the Combined Effects of Emissions and Contrails

The development and evaluation of concepts and technology to support future air traffic management systems require a hierarchy of models ranging from real-time simulations to extensive field evaluations. Air traffic simulation models such as Airspace Concept Evaluation System, Center Tracon Automation System, Future Air traffic management Concept Evaluation Tool and others are used to design air traffic systems balancing the conflicting objectives of maximizing safety, meeting future demands for airports and airspace and increase efficiency of traffic flows in the presence of uncertain weather. The impact of aviation emissions and contrails on climate imposes another constraint on the design of aircraft and aviation operations. The understanding of the complex interaction between physical climate system, the carbon and other greenhouse gas emissions and aviation activity can be improved by the development of integrated assessment models that include emission and climate models together with air traffic simulations. The modeling of aircraft emissions and their interaction with each other to change the concentration levels of different gasses in the atmosphere and the resulting impact of the radiative forcing on the equilibrium of the Earth's atmosphere is complex and requires the use of coupled atmosphere-ocean general circulation models together with three-dimensional models of carbon cycle and chemistry of other non-CO2 greenhouse gases. These models are computationally intensive and unsuitable for studies involving the generation of multiple scenarios. Simple emission and climate models, based on the input-output relations of linear systems, capture the fundamental emission to climate impact behavior by careful selection of key variables and their dynamics. The impact of various greenhouse gases depends on the total concentration, effect per unit change in atmospheric concentration and the spatial distribution of the gas. All these quantities are influenced by the lifetime of the gas. The impact of a greenhouse gas depends on the interval of assessment, which may vary from a few decades to a few centuries. Climate metrics are aimed at providing a common scale to compare different greenhouse gases. If the metrics are to be used as a tool in developing and evaluating aviation operations, they should be transparent and easy to apply. Global Warming Potential and Aggregate Global Temperature Potential are some of the commonly used metrics. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability brings together metrics, which are useful in aviation operations together with metrics used in climate studies. The capability can be used to make trade-offs between extra fuel cost and reduction in climate impact. There is considerable uncertainty in our understanding of the radiative forcing associated with emissions and contrails. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails. It can also be used to evaluate the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA's Aviation Environmental Portfolio Management Tool for Impacts.

impact of aviation on the environment↗

A fuzzy case based reasoning tool for model based approach to rocket engine health monitoring

In this system we develop a fuzzy case based reasoner that can build a case representation for several past anomalies detected, and we develop case retrieval methods that can be used to index a relevant case when a new problem (case) is presented using fuzzy sets. The choice of fuzzy sets is justified by the uncertain data. The new problem can be solved using knowledge of the model along with the old cases. This system can then be used to generalize the knowledge from previous cases and use this generalization to refine the existing model definition. This in turn can help to detect failures using the model based algorithms.

Krovvidy, Srinivas↗

Modeling Atmospheric Brown Carbon in the GISS ModelE Earth System Model

Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (RF) of BrC is still highly uncertain. To better understand its climate impact, we introduced BrC to the One-Moment Aerosol (OMA) module of the GISS ModelE Earth system model (ESM). We assessed ModelE sensitivity to primary BrC processed through a novel chemical aging scheme and to secondary BrC formed from biogenic volatile organic compounds (BVOCs). Initial results show that BrC typically contributes a top-of-the-atmosphere (TOA) radiative effect of 0.04 W m −2 . Sensitivity tests indicate that explicitly simulating BrC (separating it from other OAs), including secondary BrC, and simulating chemical bleaching of BrC contribute distinguishable radiative effects and should be accounted for in BrC schemes. This addition of prognostic BrC to ModelE allows greater physical and chemical complexity in OA representation with no apparent trade-off in model performance, as the evaluation of ModelE aerosol optical depth against Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval data, with and without the BrC scheme, reveals similar skill in both cases. Thus, BrC should be explicitly simulated to allow more physically based chemical composition, which is crucial for more detailed OA studies like comparisons to in situ measurement campaigns. We include a summary of best practices for BrC representation within ModelE at the end of this paper.

brown carbon aerosols↗

Surface texture characterization by angular distributions of scattered light

Work at the National Bureau of Standards to develop an on-line optical measurement device and attendant algorithms for automated optical scattering measurements of machined metal surfaces are described. The surfaces could be milled, ground or lapped, and the system is intended to categorize the resulting surface characteristics. The optical device consists of a He-Ne laser which is shone on a surface. The scattered light is captured by a semicircular array of 87 detector elements rotated over the scanned area. The light signals are processed through a digital voltmeter and then an A/D converter. The signals are then stored for later comparisons with optical scattering data obtained by optical instruments used with stylus instruments for characterizing surface topographies. A theoretical model has been defined which relates light scattering and the characteristics of the surface roughness. Initial experimental results with a sinusoidal surface have indicated that although the system can follow the trend of the roughness, the roughness amplitude is as yet uncertainly defined and the computations require excessive time.

Gilsinn, D. E.↗

Magellan spacecraft - Attitude determination, updates and gyro parameter calibration

A detailed mathematical algorithm for onboard autonomous attitude determination and parameter calibration in the Magellan Venus-orbiting spacecraft has been developed, and its performance has been estimated. This algorithm uses a contamination reduction attitude profile and retractive star scan maneuvers to minimize the interparameter error contamination and to maximize the parameter observability. The details of the underlying theory and strategy are described, and an extensive performance analysis with worst-case parameter errors is reported which indicates that the in-flight attitude determination unit/parameter calibration (ADU/PC) algorithm will be able to meet all the different mission phase requirements with comfortable margins. The problem of nonexact mapping retrace due to uncertain performance of control authority is addressed, and its lack of impact on the system performance is demonstrated.

Huang, W. H.↗

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

El Niño–Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.

El Niño–Southern Oscillation (ENSO)↗

A Modeling Approach to Support Changeability Analysis and Management of Earth Observation Portfolios

Earth observing (EO) mission portfolios provide data on many geophysical parameters that collectively inform our understanding of the Earth system. To observe large-scale climate trends, it is important to collect data on many parameters over time. However, gaps may occur between missions due to formulation complexity, development delays, and uncertain events in operations. These gaps may impact the ability to provide sustained measurements. Developing a balanced EO mission portfolio is key to supporting study of the Earth system. Yet, decision-making at the portfolio level is a complex task because missions often address multiple parameters. Currently, the likelihood of data gaps is often assessed for an individual parameter, but decisions and events can impact data collection for many parameters. This poster introduces a modeling approach that supports management of the many parameter impacts of decisions and uncertain events. The approach provides a foundation for analyzing changeability in EO mission portfolios. Changeability analysis provides insight into a portfolio’s sensitivity to changes caused by decisions or uncertain events. The model is developed to analyze two aspects of changeability, robustness and flexibility, in EO mission portfolios. In context of these portfolios, the authors define robustness as a portfolio’s ability to provide sustained measurements despite future uncertainties, and they define flexibility as the availability of decision alternatives that contribute to parameter coverage at little detriment to the rest of the portfolio. The proposed model characterizes a portfolio’s sensitivity to change by capturing mission-parameter interconnectivity and redundancy in parameter coverage. The model can be analyzed to identify events that can create substantial gaps, thereby revealing focus areas for mitigation efforts. The model can also be analyzed to identify gap mitigation decisions that may improve parameter coverage with little detriment to the rest of the portfolio, thereby revealing favorable pathways for portfolio improvement. Developing a process for identifying these threats and opportunities will be the focus of future work. A parallel poster proposes a standard for visualizing and communicating portfolio-level impacts of decisions and uncertain events.

Lindsey Jacobson↗

The Impact of Model Uncertainty on Spatial Compensation in Structural Acoustic Control

Turbulent boundary layer (TBL) noise is considered a primary contribution to the interior noise present in commercial airliners. There are numerous investigations of interior noise control devoted to aircraft panels; however, practical realization is a potential challenge since physical boundary conditions are uncertain at best. In most prior studies, pinned or clamped boundary conditions were assumed; however, realistic panels likely display a range of boundary conditions between these two limits. Uncertainty in boundary conditions is a challenge for control system designers, both in terms of the compensator implemented and the location of transducers required to achieve the desired control. The impact of model uncertainties, specifically uncertain boundaries, on the selection of transducer locations for structural acoustic control is considered herein. The final goal of this work is the design of an aircraft panel structure that can reduce TBL noise transmission through the use of a completely adaptive, single-input, single-output control system. The feasibility of this goal is demonstrated through the creation of a detailed analytical solution, followed by the implementation of a test model in a transmission loss apparatus. Successfully realizing a control system robust to variations in boundary conditions can lead to the design and implementation of practical adaptive structures that could be used to control the transmission of sound to the interior of aircraft. Results from this research effort indicate it is possible to optimize the design of actuator and sensor location and aperture, minimizing the impact of boundary conditions on the desired structural acoustic control.

Clark, Robert L.↗

The role and use of the stochastic linear-quadratic-Gaussian problem in control system design.

The role of the linear-quadratic stochastic control problem in engineering design is reviewed in tutorial fashion. The design approach is motivated by considering the control of a nonlinear uncertain plant about a desired input-output response. It is demonstrated how a design philosophy based on (1) deterministic perturbation control, (2) stochastic state estimation, and (3) linearized stochastic control leads to an overall closed-loop control system. The emphasis of the paper is on the philosophy of the design process, the modeling issue, and the formulation of the problem; the results are given for the sake of completeness, but no proofs are included. The systematic off-line nature of the design process is stressed throughout.

Athans, M.↗

Convective Weather Avoidance with Uncertain Weather Forecasts

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

Karahan, Sinan↗

Analysis and Optimization of Test Plans for Advanced Exploration Systems Reliability and Supportability

Future crewed exploration missions beyond Low Earth Orbit (LEO) will operate farther from Earth and be logistically isolated for longer than any previous human spaceflight mission. Under these conditions, supportability and reliability willbestronger drivers of mission mass and risk than they have been in the past. Items with high failure rates, or uncertain failure rates, can result in high spares mass requirements and/or high risk on deep space missions. Testing is a critical element of system development which provides the opportunity to identify and resolve design issues, defects, or other failure modes before they cause problems during a mission. Reliability growth programs can reduce failure rates by identifying and remove failure modes via design changes, and long-duration life testing can provide valuable data to reduce failure rate estimate uncertainty and verify (to some level of confidence) that components are as reliable as expected. Testing activities take time and resources, however, and must be incorporated into program plans in order to be fully effective. This paper presents an integrated reliability test plan analysis and optimization methodology, which has been used to inform Advanced Exploration Systems (AES) Life Support Systems (LSS) ground test planning for future missions. The methodology determines the optimal number of test units to purchase and allocation of test time –split between reliability growth and uncertainty reduction testing –across a given set of items in order to minimize spares mass for a given mission under constraints on total test cost and schedule. Model outputs also include expected spares mass after testing and the expected number of modifications or refurbishments during testing, both of which can inform program planning. Discussion of the model, conclusions, and future work are also presented.

Testing↗