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At least 379 records · Page 21

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NASA NTRS2013

Nuclear Thermal Rocket Simulation in NPSS

Four nuclear thermal rocket (NTR) models have been created in the Numerical Propulsion System Simulation (NPSS) framework. The models are divided into two categories. One set is based upon the ZrC-graphite composite fuel element and tie tube-style reactor developed during the Nuclear Engine for Rocket Vehicle Application (NERVA) project in the late 1960s and early 1970s. The other reactor set is based upon a W-UO2 ceramic- metallic (CERMET) fuel element. Within each category, a small and a large thrust engine are modeled. The small engine models utilize RL-10 turbomachinery performance maps and have a thrust of approximately 33.4 kN (7,500 lbf ). The large engine models utilize scaled RL-60 turbomachinery performance maps and have a thrust of approximately 111.2 kN (25,000 lbf ). Power deposition profiles for each reactor were obtained from a detailed Monte Carlo N-Particle (MCNP5) model of the reactor cores. Performance factors such as thermodynamic state points, thrust, specific impulse, reactor power level, and maximum fuel temperature are analyzed for each engine design.

Belair, Michael L.↗

NASA NTRS2013

Nuclear Thermal Rocket Simulation in NPSS

Four nuclear thermal rocket (NTR) models have been created in the Numerical Propulsion System Simulation (NPSS) framework. The models are divided into two categories. One set is based upon the ZrC-graphite composite fuel element and tie tube-style reactor developed during the Nuclear Engine for Rocket Vehicle Application (NERVA) project in the late 1960s and early 1970s. The other reactor set is based upon a W-UO2 ceramic-metallic (CERMET) fuel element. Within each category, a small and a large thrust engine are modeled. The small engine models utilize RL-10 turbomachinery performance maps and have a thrust of approximately 33.4 kN (7,500 lbf ). The large engine models utilize scaled RL-60 turbomachinery performance maps and have a thrust of approximately 111.2 kN (25,000 lbf ). Power deposition profiles for each reactor were obtained from a detailed Monte Carlo N-Particle (MCNP5) model of the reactor cores. Performance factors such as thermodynamic state points, thrust, specific impulse, reactor power level, and maximum fuel temperature are analyzed for each engine design.

Belair, Michael L.↗

NASA NTRSDate not supplied

The OSSE Framework at the NASA Global Modeling and Assimilation Office (GMAO)

The Global Modeling and Assimilation Office (GMAO) has been developing an Observing System Simulation Experiment (OSSE) framework. The OSSE system is currently based on the Nature Run (NR) developed by GMAO called G5NR. The G5NR is currently being tested for use in the GMAO OSSE framework. Synthetic observations have been generated based on the G5NR fields, including conventional observations, GPS, and satellite radiances. These synthetic observations are ingested using the Gridpoint Statistical Interpolation data assimilation system, with forecasts performed by the GEOS-5 model at 55 km/72L.

OSSE Framework↗

NASA NTRS2002

Micro-Mechanical Modeling of Ductile Fracture in Welded Aluminum-Lithium Alloys

This study describes a 3-D computational framework to model stable extension of a macroscopic crack under mode I conditions in ductile metals. Material separation occurs through a local fracture mechanism based on the growth and coalescence of micro voids dispersed in the material. The Gurson-Tvergaard plasticity model for void materials describes the eventual loss of material stress capacity under sustained loading. Fixed-sized computational cell elements defined on a thin layer adjacent to the crack plane provide an implicit length scale for continuum damage model. Outside this layer, the material remains undamaged by void growth, consistent with metallurgical observations. The key micro-mechanics parameters are D, the thickness of cell layer, and f 0 , the initial cell porosity.

Ahmed Ibrahim↗

NASA NTRS2015

Model-Based Prognostics of Hybrid Systems

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

prognosis↗

NASA NTRS2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Robert S. Schrom↗

NASA NTRS1989

Simple method for model reference adaptive control

A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.

Seraji, H.↗

NASA NTRS2018

Hybrid Reduced Order Model for N2-N2 Interactions for Application to Dissociation and Energy Transfer Processes

This work presents a general framework for model reduction of non-equilibrium energy transfer and dissociation processes. The multi-group maximum-entropy method is coupled with the quasi-classical trajectory method to directly construct a reduced order model for chemical non-equilibrium. Kinetic data is calculated by applying detailed balance at a microscopic level, overcoming the limitation of calculating recombination kinetic data. This approach enables the construction of a reduced order model for kinetics which bypasses the need to compute state-to-state kinetic data. This physics based reduced order model ensures that an equilibrium distribution is reached given infinite time, while allowing for non-equilibrium distributions during the relaxation and dissociation processes. A proof-of-concept test case demonstrates the applicability of this model by comparison with state-to-state kinetic data for the N2(Chi (sup 1) Sigma ((sub g), (sup plus sign)) minus N ((exp 4) S (sub u)) system with excellent agreement.

Maximum Entropy↗

NASA NTRS2021

Improving the Representation of Subtropical Boundary Layer Clouds in the NASA GEOS Model with the Eddy-Diffusivity/Mass-Flux Parameterization

A systematic underestimation of subtropical planetary boundary layer (PBL) stratocu-mulus clouds by the GEOS model has been significantly improved by a new Eddy-Diffusivity/Mass-Flux (EDMF) parameterization. The EDMF parameterization representsthe subgrid-scale transport in the dry and moist parts of the PBL in a unified mannerand it combines an adjusted eddy-diffusivity PBL scheme from GEOS with a stochasticmulti-plume mass-flux model. The new EDMF version of the GEOS model is first com-pared against the CONTROL version in a single-column model (SCM) framework for twobenchmark cases representing subtropical stratocumulus and shallow cumulus clouds, andvalidated against large eddy simulations. Global simulations are performed and comparedagainst observations and reanalysis data. The results show that the EDMF version of theGEOS model produces more realistic subtropical PBL clouds. Noteworthy, the EDMF im-provements first detected in the SCM framework translate into similar improvements of theglobal GEOS model.

Kay Suselj↗

NASA NTRS2011

Modeling Humans as Reinforcement Learners: How to Predict Human Behavior in Multi-Stage Games

This paper introduces a novel framework for modeling interacting humans in a multi-stage game environment by combining concepts from game theory and reinforcement learning. The proposed model has the following desirable characteristics: (1) Bounded rational players, (2) strategic (i.e., players account for one anothers reward functions), and (3) is computationally feasible even on moderately large real-world systems. To do this we extend level-K reasoning to policy space to, for the first time, be able to handle multiple time steps. This allows us to decompose the problem into a series of smaller ones where we can apply standard reinforcement learning algorithms. We investigate these ideas in a cyber-battle scenario over a smart power grid and discuss the relationship between the behavior predicted by our model and what one might expect of real human defenders and attackers.

Lee, Ritchie↗

NASA NTRS2023

A Framework for Evaluating Distributed Electric Propulsion on the SUSAN Electrofan Aircraft

This work presents a framework for evaluating models and algorithms for Distributed Electric Propulsion (DEP) on the SUSAN Electrofan Aircraft. Throughout the development of the SUSAN aircraft, the performance of various configurations of the aircraft will need to be analyzed. However, the static behavior alone is not sufficient to describe the performance of these configurations. Therefore, simulation with fully integrated subsystem models is required. The proposed framework considers the vehicle aerodynamic, propulsion, and control subsystems. The presented framework automatically generates control laws for any vehicle configuration in response to changes in these subsystems. To compare these different vehicle configurations, various time and frequency domain performance metrics are compared. Three different system modifications are used as cases to evaluate this framework. The first modification integrates the propulsion control system with the flight controller to enable differential thrust without stalling the main engine. This evaluation case is used to validate the framework for aircraft configurations with coupled subsystems. The second modification compares the effect of the vertical tail size on open and closed loop performance. This evaluation case is used to validate the framework for controlling different configurations and tuning towards comparable closed loop performance despite changes to the aircraft's aerodynamic model. The third modification implements two different control allocation schemes. This evaluation case demonstrates the framework's ability to evaluate allocation modifications needed to take advantage of DEP. The first evaluation case is used to show that controller integration enables differential thrust, improving realized wingfan bandwidth by up to 40\% in simulation. The second evaluation case demonstrates that the framework can stabilize the reduced tail size aircraft with closed loop control. The third evaluation case demonstrates that a pseudoinverse control allocation scheme improves lateral velocity settling time by approximately 17~seconds over a symmetric-thrust allocation. These cases show that the framework is useful for evaluating the performance of integrated system designs, enabling analyses of new models and algorithms for the SUSAN distributed electric propulsion vehicle.

Nicholas C Ogden↗

NASA NTRS2016

Predicting Real-Time Safety of the National Airspace System

To gain the situational awareness necessary for informed decision making regarding avoidance of airspace hazards, each operator must consolidate operations-relevant information from disparate sources and apply extensive domain knowledge to correctly interpret not just the current state of the NAS but forecast its (combined) evolution over the duration of the operation. This time- and workload-intensive process is periodically repeated throughout the operation so that changes can be managed in a timely manner.The imprecision, inaccuracies, inconsistency, and incompleteness of the incoming data further challenges the process. To facilitate informed decision making, this paper presents a model-based framework for the textitautomated real-time monitoring and prediction of possible effects of airspace hazards on the safety of the National Airspace System (NAS). First, hazards to flight are identified and transformed into sms, that is, quantities of interest that could be evaluated based on available data and are predictive of an unsafe event. The sms and associated thresholds that specify when an event transitions from emphsafe to emphunsafe are combined with models of airspace operations and aircraft dynamics. The framework can include any hazard to flight that can be modeled quantitatively. Models can be detailed and complex, or they can be considerably simplifed, as appropriate to the application. Real-time NAS safety monitoring and prediction begins with an estimate of the state of the NAS using the dynamic models. Given the state estimate and a probability distribution of future inputs to the NAS, we can then predict the evolution of the NAS - the future state - and the occurrence of hazards and unsafe events. The entire probability distribution of airspace sms is computed, not just point estimates, without significant assumptions regarding the distribution type andor parameters. We demonstrate our overall approach through a simulated scenario in which we predict the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress. Predictions accounting for common sources of uncertainty are included and it is shown how the predictions improve in time, become more confident, and change dynamically as new information is made available to the prediction algorithm.

safety↗

NASA NTRS2013

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗

NASA NTRS2016

Model Based Mission Assurance in a Model Based Systems Engineering (MBSE) Framework: State-of-the-Art Assessment

This report explores the current state of the art of Safety and Mission Assurance (S&MA) in projects that have shifted towards Model Based Systems Engineering (MBSE). Its goal is to provide insight into how NASA’s Office of Safety and Mission Assurance (OSMA) should respond to this shift. In MBSE, systems engineering information is organized and represented in models: rigorous computer-based representations, which collectively make many activities easier to perform, less error prone, and scalable. S&MA practices must shift accordingly. The “Objective Structure Hierarchies” recently developed by OSMA provide the framework for understanding this shift. Although the objectives themselves will remain constant, S&MA practices (activities, processes, tools) to achieve them are subject to change. This report presents insights derived from literature studies and interviews. The literature studies gleaned assurance implications from reports of space-related applications of MBSE. The interviews with knowledgeable S&MA and MBSE personnel discovered concerns and ideas for how assurance may adapt. Preliminary findings and observations are presented on the state of practice of S&MA with respect to MBSE, how it is already changing, and how it is likely to change further. Finally, recommendations are provided on how to foster the evolution of S&MA to best fit with MBSE.

Aerospace engineering↗

NASA NTRSDate not supplied

Credible Practice of Models and Simulations for Healthcare

As computational models penetrate clinical care and drive healthcare policy decisions, there is increasing need to communicate that model creation and testing follows reasonable credible practice. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. This presentation introduces the Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative multidisciplinary analysis and practitioner survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. Although some of these are common sense guidelines, many are often missed or misconstrued, even by seasoned practitioners.

credibility↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

This paper presents a technical approach to improve the confidence in the systems analysis process by integrating Uncertainty Quantification (UQ) techniques within a Model-Based Systems Analysis and Engineering (MBSA&E) framework. The MBSA&E architecture uses system models and multidisciplinary analytical solutions as central artifacts for system design and analysis. The integration of UQ enables engineers to assess and mitigate uncertainties associated with a system model, design parameters, and constraint inputs, leading to more complete design studies and further informed decision-making processes. The proposed approach leverages the strengths of MBSA&E and extends it with a UQ methodology to quantify uncertainties in the input parameters and to trace the uncertainties as they propagate throughout the system model. To demonstrate the effectiveness of an integrated MBSA&E-UQ approach, a case study involving a simplified analysis of a Transonic Truss-Braced Wing (TTBW) concept vehicle is performed. This integration enables a more comprehensive evaluation of system performance and behavior under uncertainty and a more robust approach for system design and analysis. Lastly, the paper addresses the challenges and considerations associated with integrating UQ into an MBSA&E framework.

systems analysis↗

NASA NTRS2000

Safety Metrics for Human-Computer Controlled Systems

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems.This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Leveson, Nancy G↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

systems analysis↗