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At least 163 records · Page 9

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NASA NTRS1984

Thermal mathematical modeling and system simulation of Space Shuttle less subsystem

Applications, validation tests, and upgrades of the two- and three-dimensional system level thermal mathematical system simulation models (TMSSM) used for thermal protection system (TPS) analyses are described. The TMSSM were developed as an aid to predicting the performance requirements and configurations of the Shuttle wing leading edge (WLE) and nose cone (NC) TPS tiles. The WLE and its structure were subjected to acoustic, thermal/vacuum, and air loads tests to simulate launch, on-orbit, and re-entry behavior. STS-1, -2 and -5 flight data led to recalibration of on-board instruments and raised estimates of the thermal shock at the NC and WLE. Baseline heating data are now available for the design of future TPS.

Chao, D. C.↗

NASA NTRS2011

Ontological Modeling for Integrated Spacecraft Analysis

Current spacecraft work as a cooperative group of a number of subsystems. Each of these requiresmodeling software for development, testing, and prediction. It is the goal of my team to create anoverarching software architecture called the Integrated Spacecraft Analysis (ISCA) to aid in deploying the discrete subsystems' models. Such a plan has been attempted in the past, and has failed due to the excessive scope of the project. Our goal in this version of ISCA is to use new resources to reduce the scope of the project, including using ontological models to help link the internal interfaces of subsystems' models with the ISCA architecture.I have created an ontology of functions specific to the modeling system of the navigation system of a spacecraft. The resulting ontology not only links, at an architectural level, language specificinstantiations of the modeling system's code, but also is web-viewable and can act as a documentation standard. This ontology is proof of the concept that ontological modeling can aid in the integration necessary for ISCA to work, and can act as the prototype for future ISCA ontologies.

ontological modeling↗

NASA NTRSDate not supplied

Systems Health Management and Decision Making

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Discuss research approach to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms. Note - This presentation is for the short workshop conducted at the same conference and contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS2018

Systems Health Monitoring and Prognostics Using Model Based Approach

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms.

Electronics Prognostics↗

NASA NTRS1983

Operations simulation for the design of a future space transportation system

A high, level discrete simulation model has been developed to study the operational requirements of future space transportation systems. To illustrate the capabilities of this model, the result of a study for a future fully reusable, two-stage launch vehicle concept which delivers men and material to a space station and returns are presented. Orbital transfer vehicles, based at the space station, are also included for delivery to other orbits. Results are presented which indicate that the model can be a helpful tool in evaluating the transportation system's operational needs and its ability to meet the desired mission requirements.

Morris, W. D.↗

NASA NTRS2020

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗

NASA NTRS2016

Evaluation of Contamination Inspection and Analysis Methods through Modeling System Performance

Contamination is usually identified as a risk on the risk register for sensitive space systems hardware. Despite detailed, time-consuming, and costly contamination control efforts during assembly, integration, and test of space systems, contaminants are still found during visual inspections of hardware. Improved methods are needed to gather information during systems integration to catch potential contamination issues earlier and manage contamination risks better. This research explores evaluation of contamination inspection and analysis methods to determine optical system sensitivity to minimum detectable molecular contamination levels based on IEST-STD-CC1246E non-volatile residue (NVR) cleanliness levels. Potential future degradation of the system is modeled given chosen modules representative of optical elements in an optical system, minimum detectable molecular contamination levels for a chosen inspection and analysis method, and determining the effect of contamination on the system. By modeling system performance based on when molecular contamination is detected during systems integration and at what cleanliness level, the decision maker can perform trades amongst different inspection and analysis methods and determine if a planned method is adequate to meet system requirements and manage contamination risk.

Seasly, Elaine↗

NASA NTRS1992

Ge's Mobile, Coherent Doppler Lidar Test/Ealuation Facilities

The primary objective of this independent research and development (IR and D) program in support of the Laser Atmospheric Wind Sounder (LAWS) program is to develop and evaluate technologies with direct applications to spaceborne laser wind sensing, and to develop system level engineering experience in designing, operating, and modeling a coherent Doppler lidar. GE is developing a mobile, ground based coherent Doppler lidar as an end-to-end system level test facility to evaluate applicable technologies, verify system level performance issues, perform instrument calibration, and validate end-to-end system performance model predictions. Here, the primary focus is on a description of the ground based lidar system and the performance during the initial shakedown operation after system integration.

Sroga, J. T.↗

NASA NTRS2015

Numerical Modeling of Self-Pressurization and Pressure Control by Thermodynamic Vent System in a Cryogenic Tank

This paper presents a numerical model of a system-level test bed - the multipurpose hydrogen test bed (MHTB) using Generalized Fluid System Simulation Program (GFSSP). MHTB is representative in size and shape of a fully integrated space transportation vehicle liquid hydrogen (LH2) propellant tank and was tested at Marshall Space Flight Center (MSFC) to generate data for cryogenic storage. GFSSP is a finite volume based network flow analysis software developed at MSFC and used for thermo-fluid analysis of propulsion systems. GFSSP has been used to model the self-pressurization and ullage pressure control by Thermodynamic Vent System (TVS). A TVS typically includes a Joule-Thompson (J-T) expansion device, a two-phase heat exchanger, and a mixing pump and spray to extract thermal energy from the tank without significant loss of liquid propellant. Two GFSSP models (Self-Pressurization & TVS) were separately developed and tested and then integrated to simulate the entire system. Self-Pressurization model consists of multiple ullage nodes, propellant node and solid nodes; it computes the heat transfer through Multi-Layer Insulation blankets and calculates heat and mass transfer between ullage and liquid propellant and ullage and tank wall. TVS model calculates the flow through J-T valve, heat exchanger and spray and vent systems. Two models are integrated by exchanging data through User Subroutines of both models. The integrated models results have been compared with MHTB test data of 50% fill level. Satisfactory comparison was observed between test and numerical predictions.

Majumdar, Alok↗

NASA NTRS1991

Modeling of Space Station power system components and their interactions

The authors demonstrate that the functional modeling approach is feasible in modeling large-scale spacecraft power systems such as the Space Station electric power system (EPS). The functional models for the solar array sequential shunt unit and the battery charging/discharging unit are presented. The functional modeling approach has also been applied to simulate other major EPS components. The usefulness of this approach in system-level studies has been demonstrated by incorporating these models into a power system model and simulating the system behavior under various conditions. The simulation results are consistent with those obtained experimentally. With larger time step size and reduced model complexity, the computation time required by the functional modeling approach is short. Functional models are effective in simulation studies of system-level issues, especially for large-scale power systems including many power electronic components.

Tam, Kwa-Sur↗

NASA NTRS1994

Hierarchical modeling for reliability analysis using Markov models

Markov models represent an extremely attractive tool for the reliability analysis of many systems. However, Markov model state space grows exponentially with the number of components in a given system. Thus, for very large systems Markov modeling techniques alone become intractable in both memory and CPU time. Often a particular subsystem can be found within some larger system where the dependence of the larger system on the subsystem is of a particularly simple form. This simple dependence can be used to decompose such a system into one or more subsystems. A hierarchical technique is presented which can be used to evaluate these subsystems in such a way that their reliabilities can be combined to obtain the reliability for the full system. This hierarchical approach is unique in that it allows the subsystem model to pass multiple aggregate state information to the higher level model, allowing more general systems to be evaluated. Guidelines are developed to assist in the system decomposition. An appropriate method for determining subsystem reliability is also developed. This method gives rise to some interesting numerical issues. Numerical error due to roundoff and integration are discussed at length. Once a decomposition is chosen, the remaining analysis is straightforward but tedious. However, an approach is developed for simplifying the recombination of subsystem reliabilities. Finally, a real world system is used to illustrate the use of this technique in a more practical context.

Fagundo, Arturo↗

NASA NTRS1989

System level design analyses for the Space Station Environmental Control and Life Support System

The development and verification of a computer model for the design and analysis of the current Space Station ECLSS configuration are discussed. The model is used to resolve system-level design issues, such as sizing accumulators and assessing flow control techniques. Actual component verification efforts are outlined, and technical aspects of each component model are identified. The results obtained to date and plans for future analytical efforts are summarized.

Bacskay, A. S.↗

NASA NTRSDate not supplied

Parametric Systems Analysis of a Mid-Lift/Drag Entry System for Human Mars Mission

Mars entry systems are complex with many competing design objectives. This paper presents a data-driven and physics-based approach to systems analysis and tradespace exploration for a human Mars entry system using a Mid-Lift/Drag aerodynamic decelerator. The baseline entry system includes elements for Mars aerocapture, entry, descent, and landing segments of the mission. The approach uses a set of parametric models that enable a system-level analysis, vehicle sizing, sensitivity analysis, and tradespace exploration. The paper provides a brief introduction of the Mid-Lift/Drag concept, an overview of parametric models, discussions on alternative structural concepts, results from system-level analysis, and summary remarks.

Jamshid A Samareh↗

NASA NTRS2013

The Value of SysML Modeling During System Operations: A Case Study

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

Dutenhoffer, Chelsea↗

NASA NTRS2004

Assume-Guarantee Verification of Source Code with Design-Level Assumptions

Model checking is an automated technique that can be used to determine whether a system satisfies certain required properties. To address the 'state explosion' problem associated with this technique, we propose to integrate assume-guarantee verification at different phases of system development. During design, developers build abstract behavioral models of the system components and use them to establish key properties of the system. To increase the scalability of model checking at this level, we have developed techniques that automatically decompose the verification task by generating component assumptions for the properties to hold. The design-level artifacts are subsequently used to guide the implementation of the system, but also to enable more efficient reasoning at the source code-level. In particular we propose to use design-level assumptions to similarly decompose the verification of the actual system implementation. We demonstrate our approach on a significant NASA application, where design-level models were used to identify; and correct a safety property violation, and design-level assumptions allowed us to check successfully that the property was presented by the implementation.

Giannakopoulou, Dimitra↗

NASA NTRS1978

SIMWEST - A simulation model for wind energy storage systems

This paper describes a comprehensive and efficient computer program for the modeling of wind energy systems with storage. The level of detail of SIMWEST (SImulation Model for Wind Energy STorage) is consistent with evaluating the economic feasibility as well as the general performance of wind energy systems with energy storage options. The software package consists of two basic programs and a library of system, environmental, and control components. The first program is a precompiler which allows the library components to be put together in building block form. The second program performs the technoeconomic system analysis with the required input/output, and the integration of system dynamics. An example of the application of the SIMWEST program to a current 100 kW wind energy storage system is given.

Edsinger, R. W.↗

NASA NTRS2015

An Empirical Jet-Surface Interaction Noise Model with Temperature and Nozzle Aspect Ratio Effects

An empirical model for jet-surface interaction (JSI) noise produced by a round jet near a flat plate is described and the resulting model evaluated. The model covers unheated and hot jet conditions (1 less than or equal to jet total temperature ratio less than or equal to 2.7) in the subsonic range (0.5 less than or equal to M(sub a) less than or equal to 0.9), surface lengths 0.6 less than or equal to (axial distance from jet exit to surface trailing edge (inches)/nozzle exit diameter) less than or equal to 10, and surface standoff distances (0 less than or equal to (radial distance from jet lipline to surface (inches)/axial distance from jet exit to surface trailing edge (inches)) less than or equal to 1) using only second-order polynomials to provide predictable behavior. The JSI noise model is combined with an existing jet mixing noise model to produce exhaust noise predictions. Fit quality metrics and comparisons to between the predicted and experimental data indicate that the model is suitable for many system level studies. A first-order correction to the JSI source model that accounts for the effect of nozzle aspect ratio is also explored. This correction is based on changes to the potential core length and frequency scaling associated with rectangular nozzles up to 8:1 aspect ratio. However, more work is needed to refine these findings into a formal model.

Noise↗

NASA NTRS2012

New Therapeutic Window of Regenerative Opportunity in Diabetic Retinopathy by VESGEN Analysis

Vascular pattern may serve as a useful new biomarker principle of complex, multi-scale signaling in pathological, physiological angiogenesis and microvascular remodeling. Each angiogenesis stimulator or inhibitor we have analyzed, including VEGF, bFGF, TGF-beta1, angiostatin and triamcinolone acetonide, has induced a novel "fingerprint" or "signature" biomarker vascular pattern that is spatio-temporally unique. Remodeling vasculature thereby provides an informative read-out of dominant molecular signaling, when analyzed by innovative, fractal-based VESsel GENeration (VESGEN) Analysis software. Using VESGEN to analyze ophthalmic clinical vascular images, we recently introduced a potential paradigm shift to the understanding of early-stage progression that suggests new regenerative opportunities for human diabetic retinopathy (DR), the major blinding disease for working-aged adults. In a pilot study, we discovered that angiogenesis oscillates as a surprising, homeostatic-like regeneration of retinal vessels during early progression of DR (IOVS 51(1):498). Results suggest that the term non-proliferative DR may be a misnomer. In new studies, normalization of the vasculature will be determined from the response of vascular pattern to therapeutic monitoring and treatment. We have mapped and quantified in vivo experimental models of angiogenesis, lymphangiogenesis and intravital blood flow from cellular/molecular to higher systems levels that include a murine model of infant retinopathy of prematurity (ROP); developing and pathological coronary and placental-like vessel models; progressive intestinal inflammation, growing murine tumors, and other pathological, physiological and therapeutically treated tissues of transgenic mice and avian embryos. Vascular Alterations, Visual Impairments (VIIP) & Increased Intracranial Pressure (ICP), Immunosuppression & Bone Loss: NASA-defined risk categories for human space exploration and ISS Utilization

Parsons-Wingert, Patricia A.↗