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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Model Based Systems Engineering on the Europa Mission Concept Study

At the start of 2011, the proposed Jupiter Europa Orbiter (JEO) mission was staffing up in expectation of becoming an official project later in the year for a launch in 2020. A unique aspect of the pre-project work was a strong emphasis and investment on the foundations of Model-Based Systems Engineering (MBSE). As so often happens in this business, plans changed: NASA's budget and science priorities were released and together fundamentally changed the course of JEO. As a result, it returned to being a study task whose objective is to propose more affordable ways to accomplish the science. As part of this transition, the question arose as to whether it could continue to afford the investment in MBSE. In short, the MBSE infusion has survived and is providing clear value to the study effort. By leveraging the existing infrastructure and a modest additional investment, striking advances in the capture and analysis of designs using MBSE were achieved. In the process, the need to remain relevant in the new environment has brought about a wave of innovation and progress. The effort has reaffirmed the importance of architecting. It has successfully harnessed the synergistic relationship of architecting to system modeling. We have found that MBSE can provide greater agility than traditional methods. We have also found that a diverse 'ecosystem' of modeling tools and languages (SysML, Mathematica, even Excel) is not only viable, but an important enabler of agility and adaptability. This paper will describe the successful application of MBSE in the dynamic environment of early mission formulation, the significant results produced and lessons learned in the process.

Bayer, Todd J.↗
NASA NTRS2012

Model-Based Systems Engineering Approach to Managing Mass Margin

When designing a flight system from concept through implementation, one of the fundamental systems engineering tasks ismanaging the mass margin and a mass equipment list (MEL) of the flight system. While generating a MEL and computing a mass margin is conceptually a trivial task, maintaining consistent and correct MELs and mass margins can be challenging due to the current practices of maintaining duplicate information in various forms, such as diagrams and tables, and in various media, such as files and emails. We have overcome this challenge through a model-based systems engineering (MBSE) approach within which we allow only a single-source-of-truth. In this paper we describe the modeling patternsused to capture the single-source-of-truth and the views that have been developed for the Europa Habitability Mission (EHM) project, a mission concept study, at the Jet Propulsion Laboratory (JPL).

cloud comu↗
NASA NTRS2016

Advanced Control Considerations for Turbofan Engine Design

This paper covers the application of a model-based engine control (MBEC) methodology featuring a self tuning on-board model for an aircraft turbofan engine simulation. The nonlinear engine model is capable of modeling realistic engine performance, allowing for a verification of the advanced control methodology over a wide range of operating points and life cycle conditions. The on-board model is a piece-wise linear model derived from the nonlinear engine model and updated using an optimal tuner Kalman Filter estimation routine, which enables the on-board model to self-tune to account for engine performance variations. MBEC is used here to show how advanced control architectures can improve efficiency during the design phase of a turbofan engine by reducing conservative operability margins. The operability margins that can be reduced, such as stall margin, can expand the engine design space and offer potential for efficiency improvements. Application of MBEC architecture to a nonlinear engine simulation is shown to reduce the thrust specific fuel consumption by approximately 1% over the baseline design, while maintaining safe operation of the engine across the flight envelope.

control↗
NASA NTRS2016

Interface Management for a NASA Flight Project Using Model-Based Systems Engineering (MBSE)

The goal of interface management is to identify, define, control, and verify interfaces; ensure compatibility; provide an efficient system development; be on time and within budget; while meeting stakeholder requirements. This paper will present a successful seven-step approach to interface management used in several NASA flight projects. The seven-step approach using Model Based Systems Engineering will be illustrated by interface examples from the Materials International Space Station Experiment-X (MISSE-X) project. The MISSE-X was being developed as an International Space Station (ISS) external platform for space environmental studies, designed to advance the technology readiness of materials and devices critical for future space exploration. Emphasis will be given to best practices covering key areas such as interface definition, writing good interface requirements, utilizing interface working groups, developing and controlling interface documents, handling interface agreements, the use of shadow documents, the importance of interface requirement ownership, interface verification, and product transition.

Vipavetz, Kevin↗
NASA NTRS2017

Modeling of a Turbofan Engine with Ice Crystal Ingestion in the NASA Propulsion System Laboratory

The main focus of this study is to apply a computational tool for the flow analysis of the turbine engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) at NASA Glenn Research Center. The PSL has been used to test a highly instrumented Honeywell ALF502R-5A (LF11) turbofan engine at simulated altitude operating conditions. Test data analysis with an engine cycle code and a compressor flow code was conducted to determine the values of key icing parameters, that can indicate the risk of ice accretion, which can lead to engine rollback (un-commanded loss of engine thrust). The full engine aerothermodynamic performance was modeled with the Honeywell Customer Deck specifically created for the ALF502R-5A engine. The mean-line compressor flow analysis code, which includes a code that models the state of the ice crystal, was used to model the air flow through the fan-core and low pressure compressor. The results of the compressor flow analyses included calculations of the ice-water flow rate to air flow rate ratio (IWAR), the local static wet bulb temperature, and the particle melt ratio throughout the flow field. It was found that the assumed particle size had a large effect on the particle melt ratio, and on the local wet bulb temperature. In this study the particle size was varied parametrically to produce a non-zero calculated melt ratio in the exit guide vane (EGV) region of the low pressure compressor (LPC) for the data points that experienced a growth of blockage there, and a subsequent engine called rollback (CRB). At data points where the engine experienced a CRB having the lowest wet bulb temperature of 492 degrees Rankine at the EGV trailing edge, the smallest particle size that produced a non-zero melt ratio (between 3 percent - 4 percent) was on the order of 1 micron. This value of melt ratio was utilized as the target for all other subsequent data points analyzed, while the particle size was varied from 1 micron - 9.5 microns to achieve the target melt ratio. For data points that did not experience a CRB which had static wet bulb temperatures in the EGV region below 492 degrees Rankine, a non-zero melt ratio could not be achieved even with a 1 micron ice particle size. The highest value of static wet bulb temperature for data points that experienced engine CRB was 498 degrees Rankine with a particle size of 9.5 microns. Based on this study of the LF11 engine test data, the range of static wet bulb temperature at the EGV exit for engine CRB was in the narrow range of 492 degrees Rankine - 498 degrees Rankine , while the minimum value of IWAR was 0.002. The rate of blockage growth due to ice accretion and boundary layer growth was estimated by scaling from a known blockage growth rate that was determined in a previous study. These results obtained from the LF11 engine analysis formed the basis of a unique “icing wedge.”

Turbo engine↗
NASA NTRS1991

Integrated flow and structural modeling for rocket engine component test facility propellant systems

A set of PC-based computational Dynamic Fluid Flow Simulation models is presented for modeling facility gas and cryogenic systems. Data obtained provide important information regarding performance envelope parameters for the facility using different engine components; time-dependent valve setting for controlling steady-state, quasi-steady state, and transient profiles; optimum facility pipe and pipe component sizes and parameters; momentum transfer loads; and fluid conditions at critical points. A set of COSMIC NASTRAN-based finite element models is also presented to evaluate the loads and stresses on test facility piping systems from fluid and gaseous effects, thermal chill down, and occasional wind loads. The models are based on Apple Macintosh software which makes it possible to change numerous parameters.

Dequay, L.↗
DOE OSTI2020

Building kinetic models for metabolic engineering

Kinetic formalisms of metabolism link metabolic fluxes to enzyme levels, metabolite concentrations and their allosteric regulatory interactions. Though they require the identification of physiologically relevant values for numerous parameters, kinetic formalisms uniquely establish a mechanistic link across heterogeneous omics datasets and provide an overarching vantage point to effectively inform metabolic engineering strategies. Advances in computational power, gene annotation coverage, and formalism standardization have led to significant progress over the past few years. However, careful interpretation of model predictions, limited metabolic flux datasets, and assessment of parameter sensitivity remain as challenges. In this study we highlight fundamental considerations which influence model quality and prediction, advances in methodologies, and success stories of deploying kinetic models to guide metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Domain and Specification Models for Software Engineering

This paper discusses our approach to representing application domain knowledge for specific software engineering tasks. Application domain knowledge is embodied in a domain model. Domain models are used to assist in the creation of specification models. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model. One aspect of the system-hierarchical organization is described in detail.

Iscoe, Neil↗
NASA NTRS2016

A Structured, Model-Based Systems Engineering Methodology for Operations System Design

Two widely accepted techniques for lowering the cost and risk of developing systems are (1) the use of a defined systems engineering (SE) process or methodology and (2) the reuse of existing (previously built) system components. The first technique is represented, for example, in materials published by NASA (e.g., NASA Systems Engineering Handbook) or by professional societies such as INCOSE (International Council on Systems Engineering). Well-formed SE techniques provide value by establishing the proper scope of the system (e.g., requirements), and by identifying and resolving problems relatively early in project lifecycles, when fixes are less expensive. The second technique (reuse) is applied most commonly to hardware and software; it seeks to avoid replicating design and implementation costs while also reducing risk by placing proven capabilities into operational use. In this paper, we outline a methodology combining these two techniques and extending reuse beyond hardware and software to foundational aspects of a Mission Operation System’s (MOS) design. We describe the system design artifacts that result (e.g., requirements, design documentation), as well as the reusable patterns and elements of the design, and their interrelationships. This approach is enabled by model-based systems engineering (MBSE) techniques and tools and is currently available in SysML form as a plug-in to MagicDraw. Additionally, usage of a rigorous MBSE approach allows for training materials and tutorials to be packaged within the overall model itself. The results of such an approach include decreased cost and risk during the design phase, improved ability of the MOS development team to investigate trade spaces and identify impacts to important flight-ground trade studies. Such results extend into decreased costs and risk in later phases due to improved design, decreased need for late fixes or development of "glue-ware" or scripts to fill unanticipated gaps in functionality, and improved ability to identify and plan testing and other validation activities. Finally, lower operational costs can be expected, both due to improved quality of the MOS, increased ease of maintaining updated knowledge of system configuration, and the fact that training and procedural materials are also updated at the same time as accepted system changes.

Bindschadler, Duane L.↗
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Method for Tracking and Communicating Aggregate Risk Through the Use of Model-Based Systems Engineering (MBSE) Tools

Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.

model based mission assurance↗
NASA NTRS1973

Wind tunnel investigation of a large-scale upper surface blown-flap transport model having two engines

An investigation has been conducted to determine the aerodynamic characteristics of a large-scale subsonic jet transport model with an upper surface blowing flap system that would augment lift. The model had a 25 deg swept wing of aspect ratio 7.89 and two turbofan engines with the engine centerline located at 0.256 of the wing semispan. The lift of the flap system was augmented by turbofan exhaust impingement on the Coanda surface. Results were obtained for several flap deflections and engine nozzle configurations at jet momentum coefficients from 0 to 4.0. Three-component longitudinal data are presented with two engines operating. Limited longitudinal and lateral data are presented with an engine out. In addition, limited exhaust and flap pressure data are presented.

Aoyagi, K.↗
NASA NTRS2011

Enhanced Core Noise Modeling for Turbofan Engines

This report describes work performed by MTC Technologies (MTCT) for NASA Glenn Research Center (GRC) under Contract NAS3-00178, Task Order No. 15. MTCT previously developed a first-generation empirical model that correlates the core/combustion noise of four GE engines, the CF6, CF34, CFM56, and GE90 for General Electric (GE) under Contract No. 200-1X-14W53048, in support of GRC Contract NAS3-01135. MTCT has demonstrated in earlier noise modeling efforts that the improvement of predictive modeling is greatly enhanced by an iterative approach, so in support of NASA's Quiet Aircraft Technology Project, GRC sponsored this effort to improve the model. Since the noise data available for correlation are total engine noise spectra, it is total engine noise that must be predicted. Since the scope of this effort was not sufficient to explore fan and turbine noise, the most meaningful comparisons must be restricted to frequencies below the blade passage frequency. Below the blade passage frequency and at relatively high power settings jet noise is expected to be the dominant source, and comparisons are shown that demonstrate the accuracy of the jet noise model recently developed by MTCT for NASA under Contract NAS3-00178, Task Order No. 10. At lower power settings the core noise became most apparent, and these data corrected for the contribution of jet noise were then used to establish the characteristics of core noise. There is clearly more than one spectral range where core noise is evident, so the spectral approach developed by von Glahn and Krejsa in 1982 wherein four spectral regions overlap, was used in the GE effort. Further analysis indicates that the two higher frequency components, which are often somewhat masked by turbomachinery noise, can be treated as one component, and it is on that basis that the current model is formulated. The frequency scaling relationships are improved and are now based on combustor and core nozzle geometries. In conjunction with the Task Order No. 10 jet noise model, this core noise model is shown to provide statistical accuracy comparable to the jet noise model for frequencies below blade passage. This model is incorporated in the NASA FOOTPR code and a user s guide is provided.

Stone, James R.↗
NASA NTRS1980

Finite element models of the space shuttle main engine

Finite element models were developed as input to dynamic simulations of the high pressure fuel turbopump (HPFTP), the high pressure oxidizer turbopump (HPOTP), and the space shuttle main engine (SSME). Descriptions are provided for the five basic finite element models: HPFTP rotor, HPFTP case, HPOTP rotor, HPOTP case, and SSME (excluding turbopumps). Modal results are presented for the HPFTP rotor, HPFTP case, HPOTP rotor, coupled HPFTP rotor and case, HPOTP case, coupled HPOTP rotor and case, SSME (excluding turbopumps), and SSME (including turbopumps). Results for the SSME (including turbopumps) model are compared to data from a SSME HPOTP modal survey.

Muller, G. R.↗
NASA NTRSDate not supplied

Configuration and Data Management of the NASA Power and Propulsion Element MBSE Model(s)

Systems engineers worldwide have been working to implement Model-Based Systems Engineering (MBSE) environments, tools, and methodologies. A significant, expected benefit from MBSE is a reduction in the time commitment for all aspects of systems engineering. Although advances in MBSE have occurred, a gap has emerged between the traditional configuration management (CM) processes for documents and those needed in an MBSE environment.

MBSE↗
NASA NTRS2005

Computational Model Tracking Primary Electrons, Secondary Electrons, and Ions in the Discharge Chamber of an Ion Engine

Computational modeling of the plasma located in the discharge chamber of an ion engine is an important activity so that the development and design of the next generation of ion engines may be enhanced. In this work a computational tool called XOOPIC is used to model the primary electrons, secondary electrons, and ions inside the discharge chamber. The details of this computational tool are discussed in this paper. Preliminary results from XOOPIC are presented. The results presented include particle number density distributions for the primary electrons, the secondary electrons, and the ions. In addition the total number of a particular particle in the discharge chamber as a function of time, electric potential maps and magnetic field maps are presented. A primary electron number density plot from PRIMA is given in this paper so that the results of XOOPIC can be compared to it. PRIMA is a computer code that the present investigators have used in much of their previous work that provides results that compare well to experimental results. PRIMA only models the primary electrons in the discharge chamber. Modeling ions and secondary electrons, as well as the primary electrons, will greatly increase our ability to predict different characteristics of the plasma discharge used in an ion engine.

Mahalingam, Sudhakar↗