Results for “Engineering Model” — Page 43

NASA NTRS1992

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Moore, N. R.↗

NASA NTRS1992

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Moore, N. R.↗

NASA NTRS2007

Bootstrap data methodology for sequential hybrid model building

A method for modeling engine operation comprising the steps of: 1. collecting a first plurality of sensory data, 2. partitioning a flight envelope into a plurality of sub-regions, 3. assigning the first plurality of sensory data into the plurality of sub-regions, 4. generating an empirical model of at least one of the plurality of sub-regions, 5. generating a statistical summary model for at least one of the plurality of sub-regions, 6. collecting an additional plurality of sensory data, 7. partitioning the second plurality of sensory data into the plurality of sub-regions, 8. generating a plurality of pseudo-data using the empirical model, and 9. concatenating the plurality of pseudo-data and the additional plurality of sensory data to generate an updated empirical model and an updated statistical summary model for at least one of the plurality of sub-regions.

Volponi, Allan J.↗

NASA NTRS2008

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of an Enhanced System

In this paper, an enhanced on-line diagnostic system which utilizes dual-channel sensor measurements is developed for the aircraft engine application. The enhanced system is composed of a nonlinear on-board engine model (NOBEM), the hybrid Kalman filter (HKF) algorithm, and fault detection and isolation (FDI) logic. The NOBEM provides the analytical third channel against which the dual-channel measurements are compared. The NOBEM is further utilized as part of the HKF algorithm which estimates measured engine parameters. Engine parameters obtained from the dual-channel measurements, the NOBEM, and the HKF are compared against each other. When the discrepancy among the signals exceeds a tolerance level, the FDI logic determines the cause of discrepancy. Through this approach, the enhanced system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the enhanced system is evaluated in a simulation environment using faults in sensors and components, and it is compared to an existing baseline system.

Kobayashi, Takahisa↗

NASA NTRS2024

The NASA Orbital Debris Program Office - In Service of Space Safety

Since the NASA Orbital Debris Program Office’s (ODPO) founding in 1979 at the Johnson Space Center in Houston, Texas, it has been at the forefront of orbital debris research, modeling, and policy development. The ODPO has worked in collaboration with NASA and other U.S. government missions since the 1980s to mitigate the growth of the orbital debris environment and protect the population of the Earth. Two main products from the ODPO, the Orbital Debris Engineering Model (ORDEM) and the Debris Assessment Software (DAS), are frequently among the top three most-downloaded software packages from the NASA Software Catalog. These products are provided free of charge to the public in furtherance of the goal to ensure that new space missions, in compliance with NASA’s orbital debris mitigation requirements, are developed, operated, and disposed of responsibly. In addition to these external-facing software tools, the ODPO maintains high-fidelity internal tools for reentry simulation (the Object Reentry Survival Analysis Tool, ORSAT), short-term risk assessment for robotic and human spaceflight missions (the Satellite Breakup Risk Assessment Module, SBRAM), among others. Using data from the ORDEM model, as well as using the Meteoroid Environment Model (MEM) developed by the Meteoroid Environment Office (MEO) at NASA’s Marshall Space Flight Center, the Hypervelocity Impact Technology (HVIT) team uses the BUMPER code to assess penetration risk to space vehicles in Earth orbit and beyond. This paper will discuss the services that the ODPO and HVIT provide, from mission concept development through end-of-mission, for NASA-related and commercial missions.

Chris Ostrom↗

NASA NTRS1979

A marching method for calculating line and continuum radiation in high energy flow fields

A method is presented for calculating nongrey radiative fluxes and intensities in a highly ionized, low temperature plasma with extreme line broadening. The method was developed to study radiative heating phenomena in the mass-injected hypersonic shock-layer environments characteristic of outer planet atmospheric entry, although it is not limited to such studies. The radiative properties model assumed local thermodynamic equilibrium and used standard continuum and molecular band models. The atomic line model, however, used a frequency-marching method for the frequency integration, which not only accounted completely for line overlapping (reabsorption) effects, but compared favorably in economy with the best equivalent-width methods. An assessment of hydrogen line-far-wing treatments, with recommendations for engineering models, is also presented.

Bolz, C. W., Jr.↗

NASA NTRS2008

Integrated Testing Approaches for the NASA Ares I Crew Launch Vehicle

The Ares I crew launch vehicle is being developed by the U.S. National Aeronautics and Space Administration (NASA) to provide crew and cargo access to the International Space Station (ISS) and, together with the Ares V cargo launch vehicle, serves as a critical component of NASA's future human exploration of the Moon. During the preliminary design phase, NASA defined and began implementing plans for integrated ground and flight testing necessary to achieve the first human launch of Ares I. The individual Ares I flight hardware elements - including the first stage five segment booster (FSB), upper stage, and J-2X upper stage engine - will undergo extensive development, qualification, and certification testing prior to flight. Key integrated system tests include the upper stage Main Propulsion Test Article (MPTA), acceptance tests of the integrated upper stage and upper stage engine assembly, a full-scale integrated vehicle ground vibration test (IVGVT), aerodynamic testing to characterize vehicle performance, and integrated testing of the avionics and software components. The Ares I-X development flight test will provide flight data to validate engineering models for aerodynamic performance, stage separation, structural dynamic performance, and control system functionality. The Ares I-Y flight test will validate ascent performance of the first stage, stage separation functionality, validate the ability of the upper stage to manage cryogenic propellants to achieve upper stage engine start conditions, and a high-altitude demonstration of the launch abort system (LAS) following stage separation. The Orion 1 flight test will be conducted as a full, un-crewed, operational flight test through the entire ascent flight profile prior to the first crewed launch.

Taylor, James L.↗

NASA NTRS2014

Development of a Twin-spool Turbofan Engine Simulation Using the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3 of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

thermodynamic simulation↗

NASA NTRS1982

A microprocessor application in the MTV telemetry data processor

An engineering model of the Telemetry Data Processor monitoring and display system used by the Maneuverable Television (MTV) employed in remote inspections of the Space Shuttle has been developed, incorporating the MC 6809 microprocessor. The system acquires analog and digital signals from the MTV flyer and converts them into engineering units, formatting them in several pages according to their function. Upon request, a data page can be superimposed on the video signal from the MTV camera. In addition, the system monitors key parameters for out-of-limit conditions and flashes caution and warning messages on the selected page.

Spahn, C. J.↗

NASA NTRS2011

Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems

A technique based on Evolutionary Computational Methods (ECMs) was developed that allows for the automated optimization of complex computationally modeled systems, such as autonomous systems. The primary technology, which enables the ECM to find optimal solutions in complex search spaces, derives from evolutionary algorithms such as the genetic algorithm and differential evolution. These methods are based on biological processes, particularly genetics, and define an iterative process that evolves parameter sets into an optimum. Evolutionary computation is a method that operates on a population of existing computational-based engineering models (or simulators) and competes them using biologically inspired genetic operators on large parallel cluster computers. The result is the ability to automatically find design optimizations and trades, and thereby greatly amplify the role of the system engineer.

Terrile, Richard J.↗

NASA NTRS2013

Applying Model Based Systems Engineering to NASA's Space Communications Networks

System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.

Bhasin, Kul↗

NASA NTRS1986

Mathematical model partitioning and packing for parallel computer calculation

This paper deals with the development of multiprocessor simulations from a serial set of ordinary differential equations describing a physical system. The identification of computational parallelism within the model equations is discussed. A technique is presented for identifying this parallelism and for partitioning the equations for parallel solution on a multiprocessor. Next, an algorithm which packs the equations into a minimum number of processors is described. The results of applying the packing algorithm to a turboshaft engine model are presented.

Arpasi, Dale J.↗

NASA NTRS1988

Thermal Response Of Composite Insulation

Engineering model gives useful predictions. Pair of reports presents theoretical and experimental analyses of thermal responses of multiple-component, lightweight, porous, ceramic insulators. Particular materials examined destined for use in Space Shuttle thermal protection system, test methods and heat-transfer theory useful to chemical, metallurgical, and ceramic engineers needing to calculate transient thermal responses of refractory composites.

Stewart, David A.↗

NASA NTRS1991

Design and fabrication of an autonomous rendezvous and docking sensor using off-the-shelf hardware

NASA Marshall Space Flight Center (MSFC) has developed and tested an engineering model of an automated rendezvous and docking sensor system composed of a video camera ringed with laser diodes at two wavelengths and a standard remote manipulator system target that has been modified with retro-reflective tape and 830 and 780 mm optical filters. TRW has provided additional engineering analysis, design, and manufacturing support, resulting in a robust, low cost, automated rendezvous and docking sensor design. We have addressed the issue of space qualification using off-the-shelf hardware components. We have also addressed the performance problems of increased signal to noise ratio, increased range, increased frame rate, graceful degradation through component redundancy, and improved range calibration. Next year, we will build a breadboard of this sensor. The phenomenology of the background scene of a target vehicle as viewed against earth and space backgrounds under various lighting conditions will be simulated using the TRW Dynamic Scene Generator Facility (DSGF). Solar illumination angles of the target vehicle and candidate docking target ranging from eclipse to full sun will be explored. The sensor will be transportable for testing at the MSFC Flight Robotics Laboratory (EB24) using the Dynamic Overhead Telerobotic Simulator (DOTS).

Grimm, Gary E.↗

NASA NTRSDate not supplied

Effect of Engine Thrust and Isp Tradeoffs and Alternate Propellants on ΔV Budget and Architecture Mass for 1st Generation Nuclear Thermal Propulsion Flight Test Systems

Following the first Nuclear Thermal Propulsion (NTP) system test, also known as DRACO, the next NTP system to be developed would be the 1st Generation NTP system. An analysis was conducted to determine the performance of different vehicle configurations utilizing hydrogen (H-NTP), ammonia (A-NTP), and methane (M-NTP) as propellants launched onboard commercial launch vehicles. This was enabled by a quasi-steady-state power balance engine model and vehicle component physics that sized the vehicle system using Master Equipment List (MEL) parameters. The analysis considered configuration cases outlined by a matrix of different mission classes and vehicle configurations that covered the design space of the 1st Generation NTP system to explore various propellant options, engine architectures, and mission scopes. Four mission classes were evaluated which included single burn missions performing maneuvers having a ΔV of 1 km/s and 2.5 km/s followed by 2-burn and 4-burn missions that aimed to exhaust the launch vehicles volume or mass limitations. In all cases, the NTP systems with the lowest thrust class had the longest burn time of which A-NTP and M-NTP systems provided the longest and shortest burn times depending on the launch vehicle used while H-NTP systems tended to cluster together in the middle. Longer burn times could be useful as a testing platform to increase the time for data accumulation. Across the multi-burn cases, H-NTP systems were found to be volume limited while A-NTP and M-NTP systems were mass limited. Both single burn missions showed that A-NTP configurations provided the lowest dry mass given that ammonia had the highest density with comparable performance to M-NTP systems and no requirement for cryocoolers. The results showed that beyond the propellant selection type, the launch vehicle selection, which included Starship, New Glenn, Vulcan, Falcon 9 (recoverable), and Falcon Heavy (recoverable), was a primary driving factor in the test vehicle’s capabilities. Trends were determined based on a set of dimensionless parameters that included the mass ratio of inert mass to initial wetted mass, ratio of specific impulse to burn time, and a dimensionless engine parameter (ratio of impulse to engine momentum). These relationships found the “knees-in-the-curves” that could be a significant point of reference for the designer as they indicate a change in the trend which is located at a specific impulse to burn time ratio of 1, a mass ratio of 0.6, and an engine performance parameter of 4. This study did not attempt to make a recommendation rather provide the tools for the reader to select their own configuration based on their needs.

Propellant↗

NASA NTRSDate not supplied

Effect of Engine Thrust and Isp Tradeoffs and Alternate Propellants on ΔV Budget and Architecture Mass for 1st Generation Nuclear Thermal Propulsion Flight Test Systems

Following the first Nuclear Thermal Propulsion (NTP) system test, also known as DRACO, the next NTP system to be developed would be the 1st Generation NTP system. An analysis was conducted to determine the performance of different vehicle configurations utilizing hydrogen (H-NTP), ammonia (A-NTP), and methane (M-NTP) as propellants launched onboard commercial launch vehicles. This was enabled by a quasi-steady-state power balance engine model and vehicle component physics that sized the vehicle system using Master Equipment List (MEL) parameters. The analysis considered configuration cases outlined by a matrix of different mission classes and vehicle configurations that covered the design space of the 1st Generation NTP system to explore various propellant options, engine architectures, and mission scopes. Four mission classes were evaluated which included single burn missions performing maneuvers having a ΔV of 1 km/s and 2.5 km/s followed by 2-burn and 4-burn missions that aimed to exhaust the launch vehicles volume or mass limitations. In all cases, the NTP systems with the lowest thrust class had the longest burn time of which A-NTP and M-NTP systems provided the longest and shortest burn times depending on the launch vehicle used while H-NTP systems tended to cluster together in the middle. Longer burn times could be useful as a testing platform to increase the time for data accumulation. Across the multi-burn cases, H-NTP systems were found to be volume limited while A-NTP and M-NTP systems were mass limited. Both single burn missions showed that A-NTP configurations provided the lowest dry mass given that ammonia had the highest density with comparable performance to M-NTP systems and no requirement for cryocoolers. The results showed that beyond the propellant selection type, the launch vehicle selection, which included Starship, New Glenn, Vulcan, Falcon 9 (recoverable), and Falcon Heavy (recoverable), was a primary driving factor in the test vehicle’s capabilities. Trends were determined based on a set of dimensionless parameters that included the mass ratio of inert mass to initial wetted mass, ratio of specific impulse to burn time, and a dimensionless engine parameter (ratio of impulse to engine momentum). These relationships found the “knees-in-the-curves” that could be a significant point of reference for the designer as they indicate a change in the trend which is located at a specific impulse to burn time ratio of 1, a mass ratio of 0.6, and an engine performance parameter of 4. This study did not attempt to make a recommendation rather provide the tools for the reader to select their own configuration based on their needs.

Propellant↗

NASA NTRSDate not supplied

Effect of Engine Thrust and Isp Tradeoffs and Alternate Propellants on ΔV Budget and Architecture Mass for 1st Generation Nuclear Thermal Propulsion Flight Test Systems

Following the first Nuclear Thermal Propulsion (NTP) system test, also known as DRACO, the next NTP system to be developed would be the 1st Generation NTP system. An analysis was conducted to determine the performance of different vehicle configurations utilizing hydrogen (H-NTP), ammonia (A-NTP), and methane (M-NTP) as propellants launched onboard commercial launch vehicles. This was enabled by a quasi-steady-state power balance engine model and vehicle component physics that sized the vehicle system using Master Equipment List (MEL) parameters. The analysis considered configuration cases outlined by a matrix of different mission classes and vehicle configurations that covered the design space of the 1st Generation NTP system to explore various propellant options, engine architectures, and mission scopes. Four mission classes were evaluated which included single burn missions performing maneuvers having a ΔV of 1 km/s and 2.5 km/s followed by 2-burn and 4-burn missions that aimed to exhaust the launch vehicles volume or mass limitations. In all cases, the NTP systems with the lowest thrust class had the longest burn time of which A-NTP and M-NTP systems provided the longest and shortest burn times depending on the launch vehicle used while H-NTP systems tended to cluster together in the middle. Longer burn times could be useful as a testing platform to increase the time for data accumulation. Across the multi-burn cases, H-NTP systems were found to be volume limited while A-NTP and M-NTP systems were mass limited. Both single burn missions showed that A-NTP configurations provided the lowest dry mass given that ammonia had the highest density with comparable performance to M-NTP systems and no requirement for cryocoolers. The results showed that beyond the propellant selection type, the launch vehicle selection, which included Starship, New Glenn, Vulcan, Falcon 9 (recoverable), and Falcon Heavy (recoverable), was a primary driving factor in the test vehicle’s capabilities. Trends were determined based on a set of dimensionless parameters that included the mass ratio of inert mass to initial wetted mass, ratio of specific impulse to burn time, and a dimensionless engine parameter (ratio of impulse to engine momentum). These relationships found the “knees-in-the-curves” that could be a significant point of reference for the designer as they indicate a change in the trend which is located at a specific impulse to burn time ratio of 1, a mass ratio of 0.6, and an engine performance parameter of 4. This study did not attempt to make a recommendation rather provide the tools for the reader to select their own configuration based on their needs.

Propellant↗

NASA NTRS2016

Integration Tests of the 4 kW-Class High Voltage Hall Accelerator Power Processing Unit with the HiVHAc and the SPT-140 Hall Effect Thrusters

NASA's Science Mission Directorate is sponsoring the development of a 4 kW-class Hall propulsion system for implementation in NASA science and exploration missions. The main components of the system include the High Voltage Hall Accelerator (HiVHAc), an engineering model power processing unit (PPU) developed by Colorado Power Electronics, and a xenon flow control module (XFCM) developed by VACCO Industries. NASA Glenn Research Center is performing integrated tests of the Hall thruster propulsion system. This paper presents results from integrated tests of the PPU and XFCM with the HiVHAc engineering development thruster and a SPT-140 thruster provided by Space System Loral. The results presented in this paper demonstrate thruster discharge initiation along with open-loop and closed-loop control of the discharge current with anode flow for both the HiVHAc and the SPT-140 thrusters. Integrated tests with the SPT-140 thruster indicated that the PPU was able to repeatedly initiate the thruster's discharge, achieve steady state operation, and successfully throttle the thruster between 1.5 and 4.5 kW. The measured SPT-140 performance was identical to levels reported by Space Systems Loral.

Power Processing Unit↗