Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “VALIDATION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Pratt & Whitney/Boeing Engine Validation of Noise Reduction Concepts Final Report for NASA Contract NAS3-97144, Phase 2

This report presents results of the work completed in Phase 2 of the Engine Validation of Noise Reduction Concepts (EVNRC) contract. The purpose of the program is to validate, through engine testing, advanced noise reduction concepts aimed at reducing engine noise up to 6 EPNdB and improving nacelle suppression by 50 percent relative to 1992 technology. Phase 1 of the program is completed and is summarized in NASA/CR-2014-218088.

Bock, Larry A.↗
NASA NTRS2014

UAS-Systems Integration, Validation, and Diagnostics Simulation Capability

As part of the Phase 1 efforts of NASA's UAS-in-the-NAS Project a task was initiated to explore the merits of developing a system simulation capability for UAS to address airworthiness certification requirements. The core of the capability would be a software representation of an unmanned vehicle, including all of the relevant avionics and flight control system components. The specific system elements could be replaced with hardware representations to provide Hardware-in-the-Loop (HWITL) test and evaluation capability. The UAS Systems Integration and Validation Laboratory (UAS-SIVL) was created to provide a UAS-systems integration, validation, and diagnostics hardware-in-the-loop simulation capability. This paper discusses how SIVL provides a robust and flexible simulation framework that permits the study of failure modes, effects, propagation paths, criticality, and mitigation strategies to help develop safety, reliability, and design data that can assist with the development of certification standards, means of compliance, and design best practices for civil UAS.

Buttrill, Catherine W.↗
NASA NTRS2014

A Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources

The NASA Glenn Research Center's Advanced Noise Control Fan (ANCF) was developed in the early 1990s to provide a convenient test bed to measure and understand fan-generated acoustics, duct propagation, and radiation to the farfield. A series of tests were performed primarily for the use of code validation and tool validation. Rotating Rake mode measurements were acquired for parametric sets of: (i) mode blockage, (ii) liner insertion loss, (iii) short ducts, and (iv) mode reflection.

Sutliff, Daniel L.↗
NASA NTRS2014

GCR Environmental Models III: GCR Model Validation and Propagated Uncertainties in Effective Dose

This is the last of three papers focused on quantifying the uncertainty associated with galactic cosmic rays (GCR) models used for space radiation shielding applications. In the first paper, it was found that GCR ions with Z>2 and boundary energy below 500 MeV/nucleon induce less than 5% of the total effective dose behind shielding. This is an important finding since GCR model development and validation have been heavily biased toward Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer measurements below 500 MeV/nucleon. Weights were also developed that quantify the relative contribution of defined GCR energy and charge groups to effective dose behind shielding. In the second paper, it was shown that these weights could be used to efficiently propagate GCR model uncertainties into effective dose behind shielding. In this work, uncertainties are quantified for a few commonly used GCR models. A validation metric is developed that accounts for measurements uncertainty, and the metric is coupled to the fast uncertainty propagation method. For this work, the Badhwar-O'Neill (BON) 2010 and 2011 and the Matthia GCR models are compared to an extensive measurement database. It is shown that BON2011 systematically overestimates heavy ion fluxes in the range 0.5-4 GeV/nucleon. The BON2010 and BON2011 also show moderate and large errors in reproducing past solar activity near the 2000 solar maximum and 2010 solar minimum. It is found that all three models induce relative errors in effective dose in the interval [-20%, 20%] at a 68% confidence level. The BON2010 and Matthia models are found to have similar overall uncertainty estimates and are preferred for space radiation shielding applications.

Slaba, Tony C.↗
NASA NTRS2013

KINEROS2-AGWA: Model Use, Calibration, and Validation

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

Erosion↗
NASA NTRS2012

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

pilot error↗
NASA NTRS2012

Bioculture System Validation

The Bioculture System first flight will be to validate the performance of the hardware and its automated and manual operational capabilities in the space flight environment of the International Space Station. Biology, Engineering, and Operations tests will be conducted in the Bioculture System fully characterize its automated and manual functions to support cell culturing for short and long durations. No hypothesis-driven research will be conducted with biological sample, and the science leads have all provided their concurrence that none of the data they collect will be considered as proprietary and can be free distributed to the science community. The outcome of the validation flight will be to commission the hardware for use by the science community. This presentation will provide non-proprietary details about the Bioculture System and information about the activities for the first flight.

Bioculture↗
NASA NTRS2014

Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.

Pei, Jing↗
NASA NTRS2015

V-SUIT Model Validation Using PLSS 1.0 Test Results

The dynamic portable life support system (PLSS) simulation software Virtual Space Suit (V-SUIT) has been under development at the Technische Universitat Munchen since 2011 as a spin-off from the Virtual Habitat (V-HAB) project. The MATLAB(trademark)-based V-SUIT simulates space suit portable life support systems and their interaction with a detailed and also dynamic human model, as well as the dynamic external environment of a space suit moving on a planetary surface. To demonstrate the feasibility of a large, system level simulation like V-SUIT, a model of NASA's PLSS 1.0 prototype was created. This prototype was run through an extensive series of tests in 2011. Since the test setup was heavily instrumented, it produced a wealth of data making it ideal for model validation. The implemented model includes all components of the PLSS in both the ventilation and thermal loops. The major components are modeled in greater detail, while smaller and ancillary components are low fidelity black box models. The major components include the Rapid Cycle Amine (RCA) CO2 removal system, the Primary and Secondary Oxygen Assembly (POS/SOA), the Pressure Garment System Volume Simulator (PGSVS), the Human Metabolic Simulator (HMS), the heat exchanger between the ventilation and thermal loops, the Space Suit Water Membrane Evaporator (SWME) and finally the Liquid Cooling Garment Simulator (LCGS). Using the created model, dynamic simulations were performed using same test points also used during PLSS 1.0 testing. The results of the simulation were then compared to the test data with special focus on absolute values during the steady state phases and dynamic behavior during the transition between test points. Quantified simulation results are presented that demonstrate which areas of the V-SUIT model are in need of further refinement and those that are sufficiently close to the test results. Finally, lessons learned from the modelling and validation process are given in combination with implications for the future development of other PLSS models in V-SUIT.

Olthoff, Claas↗
NASA NTRS2014

Using Lunar Observations to Validate Pointing Accuracy and Geolocation, Detector Sensitivity Stability and Static Point Response of the CERES Instruments

Validation of in-orbit instrument performance is a function of stability in both instrument and calibration source. This paper describes a method using lunar observations scanning near full moon by the Clouds and Earth Radiant Energy System (CERES) instruments. The Moon offers an external source whose signal variance is predictable and non-degrading. From 2006 to present, these in-orbit observations have become standardized and compiled for the Flight Models -1 and -2 aboard the Terra satellite, for Flight Models-3 and -4 aboard the Aqua satellite, and beginning 2012, for Flight Model-5 aboard Suomi-NPP. Instrument performance measurements studied are detector sensitivity stability, pointing accuracy and static detector point response function. This validation method also shows trends per CERES data channel of 0.8% per decade or less for Flight Models 1-4. Using instrument gimbal data and computed lunar position, the pointing error of each detector telescope, the accuracy and consistency of the alignment between the detectors can be determined. The maximum pointing error was 0.2 Deg. in azimuth and 0.17 Deg. in elevation which corresponds to an error in geolocation near nadir of 2.09 km. With the exception of one detector, all instruments were found to have consistent detector alignment from 2006 to present. All alignment error was within 0.1o with most detector telescopes showing a consistent alignment offset of less than 0.02 Deg.

Daniels, Janet L.↗
NASA NTRS2014

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administrations (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAAs mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation’s economy and protection of lives and property. The National Aerospace and Atmospheric Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Data Processing↗
NASA NTRS2014

Veggie Hardware Validation Test Preliminary Results and Lessons Learned

The Veggie hardware validation test, VEG-01, was conducted on the International Space Station during Expeditions 39 and 40 from May through June of 2014. The Veggie hardware and the VEG-01 experiment payload were launched to station aboard the SpaceX-3 resupply mission in April, 2014. Veggie was installed in an Expedite-the-Processing-of-Experiments-to-Space-Station (ExPRESS) rack in the Columbus module, and the VEG-01 validation test was initiated. Veggie installation was successful, and power was supplied to the unit. The hardware was programmed and the root mat reservoir and plant pillows were installed without issue. As expected, a small amount of growth media was observed in the sealed bags which enclosed the plant pillows when they were destowed. Astronaut Steve Swanson used the wet/dry vacuum to clean up the escaped particles. Water insertion or priming the first plant pillow was unsuccessful as an issue prevented water movement through the quick disconnect. All subsequent pillows were successfully primed, and the initial pillow was replaced with a backup pillow and successfully primed. Six pillows were primed, but only five pillows had plants which germinated. After about a week and a half it was observed that plants were not growing well and that pillow wicks were dry. This indicated that the reservoir was not supplying sufficient water to the pillows via wicking, and so the team reverted to an operational fix which added water directly to the plant pillows. Direct watering of the pillows led to a recovery in several of the stressed plants; a couple of which did not recover. An important lesson learned involved Veggie's bellows. The bellows tended to float and interfere with operations when opened, so Steve secured them to the baseplate during plant tending operations. Due to the perceived intensity of the LED lights, the crew found it challenging to both work under the lights and read crew procedures on their computer. Although the lights are not a safety hazard, for visual comfort crewmembers were advised to wear sunglasses when working with the plants and then they can lift glasses to read procedures. Steve Swanson had already trail-blazed this procedure when he initiated VEG-01. The temperature and humidity data logger was relocated mid-experiment to provide measurements on both sides of the unit. Images of the plants were downlinked weekly, and videos of installation and harvest were recorded. This imaging frequency was not sufficient to monitor and respond to changes in plant growth. Plants, samples, and data loggers will be returned on SpaceX-4, scheduled to return the fall of 2014. Lessons learned will be translated into hardware and operational modifications for future Veggie payloads.

International Space Station↗
NASA NTRS2015

Validation of an Integrated Airframe and Turbofan Engine Simulation for Evaluation of Propulsion Control Modes

The National Aeronautics and Space Administration (NASA) has developed independent airframe and engine models that have been integrated into a single real-time aircraft simulation for piloted evaluation of propulsion control algorithms. In order to have confidence in the results of these evaluations, the integrated simulation must be validated to demonstrate that its behavior is realistic and that it meets the appropriate Federal Aviation Administration (FAA) certification requirements for aircraft. The paper describes the test procedures and results, demonstrating that the integrated simulation generally meets the FAA requirements and is thus a valid testbed for evaluation of propulsion control modes.

aircraft engine simulation↗
NASA NTRS2013

Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

Model-based Systems Engineering (MBSE)↗
NASA NTRS2015

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗
NASA NTRS2014

A Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources

The NASA Glenn Research Center's Advanced Noise Control Fan (ANCF) was developed in the early 1990s to provide a convenient test bed to measure and understand fan-generated acoustics, duct propagation, and radiation to the farfield. A series of tests were performed primarily for the use of code validation and tool validation. Rotating Rake mode measurements were acquired for parametric sets of: (1) mode blockage, (2) liner insertion loss, (3) short ducts, and (4) mode reflection.

Sutliff, Daniel L.↗
NASA NTRS2013

Rigging Test Bed Development for Validation of Multi-Stage Decelerator Extractions

The Low Density Supersonic Decelerator project is developing new decelerator systems for Mars entry which would include testing with a Supersonic Flight Dynamics Test Vehicle. One of the decelerator systems being developed is a large supersonic ringsail parachute. Due to the configuration of the vehicle it is not possible to deploy the parachute with a mortar which would be the preferred method for a spacecraft in a supersonic flow. Alternatively, a multi-stage extraction process using a ballute as a pilot is being developed for the test vehicle. The Rigging Test Bed is a test venue being constructed to perform verification and validation of this extraction process. The test bed consists of a long pneumatic piston device capable of providing a constant force simulating the ballute drag force during the extraction events. The extraction tests will take place both inside a high-bay for frequent tests of individual extraction stages and outdoors using a mobile hydraulic crane for complete deployment tests from initial pack pull out to canopy extraction. These tests will measure line tensions and use photogrammetry to track motion of the elements involved. The resulting data will be used to verify packing and rigging as well, as validate models and identify potential failure modes in order to finalize the design of the extraction system.

Low Density Supersonic Decelerator (LDSD)↗
NASA NTRS2009

Disruption Tolerant Networking Flight Validation Experiment on NASA's EPOXI Mission

In October and November of 2008, the Jet Propulsion Laboratory installed and tested essential elements of Delay/Disruption Tolerant Networking (DTN) technology on the Deep Impact spacecraft. This experiment, called Deep Impact Network Experiment (DINET), was performed in close cooperation with the EPOXI project which has responsibility for the spacecraft. During DINET some 300 images were transmitted from the JPL nodes to the spacecraft. Then they were automatically forwarded from the spacecraft back to the JPL nodes, exercising DTN's bundle origination, transmission, acquisition, dynamic route computation, congestion control, prioritization, custody transfer, and automatic retransmission procedures, both on the spacecraft and on the ground, over a period of 27 days. All transmitted bundles were successfully received, without corruption. The DINET experiment demonstrated DTN readiness for operational use in space missions. This activity was part of a larger NASA space DTN development program to mature DTN to flight readiness for a wide variety of mission types by the end of 2011. This paper describes the DTN protocols, the flight demo implementation, validation metrics which were created for the experiment, and validation results.

DTN↗