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Results for “Verification and 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.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Validation and Verification of LADEE Models and Software

The Lunar Atmosphere Dust Environment Explorer (LADEE) mission will orbit the moon in order to measure the density, composition and time variability of the lunar dust environment. The ground-side and onboard flight software for the mission is being developed using a Model-Based Software methodology. In this technique, models of the spacecraft and flight software are developed in a graphical dynamics modeling package. Flight Software requirements are prototyped and refined using the simulated models. After the model is shown to work as desired in this simulation framework, C-code software is automatically generated from the models. The generated software is then tested in real time Processor-in-the-Loop and Hardware-in-the-Loop test beds. Travelling Road Show test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models are used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection and code coverage analyses are utilized to further reduce defects in the onboard flight software artifacts. These techniques are applied early and often in the development process, iteratively increasing the capabilities of the software and the fidelity of the vehicle models and test beds.

Gundy-Burlet, Karen↗
NASA NTRS2015

Independent Verification and Validation Program

Presentation to be given to European Space Agency counterparts to give an overview of NASA's IVV Program and the layout and structure of the Software Testing and Research laboratory maintained at IVV. Seeking STI-ITAR review due to the international audience. Most of the information has been presented to public audiences in the past, with some variations on data, or is in the public domain.

Research↗
NASA NTRS2008

Deep Impact Extended Mission Challenges for the Validation and Verification Test Program

The Deep Impact Spacecraft was launched on January 12, 2005 as part of NASA's Discovery Program as a radical mission to excavate the interior of a comet. The Spacecraft consisted of two separate entities known as the Flyby and the Impactor, which were commanded to separate prior to comet rendezvous with comet 9P/Tempel 1. The overall mission was deemed a success on July 4, 2005, as the 370-kg Impactor collided with the comet at 10.2 km/s. This event was captured using the camera and infrared spectrometer on the Flyby spacecraft, along with ground-based observatories. Since this event, the Flyby spacecraft has been in hibernation mode and has received only a small amount of maintenance. The Deep Impact Program was managed by the Jet Propulsion Laboratory (JPL), led by Dr. Michael A'Hearn from the University of Maryland in College Park, and built by Ball Aerospace & Technologies Corp. in Boulder, Colorado.

Test Bench↗
NASA NTRS2015

Verification and Validation of the k-kL Turbulence Model in FUN3D and CFL3D Codes

The implementation of the k-kL turbulence model using multiple computational uid dy- namics (CFD) codes is reported herein. The k-kL model is a two-equation turbulence model based on Abdol-Hamid's closure and Menter's modi cation to Rotta's two-equation model. Rotta shows that a reliable transport equation can be formed from the turbulent length scale L, and the turbulent kinetic energy k. Rotta's equation is well suited for term-by-term mod- eling and displays useful features compared to other two-equation models. An important di erence is that this formulation leads to the inclusion of higher-order velocity derivatives in the source terms of the scale equations. This can enhance the ability of the Reynolds- averaged Navier-Stokes (RANS) solvers to simulate unsteady ows. The present report documents the formulation of the model as implemented in the CFD codes Fun3D and CFL3D. Methodology, veri cation and validation examples are shown. Attached and sepa- rated ow cases are documented and compared with experimental data. The results show generally very good comparisons with canonical and experimental data, as well as matching results code-to-code. The results from this formulation are similar or better than results using the SST turbulence model.

Abdol-Hamid, Khaled S.↗
NASA NTRS2015

Second-Moment RANS Model Verification and Validation Using the Turbulence Modeling Resource Website (Invited)

The implementation of the SSG/LRR-omega differential Reynolds stress model into the NASA flow solvers CFL3D and FUN3D and the DLR flow solver TAU is verified by studying the grid convergence of the solution of three different test cases from the Turbulence Modeling Resource Website. The model's predictive capabilities are assessed based on four basic and four extended validation cases also provided on this website, involving attached and separated boundary layer flows, effects of streamline curvature and secondary flow. Simulation results are compared against experimental data and predictions by the eddy-viscosity models of Spalart-Allmaras (SA) and Menter's Shear Stress Transport (SST).

Eisfeld, Bernhard↗
NASA NTRS2016

Integrated Mecical Model (IMM) 4.0 Verification and Validation (VV) Testing (HRP IWS 2016)

Timeline, partial treatment, and alternate medications were added to the IMM to improve the fidelity of this model to enhance decision support capabilities. Using standard design reference missions, IMM VV testing compared outputs from the current operational IMM (v3) with those from the model with added functionalities (v4). These new capabilities were examined in a comparative, stepwise approach as follows: a) comparison of the current operational IMM v3 with the enhanced functionality of timeline alone (IMM 4.T), b) comparison of IMM 4.T with the timeline and partial treatment (IMM 4.TPT), and c) comparison of IMM 4.TPT with timeline, partial treatment and alternative medication (IMM 4.0).

risk assessment↗
NASA NTRS2019

Adaptations of Guidance, Navigation and Control Verification and Validation Philosophies for Small Spacecraft

Decades of experience developing increasingly capable and more complex space-craft have resulted in a set of accepted practices and philosophies to verify and validate (V&V) guidance, navigation, and control (GN&C) subsystems. Until recently, small, low-cost spacecraft have had very simple or non-existent GN&C subsystems requiring minimal or no subsystem testing. As the next generation of small spacecraft take on more challenging GN&C requirements, the GN&C community is struggling with how to scale the subsystem V&V effort to produce spacecraft approaching the reliability of flagship-class missions while staying within the reduced resources of a small satellite project. For this paper, we will examine five aspects of GN&C V&V (requirements definition, software testing and analysis, hardware component testing, integrated vehicle testing, and in-flight V&V) and compare the V&V campaign of a flagship-class mission (Mars 2020) to that of two recent, successful CubeSat missions: ASTERIA and MarCO. Experiences from the development of these CubeSats yield valuable lessons learned and guidelines for future small spacecraft designers.

Pong, Christopher M.↗
NASA NTRS2020

Design for Manufacturing Tool for Automated Fiber Placement Structures - Verification and Validation

A tool has been developed to address the growing Design for Manufacturing needs for composite structures, specifically those manufactured with automated fiber placement. This manufacturing approach presents unique challenges associated with puckers and wrinkling, tow overlaps and gaps, fiber deviation, and laminate strength. Achieving a satisfactory laminate design usually requires finding compromises between those four areas. The developed tool, dubbed the Central Optimizer, assists with the process of balancing competing design metrics in automated fiber placement. This tool was developed under the NASA Advanced Composites Consortium with input from industry partners. Under this program, the Central Optimizer has been exercised on three different structures to verify its functionality and validate ability to improve the design process for automated fiber placement structures.

August T Noevere↗