Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “VERIFICATION”

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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Model-Based Verification and Validation of Spacecraft Avionics

Our simulation was able to mimic the results of 30 tests on the actual hardware. This shows that simulations have the potential to enable early design validation - well before actual hardware exists. Although simulations focused around data processing procedures at subsystem and device level, they can also be applied to system level analysis to simulate mission scenarios and consumable tracking (e.g. power, propellant, etc.). Simulation engine plug-in developments are continually improving the product, but handling time for time-sensitive operations (like those of the remote engineering unit and bus controller) can be cumbersome.

Systems Modeling Language (SysML↗
NASA NTRS2015

Generation of Library Models for Verification of Android Applications

Android applications are difficult to verify and test since they have many external dependencies. To overcome this problem, environment generation can be used to create a model of the environment to simulate the behavior of these external dependencies. Creating this environment model manually is a tedious process and although there are many techniques available to generate models, the key lies in identifying how these techniques can be applied to a specific domain. In this paper we discuss two static analysis tools OCSEGen and Modgen and how they can be applied to the Android domain to generate models for specific parts of the environment.

Verification↗
NASA NTRS2016

SMAP Instrument Antenna, on Orbit Performance Validation and Verification

NASA’s Soil Moisture Active Passive (SMAP) Mission is currently flying in a 685 km orbit. Featuring a Synthetic Aperture Radar (SAR) and a radiometer sharing the same antenna, SMAP was developed in collaboration between Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). While the radar requirements on the instrument antenna were more benign from an RF point of view, the radiometer requirement were more difficult to meet because of the stability required by the radiometer to operate to its full potential. The instrument antenna performance was predicted by a very detailed RF model and verified by measuring a 1/10th scale model with great accuracy before launch. Once in orbit, we had the opportunity to measure the antenna performance for both the radiometer and the radar and compare it with the predicted performance given by our RF model. This paper discusses the work done both at JPL and GSFC in order to verify and validate the on orbit performance of the SMAP instrument antenna.

reflector antenna↗
NASA NTRS2017

On Orbit Performance Validation and Verification of the SMAP Instrument Antenna

NASA’s Soil Moisture Active Passive (SMAP) Mission is currently flying in a 685 km orbit. Featuring a Synthetic Aperture Radar (SAR) and a radiometer sharing the same antenna, SMAP was developed in collaboration between Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). While the radar requirements on the instrument antenna were more benign from an RF point of view, the radiometer requirement were more difficult to meet because of the stability required by the radiometer to operate to its full potential. The instrument antenna performance was predicted by a very detailed RF model and verified by measuring a 1/10th scale model with great accuracy before launch. Once in orbit, we had the opportunity to measure the antenna performance for both the radiometer and the radar and compare it with the predicted performance given by our RF model. This paper discusses the work done both at JPL and GSFC in order to verify and validate the on orbit performance of the SMAP instrument antenna.

offset reflector↗
NASA NTRSDate not supplied

Reflecting on Planning Models: A Challenge for Verification and Validation of Planning Systems

We discuss the opportunities for autonomous sys- tems to perform reflection on their planners by adapting the models used to build plans. We first describe model-based planning systems, a form of automated planning system driven by declarative models of the planning domain. These models include descriptions of the conditions and effects of actions on the state of the world. When planning the activities of cyber-physical systems, the command and data representation of the system must be formally abstracted to the actions and states described in the planning system model. When the execution of a plan either fails or produces unexpected outcomes, the execution trace can be abstracted and compared to the predicted state according to the planning model, producing a list of discrepancies; these discrepancies can then be used to fix the model. This provides part of a reflection capability, namely, a set of well-formed problems with the domain model, the abstractions, or both. The challenge lies in the rest of the reflection capability, namely, a set of techniques for changing the models or the abstractions. We discuss these challenges and describe some of the options for addressing them

Mission Planning↗
NASA NTRSDate not supplied

Runtime Verification

Explore the source record for details and available documents.

Runtime Verification↗
NASA NTRS2021

MBSE Validation and Verification: Case Study for LADEE

The Lunar Atmosphere Dust Environment Explorer (LADEE) mission orbited the moon in order to measure the density, composition, and time variability of the lunar dust environment. The successful mission launched September 7, 2013 and was de-orbited and impacted the moon's surface on April 17, 2014. The ground-side and onboard flight software for the mission was developed using a “Model-Based Software Engineering” (MBSE) methodology combined with strong reuse of Government and Commercial Off-The Shelf (G/COTS) components. Models of the spacecraft and flight software were developed in a graphical dynamics modeling package. Flight Software requirements were prototyped and refined using the simulated models. After the model was shown to work as desired in the simulation framework, C-code software was automatically generated from the models. The auto-generated software was then tested in real-time Processor-in-the-Loop and Hardware-in-the-Loop test beds. “Traveling Road Show” test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models were used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection, and code coverage analyses were utilized to further reduce defects in the onboard flight software artifacts. These techniques were applied early and often in the development process, iteratively increasing the capabilities of software and fidelity of vehicle models and test beds.

Model-Based Software Engineering, Validation and V↗