An Autonomy Software Testbed Simulation for Ocean Worlds Missions
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Damiana Catanoso↗
SEARCH · Engineering Papers
Results for “software: simulations”
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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An Innovative Approach to Modeling VIPER Rover Software Life Cycle Cost
NASA’s “Volatiles Investigating Polar Exploration Rover” (VIPER) will be the first robotic mission to prospect for water ice near the south pole of the Moon in late 2023 on a 100-Earth-day mission. The information that the VIPER rover provides will help improve understanding of the composition, distribution, and accessibility of Lunar polar volatiles and will help determine how the Moon’s resources can support future human space exploration. VIPER, however, represents a radical departure from the way that NASA has traditionally developed planetary robotic missions. A key consequence of these differences is that estimating the cost of VIPER’s rover software is challenging and complex.For example, VIPER is being developed using management procedures typically applied to NASA research and technology projects, rather than space flight programs. In addition, key portions of the rover’s software are being designed as ground software to run on mission control computers (rather than on-board the rover as flight software as with prior planetary missions) taking advantage of continuous, interactive data communications between the Moon and Earth and higher performance computing available on the ground. Moreover, the rover’s software is being engineered using Agile software development practices and incorporates a significant amount of open-source, rather than following traditional (spiral, waterfall, etc.) development methods and in-house code. In this paper, we present an innovative process to estimate the life cycle cost of VIPER’s rover software. We first describe how we modeled the architecture and code counts for three software elements: Rover Flight Software (RFSW), Rover Ground Software (RGSW), and Rover Simulation Software (RSIM). We then discuss key challenges and unique aspects of our approach, such as the lack of Lunar rover analogies, the need to integrate and test large open source software, and the strategies developed to account for use of non-space flight management practices and the impact of the COVID-19 pandemic. We conclude with a summary of our results, including cumulative distribution, nearest neighbors and cluster analysis, as well as heuristics used to confirm the reasonableness of the cost estimate.
Utz, Hans↗
Results from the Radio Frequency Mass Gauge Technology Demonstration on the Intuitive Machines Nova-C Lunar Lander
A cryogenic propellant mass gauge known as the Radio Frequency Mass Gauge (RFMG) was integrated into the Intuitive Machines (IM) Nova-C lunar lander and provided an estimate of the liquid oxygen and liquid methane mass in the lander propellant tanks throughout the IM-1 mission, including during microgravity coast phases. An RFMG electronics controller was used to measure and record the spectrum of the RF signal reflected from an antenna sensor in each tank over the frequency range 100 to 1,300 MHz. The RF spectrum of each of the tanks is unique and is sensitive to the index of refraction of the propellants and the spatial distribution of the liquid within the tanks. Electromagnetic simulation software was used to simulate the antenna response spectra for a given tank geometry, fluid properties, and liquid–vapor configurations within the tank. Over 10,000 antenna response simulations were completed for each propellant tank prior to the IM-1 mission and represented various volumetric fill levels and fluid configurations. The simulated spectra served as a database against which measured tank spectra were compared. For analysis, a spectral matching algorithm was used to find the best match between measured and simulated spectra, and the gauged mass was calculated from the most highly correlated fluid mass simulations. RFMG measurements were recorded during tank loading on the launch pad and during translunar coast, lunar orbit insertion, low lunar orbit, powered descent to the lunar surface, and postlanding on the Moon. This paper describes the RF and fluid simulations, the RFMG measurements and analysis of spectral data, the RFMG instrument, and the gauged results throughout all phases of the IM-1 mission.
lunar lander↗
Results from the Radio Frequency Mass Gauge Technology Demonstration on the Intuitive Machines Nova-C Lunar Lander
A cryogenic propellant mass gauge known as the Radio Frequency Mass Gauge (RFMG) was integrated into the Intuitive Machines (IM) Nova-C lunar lander and provided an estimate of the liquid oxygen and liquid methane mass in the lander propellant tanks throughout the IM-1 mission, including during microgravity coast phases. An RFMG electronics controller was used to measure and record the spectrum of the RF signal reflected from an antenna sensor in each tank over the frequency range 100 to 1,300 MHz. The RF spectrum of each of the tanks is unique and is sensitive to the index of refraction of the propellants and the spatial distribution of the liquid within the tanks. Electromagnetic simulation software was used to simulate the antenna response spectra for a given tank geometry, fluid properties, and liquid–vapor configurations within the tank. Over 10,000 antenna response simulations were completed for each propellant tank prior to the IM-1 mission and represented various volumetric fill levels and fluid configurations. The simulated spectra served as a database against which measured tank spectra were compared. For analysis, a spectral matching algorithm was used to find the best match between measured and simulated spectra, and the gauged mass was calculated from the most highly correlated fluid mass simulations. RFMG measurements were recorded during tank loading on the launch pad and during translunar coast, lunar orbit insertion, low lunar orbit, powered descent to the lunar surface, and postlanding on the Moon. This paper describes the RF and fluid simulations, the RFMG measurements and analysis of spectral data, the RFMG instrument, and the gauged results throughout all phases of the IM-1 mission.
lunar lander↗
AgeStrucNb : Software for Simulating and Detecting Changes in the Effective Number of Breeders ( N b)
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Tiago Antao↗
Final Report: Software for Simulation and Design of Optical Computers and Optical Neural Nets
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EM simulation↗
Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems
Science ecosystems are being built by federating computing systems and instruments located at geographically distributed sites over wide-area networks. These computing-instrument ecosystems are expected to support complex workflows that incorporate remote, automated AI-driven science experiments. Their realization, however, requires various designs to be explored and software components to be developed, in order to support the orchestration of distributed computations and experiments. It is often too expensive, infeasible, or disruptive for the entire ecosystem to be available during the typically long software development and testing periods. We propose a Virtual Infrastructure Twin (VIT) of the ecosystem that emulates its network and computing components, and incorporates its instrument software simulators. It provides a software environment nearly identical to the ecosystem to support early development and testing, and design space exploration. We present a brief overview of previous digital infrastructure twins that culminated in the VIT concept, including (i) the virtual science network environment for developing software-defined networking solutions, and (ii) the virtual federated science instrument environment for testing the federation software stack and remote instrument control software. We briefly describe VITs for Nion microscope steering and access to GPU systems.
Rao, Nageswara↗
Simulator for concurrent processing data flow architectures
A software simulator capability of simulating execution of an algorithm graph on a given system under the Algorithm to Architecture Mapping Model (ATAMM) rules is presented. ATAMM is capable of modeling the execution of large-grained algorithms on distributed data flow architectures. Investigating the behavior and determining the performance of an ATAMM based system requires the aid of software tools. The ATAMM Simulator presented is capable of determining the performance of a system without having to build a hardware prototype. Case studies are performed on four algorithms to demonstrate the capabilities of the ATAMM Simulator. Simulated results are shown to be comparable to the experimental results of the Advanced Development Model System.
Malekpour, Mahyar R.↗
Characterization Study of TestBed Infrastructure Performance in a Distributed Simulation Environment: Baseline Analysis
Characterization of the performance of Air Traffic Management Exploration (ATM-X) TestBed integration environment has been investigated and documented for one system configuration for progressively increasing traffic. Several statistical parameters were used to assess the performance of the TestBed distributed system such as mean, standard deviation, skewness, and kurtosis of latency, and update rate for aircraft state messages that are transmitted through the simulated system under investigation. It is necessary to assess the performance characteristics of distributed systems in terms of the indicated statistical parameters mentioned above. It is critical to verify the system performance with respect to a researcher’s required system performance. Computer host specifications are documented in terms of Central Processing Unit (CPU) clock speed and core count. Transmission Control Protocol/ Internet Protocol (TCP/IP) message protocol was used for data transmission. The system network topology also contributes to the latency and update rate variations from the one imposed by the data source. The motivation for selecting the TestBed infrastructure as the focus of this study can be attributed to the number of services and capabilities it provides that help simplify the process of preparing and conducting a simulation. These capabilities include an easy to use GUI for simulation configuration, access to TestBed library by the end-user of other simulation software components, a modular adapter paradigm that allows simple connectivity of external software to TestBed, connectivity with other simulation laboratories, and a Software Development Kit (SDK) for quicker development. Two types of traffic generators, Air Traffic Generator (ATG) and Multi Aircraft Control System (MACS) were used to generate messages that were injected into the TestBed distributed environment. Eight different air traffic scenarios with progressively increasing loads were generated for each air traffic simulator. The corresponding air traffic loads between the two simulators had an identical number of aircraft per scenario, but different flight plans. It was observed that the performance of MACS degraded for air traffic scenarios containing more than 200 aircraft (37.5 KB/s nominal throughput). However, ATG performed adequately under all tested air traffic loads up to 1200 aircraft (225. KB/s nominal throughput). The tests show that MACS exhibits better latency performance with smaller aircraft loads when compared to ATG. The tests also show that the TestBed infrastructure successfully transmits 1200 aircraft without significant degradation of its performance. From the latency trends for both MACS and ATG, it is clear that as aircraft load increases, the latency in the system increases as well as its standard deviation. Likewise, the trends for the update data rate for both MACS and ATG show that as the aircraft load increases, so does the standard deviation and mean of the update rates which can be attributed to the performance of MACS and ATG applications. The analysis of the results of this study have proven that the overall system performance is dependent on the individual performance of each system component that is connected to TestBed, which subsequently propagates into the system. All TestBed characterization tests were conducted in SimLabs at NASA Ames Research Center in November 2019. This study addresses the need for a baseline TestBed characterization, and the results will serve as a reference for more complex simulation systems.
Air Traffic Management simulations↗
Simulating A Factory Via Software
Software system generates simulation program from user's responses to questions. AMPS/PC system is simulation software tool designed to aid user in defining specifications of manufacturing environment and then automatically writing code for target simulation language, GPSS/PC. Domain of problems AMPS/PC simulates is that of manufacturing assembly lines with subassembly lines and manufacturing cells. Written in Turbo Pascal Version 4.
Schroer, Bernard J.↗
Simulation Modeling of Software Development Processes
A simulation modeling approach is proposed for the prediction of software process productivity indices, such as cost and time-to-market, and the sensitivity analysis of such indices to changes in the organization parameters and user requirements. The approach uses a timed Petri Net and Object Oriented top-down model specification. Results demonstrate the model representativeness, and its usefulness in verifying process conformance to expectations, and in performing continuous process improvement and optimization.
Calavaro, G. F.↗
Develop a Model Component
During my internship at NASA, I was a model developer for Ground Support Equipment (GSE). The purpose of a model developer is to develop and unit test model component libraries (fluid, electrical, gas, etc.). The models are designed to simulate software for GSE (Ground Special Power, Crew Access Arm, Cryo, Fire and Leak Detection System, Environmental Control System (ECS), etc. ~.) before they are implemented into hardware. These models support verifying local control and remote software for End-Item Software Under Test (SUT). The model simulates the physical behavior (function, state, limits and 110) of each end-item and it's dependencies as defined in the Subsystem Interface Table, Software Requirements & Design Specification (SRDS), Ground Integrated Schematic (GIS), and System Mechanical Schematic.(SMS). The software of each specific model component is simulated through MATLAB's Simulink program. The intensiv~ model development life cycle is a.s follows: Identify source documents; identify model scope; update schedule; preliminary design review; develop model requirements; update model.. scope; update schedule; detailed design review; create/modify library component; implement library components reference; implement subsystem components; develop a test script; run the test script; develop users guide; send model out for peer review; the model is sent out for verific~tionlvalidation; if there is empirical data, a validation data package is generated; if there is not empirical data, a verification package is generated; the test results are then reviewed; and finally, the user. requests accreditation, and a statement of accreditation is prepared. Once each component model is reviewed and approved, they are intertwined together into one integrated model. This integrated model is then tested itself, through a test script and autotest, so that it can be concluded that all models work conjointly, for a single purpose. The component I was assigned, specifically, was a fluid component, a discrete pressure switch. The switch takes a fluid pressure input, and if the pressure is greater than a designated cutoff pressure, the switch would stop fluid flow.
Ensey, Tyler S.↗
Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1
ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Medium Fidelity Simulation of Oxygen Tank Venting
The item to he cleared is a medium-fidelity software simulation model of a vented cryogenic tank. Such tanks are commonly used to transport cryogenic liquids such as liquid oxygen via truck, and have appeared on liquid-fueled rockets for decades. This simulation model works with the HCC simulation system that was developed by Xerox PARC and NASA Ames Research Center. HCC has been previously cleared for distribution. When used with the HCC software, the model generates simulated readings for the tank pressure and temperature as the simulated cryogenic liquid boils off and is vented. Failures (such as a broken vent valve) can be injected into the simulation to produce readings corresponding to the failure. Release of this simulation will allow researchers to test their software diagnosis systems by attempting to diagnose the simulated failure from the simulated readings. This model does not contain any encryption software nor can it perform any control tasks that might be export controlled.
Sweet, Adam↗
Computer simulator for a mobile telephone system
A software simulator was developed to assist NASA in the design of the land mobile satellite service. Structured programming techniques were used by developing the algorithm using an ALCOL-like pseudo language and then encoding the algorithm into FORTRAN 4. The basic input data to the system is a sine wave signal although future plans call for actual sampled voice as the input signal. The simulator is capable of studying all the possible combinations of types and modes of calls through the use of five communication scenarios: single hop systems; double hop, signal gateway system; double hop, double gateway system; mobile to wireline system; and wireline to mobile system. The transmitter, fading channel, and interference source simulation are also discussed.
Schilling, D. L.↗
Computer simulator for a mobile telephone system
A software simulator was developed to help in the design of the LMSS. The simulator is used to study the characteristics and implementation requirements of the LMSS' configuration.
Schilling, D. L.↗
Computer simulator for a mobile telephone system
A software simulator to help NASA in the design of the LMSS was developed. The simulator will be used to study the characteristics of implementation requirements of the LMSS's configuration with specifications as outlined by NASA.
Schilling, D. L.↗
Avoiding pitfalls in simulating real-time computer systems
The software simulation of a computer target system on a computer host system, known as an interpretive computer simulator (ICS), functionally models and implements the action of the target hardware. For an ICS to function as efficiently as possible and to avoid certain pitfalls in designing an ICS, it is important that the details of the hardware architectural design of both the target and the host computers be known. This paper discusses both host selection considerations and ICS design features that, without proper consideration, could make the resulting ICS too slow to use or too costly to maintain and expand.
Smith, R. S.↗