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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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Developing a Model Component

The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is,. responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) is a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The purpose of the UCTS is to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems s:luring their development. As an intern at KSC, my assignment was to develop a model component for the UCTS. I was given a fluid component (drier) to model in Matlab. The drier was a Catch All replaceable core type filter-drier. The filter-drier provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-drier also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. I completed training for UNIX and Simulink to help aid in my assignment. The filter-drier was modeled by determining affects it has on the pressure, velocity and temperature of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my model filter-drier in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements.

Fields, Christina M.↗

System Testing of Ground Cooling System Components

This internship focused primarily upon software unit testing of Ground Cooling System (GCS) components, one of the three types of tests (unit, integrated, and COTS/regression) utilized in software verification. Unit tests are used to test the software of necessary components before it is implemented into the hardware. A unit test determines that the control data, usage procedures, and operating procedures of a particular component are tested to determine if the program is fit for use. Three different files are used to make and complete an efficient unit test. These files include the following: Model Test file (.mdl), Simulink SystemTest (.test), and autotest (.m). The Model Test file includes the component that is being tested with the appropriate Discrete Physical Interface (DPI) for testing. The Simulink SystemTest is a program used to test all of the requirements of the component. The autotest tests that the component passes Model Advisor and System Testing, and puts the results into proper files. Once unit testing is completed on the GCS components they can then be implemented into the GCS Schematic and the software of the GCS model as a whole can be tested using integrated testing. Unit testing is a critical part of software verification; it allows for the testing of more basic components before a model of higher fidelity is tested, making the process of testing flow in an orderly manner.

Unit Test↗

LADEE Multi-Domain Simulation

The Lunar Atmosphere Dust Environment Explorer (LADEE) was a small explorer class spacecraft that was launched on Sept 7, 2013 and that was de-orbited and successfully impacted the Moons surface on April 17, 2014 after completing all of the mission objectives. The low-cost rapidly prototyped hardware design used for the spacecraft was extend to the development of the software base. To achieve this goal, a Model Based Design approach was utilized to develop the onboard flight software, and out of this development a model based multipurpose simulator was created of the LADEE spacecraft and its mission environment. This simulator extended the traditional function of propagating the vehicle's kinematic and rotational states and included the electrical and thermal states propagation. Traditionally, these domains are handled by domain specific high fidelity simulations that use the states histories from other domains as input. By reducing the fidelity and abstracting the relevant features being monitored and controlled by the flight software, it was possible to model the coupling across these domains resulting in more accurate overall system behavior. A faster than real-time workstation (WSIM) version of the LADEE simulator was used to develop and test the software control algorithms in the Simulink environment. To maximize the performance of the simulation, modeling knobs were introduced to reduce the resolution of the some of the domains models when the effects of that domain were not significant for the scope of that simulation. The automatic code generation feature in Simulink was used to port the simulation to several real-time environments to support Processor-in-the-Loop (PIL) and Hardware-in-the-Loop (HIL) testing, verification and validation. The real-time environment required that the design of each of the domain models be deterministic as possible in the time required to perform all of the calculations to update its states. The simulation interface was designed to be compatible with the command interface employed by the LADEE mission operation team. The WSIM, PIL, and HIL simulators thus used a common interface and thus were used for flight software testing, for mission operations personnel training (nominal and off-nominal operations) prior to the mission and to perform command sequence verification during the mission. This presentation will look at the modeling strategies used to create a common interface to the simulator and to model and couple multiple domains within the simulation, the results of those strategies, and the lessons learned.

Multi-Domain↗

The Ten Lockheed Martin Cyber-Physical Challenges: Formalized, Analyzed, and Explained

Capturing and analyzing requirements of Cyber-Physical Systems (CPS) can be challenging, since CPS models typically involve time-varying and real-valued variables, physical system dynamics, or even adaptive behavior. MATLAB/Simulinkis a development and simulation framework that is widely used in industry to capture such systems. In this paper, we report on the application of NASA Ames tools to perform end-to-end analysis of the Ten Lockheed Martin Challenge Problems (LMCPS). LMCPS is a set of industrial Simulink model benchmarks and natural language requirements developed by domain experts. Our framework, which integrates the tools FRET and COCOSIM, is used to: 1) elicit, explain, and formalize the semantics of the given natural language requirements; 2) generate verification code and monitors that can be automatically attached to the Simulink models; 3) perform verification by using SMT-based model checkers. FRET and COCOSIM are open source, and can be used by other researchers and practitioners to replicate our case study. We provide a categorization of recurring patterns in the formalization of the requirements and discuss the strengths and weaknesses of our automated verification approach.

Anastasia Mavridou↗

Lunar Lander Landing Modeling and Simulation in Simscape

The landing gear is a critical subsystem of a lander for a successful landing on the moon or a planet. During a landing event, structural loading, energy absorption and toppling stability are important factors for the landing gear development. These aspects can be studied using simulations. The landing gear comprising the primary struct, secondary structs, footpad, and joints, is easily modeled using Simscape Multibody toolbox. The energy absorption mechanisms in the structs is readily modeled using Simulink and Multibody blocks based on the relative motions of the inner and outer cylinder of the structures. During touchdown, the footpads strike the lunar surface, and the contact forces can be modeled including the soil mechanical properties. Slosh dynamics are included using a mechanical pendulum model. Tip-over controllers are developed using Simulink blocks and toolboxes. This model was intensively tested manually then additionally with Monte Carlo simulation. It offers the opportunity for landing stability study, i.e. the max slope a lander can land without tipping over in 3D realistic landing situations.

Wei Wu↗

Design, Formalization, and Verification of Decision Making for Intelligent Systems

The development of autonomous systems requires a rigorous process that can guarantee a system’s reliability in critical applications. At its core, an autonomous system bases its behavior on a well-defined decision making system. In this paper, we present a methodological basis for the design, formalization and formal verification of Decision Making systems for autonomous agents. The approach is generally applicable to operational objectives that can be functionally decomposed and subsequently represented as Hierarchical Finite State Machines. As a case study, we present the application of this method to implement a Decision Making model in Simulink. Furthermore, we present how we use NASA’s FRET tool to write requirements in structured natural language and generate formal specifications that can be automatically digested by NASA’s CoCoSim tool. Finally, we present how, by leveraging CoCoSim, we perform formal verification against the Simulink model and present analysis results.

Model-based development↗

Design, Formalization, and Verification of Decision Making for Intelligent Systems

The development of autonomous systems requires a rigorous process that can guarantee a system’s reliability in critical applications. At its core, an autonomous system bases its behavior on a well-defined decision making system. In this paper, we present a methodological basis for the design, formalization and formal verification of Decision Making systems for autonomous agents. The approach is generally applicable to operational objectives that can be functionally decomposed and subsequently represented as Hierarchical Finite State Machines. As a case study, we present the application of this method to implement a Decision Making model in Simulink. Furthermore, we present how we use NASA’s FRET tool to write requirements in structured natural language and generate formal specifications that can be automatically digested by NASA’s CoCoSim tool. Finally, we present how, by leveraging CoCoSim, we perform formal verification against the Simulink model and present analysis results.

Model-based development↗

Flight Dynamics Modeling for a Rapid Conceptual Development Environment

This paper presents the integration of flight dynamics modeling (FDM) within an aircraft conceptual development framework. Within this framework, FDM and simulation are used for the preliminary analysis of the takeoff, landing, and critical loss of thrust performance of early-stage aircraft concepts. The aerodynamic and propulsive models are built using the XML-based DAVE-ML model exchange. Automated integration of these models is achieved using the Simulink® model generation available through the DAVEtools Java package in addition to Simulink®-based flight simulation blocks. Results demonstrating the established methods are presented for the analysis of a twin-engine light transport example aircraft. This work establishes methods that will be used to perform trade studies of aircraft designed for Regional Air Mobility operations. These aircraft will require short takeoff and landing distances in addition to steep climb and descent gradients, each of which can be estimated and applied as design space constraints using the current methods.

Flight Dynamics↗

New Developments and Capabilities Within WEC-Sim: Preprint

WEC-Sim is an open-source software for simulating wave energy converters, which has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (Sandia) within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with our latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1 which spans over a two year period from June 2020 to September 2022. New features to be described will include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗

Sensitivity study of parameters important to Molten Salt Reactor Safety

This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann’s model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon’s 550MW th MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

HERO WEC V1.0 - WEC-Sim Model

This zip file contains the files that are needed to simulate NREL's HERO WEC (hydraulic and electric reverse osmosis wave energy converter). This requires the user to have already installed WEC-Sim. In addition to the standard toolboxes that are required to run WEC-Sim the user will also need the Simscape Fluids and Simscape Driveline packages. In the zip file you will find the following: - HEROV1_HPTO.slx: Simulink-based WEC Sim model of the first gen (V1.0) Hydraulic PTO (power take-off) that was designed for the HERO WEC - wecSimInputFile.m: Input file needed to run the model - userDefinedFunctionsMCR.m: MCR (multi condition run) script that is needed if a use wants to simulate multiple wave conditions. - geometry (folder): Includes the geometry file that is needed for visualization - hydroData (folder): Includes the required WAMIT data to run WEC-Sim

16 TIDAL AND WAVE POWER↗

HERO WEC V1.0 - WEC-Sim Model (July 2024)

**This submission supersedes submission MHKDR-483** This submission file contains the files that are needed to simulate NREL's HERO WEC (hydraulic and electric reverse osmosis wave energy converter). This requires the user to have already installed WEC-Sim. In addition to the standard toolboxes that are required to run WEC-Sim the user will also need the Simscape Fluids and Simscape Driveline packages. The zip file (HERO_V1_WECSim_2024.zip) contains the following: - HERO_HPTO_2024.slx: Simulink-based WEC Sim model of the first gen (V1.0) Hydraulic PTO (power take-off) that was designed for the HERO WEC. This model has been updated since submission #483 based on in-laboratory experimental results. - wecSimInputFile.m: Input file needed to run the model - userDefinedFunctionsMCR.m: MCR (multi condition run) script that is needed if a use wants to simulate multiple wave conditions. - geometry (folder): Includes the geometry file that is needed for visualization - hydroData (folder): Includes the required WAMIT data to run WEC-Sim -HydVisualization.mlx: Visualization script to plot simulation results (not needed to run)

16 TIDAL AND WAVE POWER↗

An Introduction to Transient Engine Applications Using the Numerical Propulsion System Simulation (NPSS) and MATLAB

This document outlines methodologies designed to improve the interface between the Numerical Propulsion System Simulation framework and various control and dynamic analyses developed in the Matlab and Simulink environment. Although NPSS is most commonly used for steady-state modeling, this paper is intended to supplement the relatively sparse documentation on it's transient analysis functionality. Matlab has become an extremely popular engineering environment, and better methodologies are necessary to develop tools that leverage the benefits of these disparate frameworks. Transient analysis is not a new feature of the Numerical Propulsion System Simulation (NPSS), but transient considerations are becoming more pertinent as multidisciplinary trade-offs begin to play a larger role in advanced engine designs. This paper serves to supplement the relatively sparse documentation on transient modeling and cover the budding convergence between NPSS and Matlab based modeling toolsets. The following sections explore various design patterns to rapidly develop transient models. Each approach starts with a base model built with NPSS, and assumes the reader already has a basic understanding of how to construct a steady-state model. The second half of the paper focuses on further enhancements required to subsequently interface NPSS with Matlab codes. The first method being the simplest and most straightforward but performance constrained, and the last being the most abstract. These methods aren't mutually exclusive and the specific implementation details could vary greatly based on the designer's discretion. Basic recommendations are provided to organize model logic in a format most easily amenable to integration with existing Matlab control toolsets.

Matlab↗

Effects of Heat Transfer Coefficient Variation on Nuclear Thermal Propulsion Engine Performance

A physics-based Nuclear Thermal Propulsion (NTP) Testing Reference Design (TRD) power balance model was coded in Simulink to investigate engine performance for various design and parameter modifications. Since the primary mode of heat transfer in NTP engines is convective, the convective heat transfer coefficient (HTC) is a key parameter that requires accurate representation. The industry standard Westinghouse correlation has an uncertainty of ±20% which was investigated in this study. The results showed that a 20% decrease in the HTC led to a 4.14% increase in maximum fuel temperature while a 20% decrease in the HTC led to a 1.81% decrease in maximum fuel temperature suggesting that narrowing the uncertainty of this correlation through experimental work would be a critical step in the development of NTP engines. Furthermore, a maximum fuel temperature relationship with specific impulse was developed for the TRD engine which showed potential engine operation between specific impulse values of 715 and 900 seconds with minimal changes to the engine design. This graph could be useful for high level vehicle performance estimations for fuel types with different maximum operating temperatures.

Heat Transfer Coefficient↗

Effects of Varying the Heat Transfer Coefficient on Engine Performance

A physics-based Nuclear Thermal Propulsion (NTP) Testing Reference Design (TRD) power balance model was coded in Simulink to investigate engine performance for various design and parameter modifications. Since the primary mode of heat transfer in NTP engines is convective, the convective heat transfer coefficient (HTC) is a key parameter that requires accurate representation. The industry standard Westinghouse correlation has an uncertainty of ±20% which was investigated in this study. The results showed that a 20% decrease in the HTC led to a 4.14% increase in maximum fuel temperature while a 20% decrease in the HTC led to a 1.81% decrease in maximum fuel temperature suggesting that narrowing the uncertainty of this correlation through experimental work would be a critical step in the development of NTP engines. Furthermore, a maximum fuel temperature relationship with specific impulse was developed for the TRD engine which showed potential engine operation between specific impulse values of 715 and 900 seconds with minimal changes to the engine design. This graph could be useful for high level vehicle performance estimations for fuel types with different maximum operating temperatures.

Heat Transfer Coefficient↗

Integration of a SMES–Battery-Based Hybrid Energy Storage System into Microgrids

The future trends of the industry require major renovations in the infrastructure of transmission, distribution, and storing of generated energy. With the increased use of renewable energy across the globe, energy storage (ES) systems have started to play a prominent role in shaping the future of the ES market. However, because of the uneven distribution of the renewable energy throughout the world, more emphasis must be made to the integration of power grids with the ES devices to utilize the excess power more effectively. In this paper, a study is performed regarding the integration of a hybrid system, consisting of a lithium-ion battery (LIB) and superconducting magnetic energy storage (SMES), into an interconnected microgrid operation. The structure of a microgrid is explained by analyzing the selected battery (LIB) and voltage source converter (VSC)-based SMES unit via MATLAB & Simulink. Finally, the voltage waveforms are compared and discussed in detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analysis of the Current Limiting Performance of a Novel DC-SFCL in the VSC-HVDC System

With increasing demand of the power load and the development of the new energy resources, voltage-sourced converter-based high-voltage direct current (VSC-HVDC) transmission system has been widely utilized. However, its development is seriously limited due to short circuit. To address this, high-temperature superconducting direct current fault current limiter (DC-SFCL) is designed. In this paper, a novel topology of DC-SFCL is firstly presented along with its principle and mathematical model. Secondly, the thermoelectric model of its superconducting current-limiting unit (SCLU) is established. In addition, simulation of VSC-HVDC system containing this novel DC-SFCL topology is analyzed using Simulink software. Finally, experimental measurements are designed and conducted to verify the correctness of the theoretical model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗