SEARCH · Engineering Papers

Results for “system level modeling”

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.

SourceResearch connectionFrom yearThrough year

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

At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

NASA NTRS1991

Hybrid CMS methods with model reduction for assembly of structures

Future on-orbit structures will be designed and built in several stages, each with specific control requirements. Therefore there must be a methodology which can predict the dynamic characteristics of the assembled structure, based on the dynamic characteristics of the subassemblies and their interfaces. The methodology developed by CSC to address this issue is Hybrid Component Mode Synthesis (HCMS). HCMS distinguishes itself from standard component mode synthesis algorithms in the following features: (1) it does not require the subcomponents to have displacement compatible models, which makes it ideal for analyzing the deployment of heterogeneous flexible multibody systems, (2) it incorporates a second-level model reduction scheme at the interface, which makes it much faster than other algorithms and therefore suitable for control purposes, and (3) it does answer specific questions such as 'how does the global fundamental frequency vary if I change the physical parameters of substructure k by a specified amount?'. Because it is based on an energy principle rather than displacement compatibility, this methodology can also help the designer to define an assembly process. Current and future efforts are devoted to applying the HCMS method to design and analyze docking and berthing procedures in orbital construction.

Farhat, Charbel↗

NASA NTRSDate not supplied

Comprehensive Analysis Aeroelastic Stability Predictions for the Mars Sample Recovery Helicopters and Ingenuity

A rotorcraft comprehensive analysis was used to generate aeroelastic stability predictions for both Ingenuity and the Mars Sample Recovery Helicopters. The analysis was performed multiple times for each rotor system with sequential increases to the level of modeling complexity. Initial cases used an independent blade analysis, trim inflow distribution, no airframe degrees of freedom, and a hover condition (a time-invariant problem). The final model used all blades, dynamic inflow, airframe degrees of freedom, and a Floquet theory approach to the flutter analysis. The approach of sequentially increasing modeling complexity was employed to ensure the causes of any observed instabilities could be identified. For each case, stability results were determined across a range of air densities, tip Mach numbers, and rotor collective pitch settings. For the Sample Recovery Helicopter, a forward flight condition analysis with the highest level of modeling complexity was also performed. The aeroelastic stability predictions showed both the Ingenuity and Sample Recovery Helicopter rotor systems to be stable for all analyzed conditions. Parameter excursions of structural properties were performed to explore conditions resulting in aeroelastic instabilities.

Aeroelastic↗

NASA NTRS1987

A technique for evaluating the application of the pin-level stuck-at fault model to VLSI circuits

Accurate fault models are required to conduct the experiments defined in validation methodologies for highly reliable fault-tolerant computers (e.g., computers with a probability of failure of 10 to the -9 for a 10-hour mission). Described is a technique by which a researcher can evaluate the capability of the pin-level stuck-at fault model to simulate true error behavior symptoms in very large scale integrated (VLSI) digital circuits. The technique is based on a statistical comparison of the error behavior resulting from faults applied at the pin-level of and internal to a VLSI circuit. As an example of an application of the technique, the error behavior of a microprocessor simulation subjected to internal stuck-at faults is compared with the error behavior which results from pin-level stuck-at faults. The error behavior is characterized by the time between errors and the duration of errors. Based on this example data, the pin-level stuck-at fault model is found to deliver less than ideal performance. However, with respect to the class of faults which cause a system crash, the pin-level, stuck-at fault model is found to provide a good modeling capability.

Palumbo, Daniel L.↗

NASA NTRS1989

Issues in CSI analysis for large scale systems

Future spacecraft such as the International Space Station result in flexible models with hundreds, or perhaps thousands of modes in a frequency range where the potential for control/structure interaction exists. This provides the analyst with a formidable model reduction problem at both the component and the system level. Approaches to normal modes as a structural representation, applicability of alternate structural representations and algorithms for selecting important modal degrees of freedom at both the component and the system level are discussed. Practical implementation of these techniques on a large scale model of the Space Station are presented.

Blelloch, Paul↗

NASA NTRS1999

The 13th Technology of Deep Space One

model-based-code-generation↗

NASA NTRS1989

Multi-level manual and autonomous control superposition for intelligent telerobot

Space telerobots are recognized to require cooperation with human operators in various ways. Multi-level manual and autonomous control superposition in telerobot task execution is described. The object model, the structured master-slave manipulation system, and the motion understanding system are proposed to realize the concept. The object model offers interfaces for task level and object level human intervention. The structured master-slave manipulation system offers interfaces for motion level human intervention. The motion understanding system maintains the consistency of the knowledge through all the levels which supports the robot autonomy while accepting the human intervention. The superposing execution of the teleoperational task at multi-levels realizes intuitive and robust task execution for wide variety of objects and in changeful environment. The performance of several examples of operating chemical apparatuses is shown.

Hirai, Shigeoki↗

NASA NTRS1981

A new method for calculating time-dependent atomic level populations

A method is described for reducing the number of levels to be dealt with in calculating time-dependent populations of atoms or ions in plasmas. The procedure effectively extends the collisional-radiative model to consecutive stages of ionization, treating ground and metastable levels explicitly and excited levels implicitly. Direct comparisons of full and simulated systems are carried out for five-level models.

Kastner, S. O.↗

NASA NTRS2012

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Hutto, Clayton↗

NASA NTRS2005

Evaluation of Cryofreezer Technology through Simulation and Testing (DRAFT)

A cryofreezer system is being evaluated as a new method of compressing and storing carbon dioxide (CO2) in an Advanced Life Support (ALS) Environmental Control and Life Support System (ECLSS). A cryocooler is used to provide cold temperatures and heat removal while CO2 freezes and accumulates around a coldtip. The CO2 can then be stored as a liquid or high-pressure gas after it has been accumulated. This system was originally conceived as an In-Situ Resource Utilization (ISRU) application for collecting CO2 from the Mars atmosphere to be converted to methane fuel with a Sabatier reaction. In the ALS application, this system could collect CO2 from the International Space Station (ISS) Carbon Dioxide Removal Assembly (CDRA) for delivery to the Sabatier reactor. The Sabatier reaction is an important part of proposed Air Revitalization System (ARS) for ALS, and technology sharing is often possible between ISRU and ARS applications in CO2 processing systems. A prototype system developed and initially tested by Lockheed Martin Astronautics is now being evaluated in the Air Revitalization Technology Evaluation Facility (ARTEF) at NASA Johnson Space Center (JSC). This paper will discuss testing conducted through December 2004 to examine the performance and capacity of the system under a variety of input conditions. A simulation of the system was developed simultaneously using the Aspen Custom Modeler (ACM) software package. Several approaches using varying levels of detail could be used when modeling the system, and this paper will discuss the assumptions and choices made in this simulation, as well as the validity of the simulation for predicting performance of the prototype unit.

Anderson, Molly↗

NASA NTRS2017

UAV Trajectory Modeling Using Neural Networks

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural network should be able to predict the vehicle's future states at next time step. A complete 4-D trajectory are then generated step by step using the trained neural network. Experiments in this work show that the neural network can approximate the sUAV's model and predict the trajectory accurately.

Neural Networks↗

NASA NTRS1990

A PC based fault diagnosis expert system

The Integrated Status Assessment (ISA) prototype expert system performs system level fault diagnosis using rules and models created by the user. The ISA evolved from concepts to a stand-alone demonstration prototype using OPS5 on a LISP Machine. The LISP based prototype was rewritten in C and the C Language Integrated Production System (CLIPS) to run on a Personal Computer (PC) and a graphics workstation. The ISA prototype has been used to demonstrate fault diagnosis functions of Space Station Freedom's Operation Management System (OMS). This paper describes the development of the ISA prototype from early concepts to the current PC/workstation version used today and describes future areas of development for the prototype.

Marsh, Christopher A.↗

NASA NTRS2000

The 13th Technology of Deep Space One - Abstract

On October 24th, 1998, the Deep Space One (DS-1) spacecraft launched aboard a Delta II rocket as the first step towards the bold task of testing and validating 12 new technologies for future missions. This launch also represented yet another thrilling event; namely, the successful test and validation of a 13th heretofore undisclosed technology: model-based code-generation of the spacecraft's system-level fault-protection (FP) software from behavioral state diagrams and structural models.In this paper, we describe the process we used to leverage model-based code generation from state diagrams and structural specifications to better respond to the evolving requirements and scope of DS- I's system-level fault-protection design, development, test and operation. The evolution of the high-level design and the low-level changes in the flight software architecture and interfaces contributed to multiplying the number and frequency of fault-protection software releases thereby creating a multitude of software integration issues. To address the resulting software integration issues, we broadened the scope of code -eneration to other forms of model- based analysis techniques more traditionally associated with first-principle's reasoning about physical models. Additionally, we describe our in-flight launch and initial acquisition experience.

Rouquette, Nicolas↗

NASA NTRS1980

Evaluation of computing systems using functionals of a Stochastic process

An intermediate model was used to represent the probabilistic nature of a total system at a level which is higher than the base model and thus closer to the performance variable. A class of intermediate models, which are generally referred to as functionals of a Markov process, were considered. A closed form solution of performability for the case where performance is identified with the minimum value of a functional was developed.

Meyer, J. F.↗

NASA NTRS2004

Turbofan Engine Simulated in a Graphical Simulation Environment

Recently, there has been an increase in the development of intelligent engine technology with advanced active component control. The computer engine models used in these control studies are component-level models (CLM), models that link individual component models of state space and nonlinear algebraic equations, written in a computer language such as Fortran. The difficulty faced in performing control studies on Fortran-based models is that Fortran is not supported with control design and analysis tools, so there is no means for implementing real-time control. It is desirable to have a simulation environment that is straightforward, has modular graphical components, and allows easy access to health, control, and engine parameters through a graphical user interface. Such a tool should also provide the ability to convert a control design into real-time code, helping to make it an extremely powerful tool in control and diagnostic system development. Simulation time management is shown: Mach number versus time, power level angle versus time, altitude versus time, ambient temperature change versus time, afterburner fuel flow versus time, controller and actuator dynamics, collect initial conditions, CAD output, and component-level model: CLM sensor, CAD input, and model output. The Controls and Dynamics Technologies Branch at the NASA Glenn Research Center has developed and demonstrated a flexible, generic turbofan engine simulation platform that can meet these objectives, known as the Modular Aero-Propulsion System Simulation (MAPSS). MAPSS is a Simulink-based implementation of a Fortran-based, modern high pressure ratio, dual-spool, low-bypass, military-type variable-cycle engine with a digital controller. Simulink (The Mathworks, Natick, MA) is a computer-aided control design and simulation package allows the graphical representation of dynamic systems in a block diagram form. MAPSS is a nonlinear, non-real-time system composed of controller and actuator dynamics (CAD) and component-level model (CLM) modules. The controller in the CAD module emulates the functionality of a digital controller, which has a typical update rate of 50 Hz. The CLM module simulates the dynamics of the engine components and uses an update rate of 2500 Hz, which is needed to iterate to balance mass and energy among system components. The actuators in the CAD module use the same sampling rate as those in the CLM. Two graphs of normalized spool speed versus time in seconds and one graph of normalized average metal temperature versus time in seconds is shown. MAPSS was validated via open-loop and closed-loop comparisons with the Fortran simulation. The preceding plots show the normalized results of a closed-loop comparison looking at three states of the model: low-pressure spool speed, high-pressure spool speed, and the average metal temperature measured from the combustor to the high-pressure turbine. In steady state, the error between the simulations is less than 1 percent. During a transient, the difference between the simulations is due to a correction in MAPSS that prevents the gas flow in the bypass duct inlet from flowing forward instead of toward the aft end, which occurs in the Fortran simulation. A comparison between MAPSS and the Fortran model of the bypass duct inlet flow for power lever angles greater than 35 degrees is shown.

Parker, Khary I.↗

NASA NTRS1998

Integration of the Remote Agent for the NASA Deep Space One Autonomy Experiment

This paper describes the integration of the Remote Agent (RA), a spacecraft autonomy system which is scheduled to control the Deep Space 1 spacecraft during a flight experiment in 1999. The RA is a reusable, model-based autonomy system that is quite different from software typically used to control an aerospace system. We describe the integration challenges we faced, how we addressed them, and the lessons learned. We focus on those aspects of integrating the RA that were either easier or more difficult than integrating a more traditional large software application because the RA is a model-based autonomous system. A number of characteristics of the RA made integration process easier. One example is the model-based nature of RA. Since the RA is model-based, most of its behavior is not hard coded into procedural program code. Instead, engineers specify high level models of the spacecraft's components from which the Remote Agent automatically derives correct system-wide behavior on the fly. This high level, modular, and declarative software description allowed some interfaces between RA components and between RA and the flight software to be automatically generated and tested for completeness against the Remote Agent's models. In addition, the Remote Agent's model-based diagnosis system automatically diagnoses when the RA models are not consistent with the behavior of the spacecraft. In flight, this feature is used to diagnose failures in the spacecraft hardware. During integration, it proved valuable in finding problems in the spacecraft simulator or flight software. In addition, when modifications are made to the spacecraft hardware or flight software, the RA models are easily changed because they only capture a description of the spacecraft. one does not have to maintain procedural code that implements the correct behavior for every expected situation. On the other hand, several features of the RA made it more difficult to integrate than typical flight software. For example, the definition of correct behavior is more difficult to specify for a system that is expected to reason about and flexibly react to its environment than for a traditional flight software system. Consequently, whenever a change is made to the RA it is more time consuming to determine if the resulting behavior is correct. We conclude the paper with a discussion of future work on the Remote Agent as well as recommendations to ease integration of similar autonomy projects.

Dorais, Gregory A.↗

NASA NTRS1992

Predictive Caching Using the TDAG Algorithm

We describe how the TDAG algorithm for learning to predict symbol sequences can be used to design a predictive cache store. A model of a two-level mass storage system is developed and used to calculate the performance of the cache under various conditions. Experimental simulations provide good confirmation of the model.

Laird, Philip↗

NASA NTRSDate not supplied

An Initial Vibro-Acoustic Model for Predicting Electric Motor Noise

A system-level tool to predict electric motor noise, suitable for trade studies of eVTOL and UAM aircraft, does not exist. This work describes the ongoing effort to develop such a tool. It utilizes a 3 phase prediction routine that models the electro-magnetic interactions of the electric motor, the resulting structural vibrations of the motor rotor, and finally the acoustic propagation generated by those structural vibrations.

Electric Motor Noise↗

NASA NTRSDate not supplied

A Technology Maturation Plan for the Development of Nuclear Electric Propulsion

Over the last two years NASA’s Space Nuclear Propulsion (SNP) Project formulated a Technology Maturation Plan (TMP) for development of the sub-systems needed for a MW-class Nuclear Electric Propulsion (NEP) system which, combined with a high thrust chemical propulsion stage, would be suitable for human missions to Mars. Two recent assessments, independently conducted by the National Academies for Science, Engineering, and Medicine and the NASA Engineering & Safety Center, concluded that the technologies required for a high-power NEP system are immature and the attendant risks insufficiently quantified to justify initiating a flight project. For NEP to be available as a viable option to meet flight opportunities in the late 2030s / 2040s time frame, development of the key sub-systems must begin now. SNP has subdivided the NEP system into five Critical Technology Elements (CTE): the nuclear reactor, power conversion, power management and distribution, electric propulsion sub-system, and the primary heat rejection system. Development plans for each of these CTEs have been drafted which will serve as the template for a focused milestone-driven research and development campaign intended to advance each CTE to Technology Readiness Level (TRL) 5. This will be accomplished by building and testing hardware at relevant power levels (~ 1 MW) and for relevant durations (2,500 hours, ~10% of the required operational lifetime) and conducting numerical modeling of the CTEs anchored by the accumulated test data to predict system performance and reliability. Concurrent with this work, high-level coupled system/mission modeling will be carried out to refine the key performance parameters that the various CTEs must achieve. Non-advocate reviews will be held at milestone points to assess progress and inform down-select decisions. The strategy for formulating the TMP was described previously*; this paper describes ongoing progress on the drafting and baselining of the plan, including key specific details. * “Strategy for Developing Technologies for Megawatt-class Nuclear Electric Propulsion Systems”, K.A. Polzin, et. al., International Electric Propulsion Conference IEPC 2022, IEPC-2022-155

Nuclear Electric Propulsion↗