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At least 397 records · Page 22

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

Pan, Jianqiang↗

Tools for describing the reference architecture for space data systems

This paper has briefly presented the Reference Architecture for Space Data Systems (RASDS) that is being developed by the CCSDS Systems Architecture Working Group (SAWG). The SAWG generated some sample architectures (spacecraft onboard architectures, space link architectures, cross-support architectures) using this RASDS approach, and RASDS was proven to be a powerful tool for describing and relating different space data system architectures.

communication↗

High-Performance Algorithm for Solving the Diagnosis Problem

An improved method of model-based diagnosis of a complex engineering system is embodied in an algorithm that involves considerably less computation than do prior such algorithms. This method and algorithm are based largely on developments reported in several NASA Tech Briefs articles: The Complexity of the Diagnosis Problem (NPO-30315), Vol. 26, No. 4 (April 2002), page 20; Fast Algorithms for Model-Based Diagnosis (NPO-30582), Vol. 29, No. 3 (March 2005), page 69; Two Methods of Efficient Solution of the Hitting-Set Problem (NPO-30584), Vol. 29, No. 3 (March 2005), page 73; and Efficient Model-Based Diagnosis Engine (NPO-40544), on the following page. Some background information from the cited articles is prerequisite to a meaningful summary of the innovative aspects of the present method and algorithm. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD. Diagnosis the task of finding faulty components is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. The calculation of a minimal diagnosis is inherently a hard problem, the solution of which requires amounts of computation time and memory that increase exponentially with the number of components of the engineering system. Among the developments to reduce the computational burden, as reported in the cited articles, is the mapping of the diagnosis problem onto the integer-programming (IP) problem. This mapping makes it possible to utilize a variety of algorithms developed previously for IP to solve the diagnosis problem. In the IP approach, the diagnosis problem can be formulated as a linear integer optimization problem, which can be solved by use of well-developed integer-programming algorithms. This concludes the background information.

Fijany, Amir↗

Nuclear Engine System Simulation (NESS). Volume 1: Program user's guide

A Nuclear Thermal Propulsion (NTP) engine system design analysis tool is required to support current and future Space Exploration Initiative (SEI) propulsion and vehicle design studies. Currently available NTP engine design models are those developed during the NERVA program in the 1960's and early 1970's and are highly unique to that design or are modifications of current liquid propulsion system design models. To date, NTP engine-based liquid design models lack integrated design of key NTP engine design features in the areas of reactor, shielding, multi-propellant capability, and multi-redundant pump feed fuel systems. Additionally, since the SEI effort is in the initial development stage, a robust, verified NTP analysis design tool could be of great use to the community. This effort developed an NTP engine system design analysis program (tool), known as the Nuclear Engine System Simulation (NESS) program, to support ongoing and future engine system and stage design study efforts. In this effort, Science Applications International Corporation's (SAIC) NTP version of the Expanded Liquid Engine Simulation (ELES) program was modified extensively to include Westinghouse Electric Corporation's near-term solid-core reactor design model. The ELES program has extensive capability to conduct preliminary system design analysis of liquid rocket systems and vehicles. The program is modular in nature and is versatile in terms of modeling state-of-the-art component and system options as discussed. The Westinghouse reactor design model, which was integrated in the NESS program, is based on the near-term solid-core ENABLER NTP reactor design concept. This program is now capable of accurately modeling (characterizing) a complete near-term solid-core NTP engine system in great detail, for a number of design options, in an efficient manner. The following discussion summarizes the overall analysis methodology, key assumptions, and capabilities associated with the NESS presents an example problem, and compares the results to related NTP engine system designs. Initial installation instructions and program disks are in Volume 2 of the NESS Program User's Guide.

Pelaccio, Dennis G.↗

Fault diagnosis for the Space Shuttle main engine

A conceptual design of a model-based fault detection and diagnosis system is developed for the Space Shuttle main engine. The design approach consists of process modeling, residual generation, and fault detection and diagnosis. The engine is modeled using a discrete time, quasilinear state-space representation. Model parameters are determined by identification. Residuals generated from the model are used by a neural network to detect and diagnose engine component faults. Fault diagnosis is accomplished by training the neural network to recognize the pattern of the respective fault signatures. Preliminary results for a failed valve, generated using a full, nonlinear simulation of the engine, are presented. These results indicate that the developed approach can be used for fault detection and diagnosis. The results also show that the developed model is an accurate and reliable predictor of the highly nonlinear and very complex engine.

Duyar, Ahmet↗

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and building behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A fuzzy case based reasoning tool for model based approach to rocket engine health monitoring

In this system we develop a fuzzy case based reasoner that can build a case representation for several past anomalies detected, and we develop case retrieval methods that can be used to index a relevant case when a new problem (case) is presented using fuzzy sets. The choice of fuzzy sets is justified by the uncertain data. The new problem can be solved using knowledge of the model along with the old cases. This system can then be used to generalize the knowledge from previous cases and use this generalization to refine the existing model definition. This in turn can help to detect failures using the model based algorithms.

Krovvidy, Srinivas↗

Rule-based simulation models

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

Nieten, Joseph L.↗

Studies and analyses of the space shuttle main engine

The primary objectives were to: evaluate ways to maximize the information yield from the current Space Shuttle Main Engine (SSME) condition monitoring sensors, identify additional sensors or monitoring capabilities which would significantly improve SSME data, and provide continuing support of the Main Engine Cost/Operations (MECO) model. In the area of SSME condition monitoring, the principal tasks were a review of selected SSME failure data, a general survey of condition monitoring, and an evaluation of the current engine monitoring system. A computerized data base was developed to assist in modeling engine failure information propagations. Each of the above items is discussed in detail. Also included is a brief discussion of the activities conducted in support of the MECO model.

Tischer, Alan E.↗

Engine Data Interpretation System (EDIS)

A prototype of an expert system was developed which applies qualitative or model-based reasoning to the task of post-test analysis and diagnosis of data resulting from a rocket engine firing. A combined component-based and process theory approach is adopted as the basis for system modeling. Such an approach provides a framework for explaining both normal and deviant system behavior in terms of individual component functionality. The diagnosis function is applied to digitized sensor time-histories generated during engine firings. The generic system is applicable to any liquid rocket engine but was adapted specifically in this work to the Space Shuttle Main Engine (SSME). The system is applied to idealized data resulting from turbomachinery malfunction in the SSME.

Cost, Thomas L.↗

Precision Landing Navigation Performance of Human-Scale Lunar and Mars Landers

To meet the unique challenges of crewed Lunar and Mars precision landings, NASA’s Safe and Precise Landing Integrated Capabilities Evolution project has worked to advance autonomous spacecraft navigation by increasing the technology readiness level of key deorbit, entry, descent, and landing systems, including navigation sensors. Different sensors and their effects on overall system performance are evaluated using six-degree-of-freedom simulations with physics-based engineering models that capture the relevant vehicle systems and environmental effects. Building on an existing simulation framework, this work demonstrates how improved modeling fidelity enables rapid and detailed assessment of various navigation sensors on human-scale Lunar and Mars landing vehicles using NASA reference architectures.

navigation↗

Flex Fuel Optimized SI and HCCI Engine

The central objective of the proposed work is to demonstrate an HCCI (homogeneous charge compression ignition) capable SI (spark ignited) engine that is capable of fast and smooth mode transition between SI and HCCI combustion modes. The model-based control technique was used to develop and validate the proposed control strategy for the fast and smooth combustion mode transition based upon the developed control-oriented engine; and an HCCI capable SI engine was designed and constructed using production ready two-step valve-train with electrical variable valve timing actuating system. Finally, smooth combustion mode transition was demonstrated on a metal engine within eight engine cycles. The Chrysler turbocharged 2.0L I4 direct injection engine was selected as the base engine for the project and the engine was modified to fit the two-step valve with electrical variable valve timing actuating system. To develop the model-based control strategy for stable HCCI combustion and smooth combustion mode transition between SI and HCCI combustion, a control-oriented real-time engine model was developed and implemented into the MSU HIL (hardware-in-the-loop) simulation environment. The developed model was used to study the engine actuating system requirement for the smooth and fast combustion mode transition and to develop the proposed mode transition control strategy. Finally, a single cylinder optical engine was designed and fabricated for studying the HCCI combustion characteristics. Optical engine combustion tests were conducted in both SI and HCCI combustion modes and the test results were used to calibrate the developed control-oriented engine model. Intensive GT-Power simulations were conducted to determine the optimal valve lift (high and low) and the cam phasing range. Delphi was selected to be the supplier for the two-step valve-train and Denso to be the electrical variable valve timing system supplier. A test bench was constructed to develop control strategies for the electrical variable valve timing (VVT) actuating system and satisfactory electrical VVT responses were obtained. Target engine control system was designed and fabricated at MSU for both single-cylinder optical and multi-cylinder metal engines. Finally, the developed control-oriented engine model was successfully implemented into the HIL simulation environment. The Chrysler 2.0L I4 DI engine was modified to fit the two-step vale with electrical variable valve timing actuating system. A used prototype engine was used as the base engine and the cylinder head was modified for the two-step valve with electrical VVT actuating system. Engine validation tests indicated that cylinder #3 has very high blow-by and it cannot be reduced with new pistons and rings. Due to the time constraint, it was decided to convert the four-cylinder engine into a single cylinder engine by blocking both intake and exhaust ports of the unused cylinders. The model-based combustion mode transition control algorithm was developed in the MSU HIL simulation environment and the Simulink based control strategy was implemented into the target engine controller. With both single-cylinder metal engine and control strategy ready, stable HCCI combustion was achived with COV of 2.1% Motoring tests were conducted to validate the actuator transient operations including valve lift, electrical variable valve timing, electronic throttle, multiple spark and injection controls. After the actuator operations were confirmed, 15-cycle smooth combustion mode transition from SI to HCCI combustion was achieved; and fast 8-cycle smooth combustion mode transition followed. With a fast electrical variable valve timing actuator, the number of engine cycles required for mode transition can be reduced down to five. It was also found that the combustion mode transition is sensitive to the charge air and engine coolant temperatures and regulating the corresponding temperatures to the target levels during the combustion mode transition is the key for a smooth combustion mode transition. As a summary, the proposed combustion mode transition strategy using the hybrid combustion mode that starts with the SI combustion and ends with the HCCI combustion was experimentally validated on a metal engine. The proposed model-based control approach made it possible to complete the SI-HCCI combustion mode transition within eight engine cycles utilizing the well controlled hybrid combustion mode. Without intensive control-oriented engine modeling and HIL simulation study of using the hybrid combustion mode during the mode transition, it would be impossible to validate the proposed combustion mode transition strategy in a very short period.

33 ADVANCED PROPULSION SYSTEMS↗

A systems engineering analysis of three-point and four-point wind turbine drivetrain configurations

This study compares the impact of drivetrain configuration on the mass and capital cost of a series of wind turbines ranging from 1.5 MW to 5.0 MW power ratings for both land-based and offshore applications. The analysis is performed with a new physics-based drivetrain analysis and sizing tool, Drive Systems Engineering (DriveSE), which is part of the Wind-Plant Integrated System Design & Engineering Model. DriveSE uses physics-based relationships to size all major drivetrain components according to given rotor loads simulated based on International Electrotechnical Commission design load cases. The model's sensitivity to input loads that contain a high degree of variability was analyzed. Aeroelastic simulations are used to calculate the rotor forces and moments imposed on the drivetrain for each turbine design. DriveSE is then used to size all of the major drivetrain components for each turbine for both three-point and four-point configurations. The simulation results quantify the trade-offs in mass and component costs for the different configurations. On average, a 16.7% decrease in total nacelle mass can be achieved when using a three-point drivetrain configuration, resulting in a 3.5% reduction in turbine capital cost. This analysis is driven by extreme loads and does not consider fatigue. Thus, the effects of configuration choices on reliability and serviceability are not captured. Furthermore, a first order estimate of the sizing, dimensioning and costing of major drivetrain components are made which can be used in larger system studies which consider trade-offs between subsystems such as the rotor, drivetrain and tower.

17 WIND ENERGY↗

On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data Results

Self-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.

Prather, Maurice↗

Physically-based control-oriented modeling for turbocharged stoichiometric spark-ignited engine with cooled EGR and flexible VVT systems

Accurate estimation and prediction of engine gas exchange system and in-cylinder conditions are critical for spark-ignited engine control and diagnostic algorithm development. In this paper, a physically-based, control-oriented model for a 2.8 l turbocharged, variable valve timing (VVT) and low pressure (LP) exhaust gas recirculation (EGR)-utilizing SI engine was developed. The model includes the impact of modulation to any combination of 10 actuators, including the throttle valve, compressor bypass valve, fueling rate, waste-gate, LP EGR valve, number of deactivated cylinders, intake valve open (IVO) timing, intake valve close (IVC) timing, exhaust valve open (EVO) timing and exhaust valve close (EVC) timing. The accuracy of the model in capturing engine dynamics was demonstrated by validating it against high-fidelity engine GT-Power simulation results for various drive cycles, particularly emphasizing elevated loads. In comparison to the open literature, novel contributions of the effort described in this paper includes in-cylinder gas composition modeling and turbine-out pressure estimation.

Zhang, Xu↗

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Schwabacher, Mark A.↗

JacketSE: An Offshore Wind Turbine Jacket Sizing Tool; Theory Manual and Sample Usage with Preliminary Validation

This manual summarizes the theory and preliminary verifications of the JacketSE module, which is an offshore jacket sizing tool that is part of the Wind-Plant Integrated System Design & Engineering Model toolbox. JacketSE is based on a finite-element formulation and on user-prescribed inputs and design standards' criteria (constraints). The physics are highly simplified, with a primary focus on satisfying ultimate limit states and modal performance requirements. Preliminary validation work included comparing industry data and verification against ANSYS, a commercial finite-element analysis package. The results are encouraging, and future improvements to the code are recommended in this manual.

17 WIND ENERGY↗

Process-Based Balance-of-System Cost Modeling for Offshore Wind Power Plants in the United States: Preprint

This work describes the development of a process based and open source balance of system cost model which provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute the times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays due to weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation; installation times are shown to agree with real data with relative errors of less than 35\%. Case studies are presented to demonstrate the functionality of the model. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. This quantifies the cost benefit tradeoffs of decreasing number of turbines, increased turbine spacing, and fewer turbine terminations and shows a net cost savings. These results demonstrate that the BOS model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗