Department of Energy Models Based Integrated Tools PTC Corporate Overview
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42 ENGINEERING↗
SEARCH · Engineering Papers
Results for “model based engineering”
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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Particle Filtering for Model-Based Anomaly Detection in Sensor Networks
A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.
Solano, Wanda↗
Facilitating Analysis of Multiple Partial Data Streams
Robotic Operations Automation: Mechanisms, Imaging, Navigation report Generation (ROAMING) is a set of computer programs that facilitates and accelerates both tactical and strategic analysis of time-sampled data especially the disparate and often incomplete streams of Mars Explorer Rover (MER) telemetry data described in the immediately preceding article. As used here, tactical refers to the activities over a relatively short time (one Martian day in the original MER application) and strategic refers to a longer time (the entire multi-year MER missions in the original application). Prior to installation, ROAMING must be configured with the types of data of interest, and parsers must be modified to understand the format of the input data (many example parsers are provided, including for general CSV files). Thereafter, new data from multiple disparate sources are automatically resampled into a single common annotated spreadsheet stored in a readable space-separated format, and these data can be processed or plotted at any time scale. Such processing or plotting makes it possible to study not only the details of a particular activity spanning only a few seconds, but also longer-term trends. ROAMING makes it possible to generate mission-wide plots of multiple engineering quantities [e.g., vehicle tilt as in Figure 1(a), motor current, numbers of images] that, heretofore could be found only in thousands of separate files. ROAMING also supports automatic annotation of both images and graphs. In the MER application, labels given to terrain features by rover scientists and engineers are automatically plotted in all received images based on their associated camera models (see Figure 2), times measured in seconds are mapped to Mars local time, and command names or arbitrary time-labeled events can be used to label engineering plots, as in Figure 1(b).
Maimone, Mark W.↗
Mathematical description of complex chemical kinetics and application to CFD modeling codes
A major effort in combustion research at the present time is devoted to the theoretical modeling of practical combustion systems. These include turbojet and ramjet air-breathing engines as well as ground-based gas-turbine power generating systems. The ability to use computational modeling extensively in designing these products not only saves time and money, but also helps designers meet the quite rigorous environmental standards that have been imposed on all combustion devices. The goal is to combine the very complex solution of the Navier-Stokes flow equations with realistic turbulence and heat-release models into a single computer code. Such a computational fluid-dynamic (CFD) code simulates the coupling of fluid mechanics with the chemistry of combustion to describe the practical devices. This paper will focus on the task of developing a simplified chemical model which can predict realistic heat-release rates as well as species composition profiles, and is also computationally rapid. We first discuss the mathematical techniques used to describe a complex, multistep fuel oxidation chemical reaction and develop a detailed mechanism for the process. We then show how this mechanism may be reduced and simplified to give an approximate model which adequately predicts heat release rates and a limited number of species composition profiles, but is computationally much faster than the original one. Only such a model can be incorporated into a CFD code without adding significantly to long computation times. Finally, we present some of the recent advances in the development of these simplified chemical mechanisms.
Bittker, D. A.↗
Mathematical Description of Complex Chemical Kinetics and Application to CFD Modeling Codes
A major effort in combustion research at the present time is devoted to the theoretical modeling of practical combustion systems. These include turbojet and ramjet air-breathing engines as well as ground-based gas-turbine power generating systems. The ability to use computational modeling extensively in designing these products not only saves time and money, but also helps designers meet the quite rigorous environmental standards that have been imposed on all combustion devices. The goal is to combine the very complex solution of the Navier-Stokes flow equations with realistic turbulence and heat-release models into a single computer code. Such a computational fluid-dynamic (CFD) code simulates the coupling of fluid mechanics with the chemistry of combustion to describe the practical devices. This paper will focus on the task of developing a simplified chemical model which can predict realistic heat-release rates as well as species composition profiles, and is also computationally rapid. We first discuss the mathematical techniques used to describe a complex, multistep fuel oxidation chemical reaction and develop a detailed mechanism for the process. We then show how this mechanism may be reduced and simplified to give an approximate model which adequately predicts heat release rates and a limited number of species composition profiles, but is computationally much faster than the original one. Only such a model can be incorporated into a CFD code without adding significantly to long computation times. Finally, we present some of the recent advances in the development of these simplified chemical mechanisms.
Bittker, D. A.↗
Multidisciplinary design optimization in Architecture, Engineering, and Construction: a detailed review and call for collaboration
The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. Herein, we further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
LDEXPT, an intelligent database system for the Composite Load Spectra project
The Composite Load Spectra project develops probabilistic models to simulate the probabilistic loads for selected components of a generic space propulsion system. Tremendous information such as engine load variables and their distributions is needed by the simulation program. An intelligent data base system was constructed and integrated with the probabilistic load simulation program to manage and maintain the knowledge base of the Composite Load Spectra project. The intelligent data base system takes care of the data retrieval and storage functions and has expert knowledge on engine load models and associated engine variables. The integration of the intelligent data base into the load simulation program achieves a smooth coupling between the numeric processing (load simulation calculation) and the symbolic processing (intelligent load information management).
Ho, H.↗
Analytical prediction of the performance and stability of a J85-13 compressor with distorted inlet flow
The parallel compressor concept was studied using a compressor model based on the overall clean-inlet performance map obtained from experimental tests in an altitude chamber using a General Electric J85-13 turbojet engine. The model, which includes a static-pressure balance calculation at compressor discharge, was exercised at conditions corresponding to 10 different screen-induced distortion patterns included in the experimental data base. The spoiled area of these patterns ranged from 30 deg to 180 deg, and the distortion screen density, or the area blocked by the screen wire per unit area of screen, varied from 26 to 69 percent. The study indicates that at the higher corrected speeds, the analytical surge lines obtained are good representations of the corresponding experimental surge lines and are independent of distortion angle or distortion angle or distortion level.
Milner, E. J.↗
Investigation of thermal-fluid mechanical characteristics of the capillary pump and the pumped two-phase loop
This first semi-annual report summarized progress made on NASA Goddard Space Flight Center (GSFC) Grant NAG 5-834 during the period September 1, 1986 to February 28, 1987. The goal of the project is to gain a better understanding of the transient behavior of the Capillary Pump Loop (CPL) developed and tested by the GSFC. The investigation is directed toward development of analytical models to represent the transient thermal-fluid mechanic processes occurring in different parts of the CPL engineering model. Evaluation of the available test data has been the starting point for the investigation. Based on results of this evaluation, supplementary tests will be conducted by using a CPL test system already operational in the Heat Transfer laboratory of the university. Of particular interest is the oscillatory behavior of the CPL engineering model exhibited during some of the earlier test runs conducted at NASA-GSFC and Johnson Space Center (JSC).
Kiper, Ali M.↗
Intensity measure adequacy assessment for nonlinear site response using Information Theory
Nonlinear site response modeling is a crucial aspect of Probabilistic Seismic Hazard Analysis. Site amplification models routinely rely on a rock intensity measure to characterize the strength of the bedrock motion. However, the adequacy of such intensity measures towards predicting amplifications across the oscillator period range has not been investigated in the literature. This paper analyzes the adequacy of rock intensity measures using state of the art criterion established in Performance-Based Earthquake Engineering and techniques from Information Theory. The efficiency and the sufficiency of several rock intensity measure are assessed. It was found that spectral accelerations at low periods usually are adequate for predicting amplifications across the period range. This supports the current practice of using Peak Ground Acceleration in Ground Motion Models. However, for extremely soft sites, which demonstrate nonlinear effects well into the period range, it is better practice to ensure that amplification and spectral acceleration share the same oscillator period. Lastly, for predicting the peak shear strain (an important parameter that controls nonlinearity of site response), Peak Ground Velocity is generally adequate, and this conclusion is in line with the definition of proxy shear strain.
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IMPLEMENTING THE NFPA 805 PROCESS: Observations of a Technical Reviewer
In June 2004 the U.S. Nuclear Regulatory Commission (NRC) amended its fire protection requirements to permit existing nuclear power reactor licensees to voluntarily adopt fire protection requirements contained in National Fire Protection Association (NFPA) Standard 805. NFPA 805 is a performance-based standard for nuclear power plant fire protection that is an alternative to the deterministic, prescriptive fire protection requirements, such as 10 CFR 50 Appendix R, that was issued in 1980. One aspect of implementing NFPA 805 is that the licensee adopts the performance goals, objectives, and criteria for nuclear safety specified in the Standard. These goals, objectives, and criteria can be met through the implementation of deterministic approaches or performance-based approaches, including engineering analyses, probabilistic risk assessment, and fire modeling. Licensees voluntarily adopting the fire protection requirements in NFPA 805 must submit a license amendment request (LAR) to the NRC. The LAR provides the new proposed fire protection licensing basis, including the methodology and results of required evaluations and analyses that show how the NFPA 805 performance criteria are met. As of August 2014, licensees have submitted LARs for 26 nuclear power plants, representing 42 nuclear reactor units. Of these, 7 nuclear power plants, representing 10 nuclear reactor units, have been issued a safety evaluation (SE) by the NRC approving transition of their fire protection licensing basis to one that complies with NFPA 805. Pacific Northwest National Laboratory (PNNL) supports the NRC staff’s technical review of the LARs in the areas of fundamental fire protection, safe shutdown analysis, and Probabilistic Risk Assessment (PRA). PNNL, of course, cannot speak for the nuclear industry and its choice of implementation strategies or the NRC staff’s assessment of the approaches being taken to adopt NFPA 805. However, as a reviewer of the technical details of these submittals, PNNL is in a position to observe the array of implementation tactics taken in these submittals, and observe different ways licensees are making the NFPA 805 process work. For example, we see differences in how fire areas are being transitioned, the kinds of plant modifications being implemented, the changes being made to plant procedures, the number and types of recovery actions being credited, and the kinds and extent of detailed modeling being performed in support of the Fire PRAs. As a caveat, we note that it is probably too early to comment on the overall success or limitations of the NFPA 805 process or provide lessons learned for the future. Furthermore, it is not our intention to endorse any particular approach taken in a submittal over another or to critique the industry or the regulator. Rather our goal in this paper is to summarize a set of interesting and useful differences across submittals that may provide context for further future discussions about what we (i.e., reviewers, industry, and regulators) have learned in being part of the NFPA process; and how to best use that information to inform future NFPA 805 activities or other risk-informed endeavors.
NFPA 805, PRA, PSA, probabilistic risk assessment,↗
Aerothermo-Structural Analysis of Low Cost Composite Nozzle/Inlet Components
This research is a cooperative effort among the Turbomachinery and Propulsion Division of NASA Glenn, CCMR of NC A&T State University, and the Tuskegee University. The NC A&T is the lead center and Tuskegee University is the participating institution. Objectives of the research were to develop an integrated aerodynamic, thermal and structural analysis code for design of aircraft engine components, such as, nozzles and inlets made of textile composites; conduct design studies on typical inlets for hypersonic transportation vehicles and setup standards test examples and finally manufacture a scaled down composite inlet. These objectives are accomplished through the following seven tasks: (1) identify the relevant public domain codes for all three types of analysis; (2) evaluate the codes for the accuracy of results and computational efficiency; (3) develop aero-thermal and thermal structural mapping algorithms; (4) integrate all the codes into one single code; (5) write a graphical user interface to improve the user friendliness of the code; (6) conduct test studies for rocket based combined-cycle engine inlet; and finally (7) fabricate a demonstration inlet model using textile preform composites. Tasks one, two and six are being pursued. Selected and evaluated NPARC for flow field analysis, CSTEM for in-depth thermal analysis of inlets and nozzles and FRAC3D for stress analysis. These codes have been independently verified for accuracy and performance. In addition, graphical user interface based on micromechanics analysis for laminated as well as textile composites was developed. Demonstration of this code will be made at the conference. A rocket based combined cycle engine was selected for test studies. Flow field analysis of various inlet geometries were studied. Integration of codes is being continued. The codes developed are being applied to a candidate example of trailblazer engine proposed for space transportation. A successful development of the code will provide a simpler, faster and user-friendly tool for conducting design studies of aircraft and spacecraft engines, applicable in high speed civil transport and space missions.
Shivakumar, Kuwigai↗
Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty
This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parameters as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about 28% of incremental oil recovery. The sensitivity analysis reduced the number of control variables to decrease computational time. A risk aversion factor was used to represent results at various confidence levels to assist management in the decision-making process. The defined objective functions were proved to be a robust approach to co-optimize oil recovery and CO 2 storage. The Farnsworth CO 2 project will serve as a benchmark for future CO 2 –EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.
54 ENVIRONMENTAL SCIENCES↗
Modal Survey of ETM-3, A 5-Segment Derivative of the Space Shuttle Solid Rocket Booster
The complex interactions between internal motor generated pressure oscillations and motor structural vibration modes associated with the static test configuration of a Reusable Solid Rocket Motor have potential to generate significant dynamic thrust loads in the 5-segment configuration (Engineering Test Motor 3). Finite element model load predictions for worst-case conditions were generated based on extrapolation of a previously correlated 4-segment motor model. A modal survey was performed on the largest rocket motor to date, Engineering Test Motor #3 (ETM-3), to provide data for finite element model correlation and validation of model generated design loads. The modal survey preparation included pretest analyses to determine an efficient analysis set selection using the Effective Independence Method and test simulations to assure critical test stand component loads did not exceed design limits. Historical Reusable Solid Rocket Motor modal testing, ETM-3 test analysis model development and pre-test loads analyses, as well as test execution, and a comparison of results to pre-test predictions are discussed.
Nielsen, D.↗
Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction
Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present paper, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to develop significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Comparing Global Spray Combustion Characteristics and Local Shot-to-Shot Variations in a Reacting n -Heptane Spray
In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained for guidance and validation. For Reynolds-averaged Navier–Stokes (RANS)-based Computational fluid dynamics (CFD) modeling approaches, representative ensemble average experimental results are important. For high-fidelity models such as large eddy simulations (LES)-based CFD, precise individual experimental results are desirable. However, making comparisons between a given experiment and LES is a challenge since local parameters cannot be directly compared. In this work, an optically accessible constant pressure flow rig (CPFR) is utilized to acquire diesel-like fuel injection and reaction behavior simultaneously with three optical diagnostic techniques: rainbow Schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The CPFR allows a large number of repeated injection experiments to be performed for statistical analysis and convergence using ensemble-averaging techniques, while maintaining highly repeatable test conditions. Even for stable test conditions, variations in local turbulent fuel–air mixing introduce variability, which manifests as significant differences in OH* and 2CP results. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, liftoff length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each dataset, are presented and discussed. Finally, a statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the dataset for discussion and analysis of shot-to-shot variations.
42 ENGINEERING↗
On-Board Battery Monitoring and Prognostics for Electric-Propulsion Aircraft
The reliability of the propulsion system of an aircraft is paramount for the aircraft safety and hence the aircraft health must be monitored continuously. In contrast to fuel- operated aircraft, electric battery-operated propulsion system poses specific problems, such as, the remaining battery power does not linearly decrease and cannot be measured directly. In this paper, we describe a combined monitoring and prognostics architecture that can continuously monitor all components of the electric propulsion system with respect to safety and performance properties as well as state of charge and rest of useful life for the battery. Our system combines a detailed electrochemical battery model for Li-ion batteries with a powerful prognostics engine based upon an Unscented Kalman Filter with the R2U2 monitoring device, which provides efficient observers for metric temporal logic and Bayesian reasoning. R2U2 is a real-time, realizable, responsive, unobtrusive unit, which continuously monitors sensor readings, outputs of the prognostics engine, as well as the ight software status for safety, performance, and security properties. We illustrate our architecture with two case studies, one reporting actual ight tests with an X8+ octocopter and the other a software-in-the-loop simulation with an unmanned Edge 540 electric aircraft model.
Kulkarni, Chetan↗
Integrating narratives into decision making for complex systems engineering design issues
Abstract Engineering decision making and design requires collaboration between groups from different disciplines, each with different tools, vocabulary, and concerns. Traditional engineering decision‐making tools are generally based on understanding the decision makers’ values, modeling uncertainty with probability, and selecting the alternative that maximizes utility. This rational approach to decision making may not be well understood or used by many stakeholders involved in the engineering design process. Constructing narratives, a basic means of human communication, may aid in engineering communication and comprehension and help with decision making. Narratives represent events by means of a story and usually include characters or agents who cause events and to whom events happen. This paper recommends three methods for how the use of narrative can be applied to the area of engineering decision making. These methods include connecting the decision maker to the analysis, creating narrative simulations for training decision makers, and fostering consensus in problems with multiple stakeholders. An illustrative example of designing a better cookstove for the developing world demonstrates the role that understanding narratives of various stakeholders can play for accomplishing complex systems engineering.
MacKenzie, Cameron A.↗