Modeling Spacesuit-Human Interaction for Injury Risk Identification
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Garima Gupta↗
SEARCH · Engineering Papers
Results for “model identification”
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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Post landing design and testing of an ACRV model
Consideration is given to a 1990-1991 program concentrated on the design, building, and testing of a one-fifth scale model of the egress and stabilization systems for an Apollo Command Module (ACM)-based assured crew return vehicle (ACRV). The program is aimed at determining the feasibility of 1) stabilizing the ACRV out of the range of motions which cause space sickness and 2) the safe and rapid removaling of a sick or injured crewmember from the ACRV. Research have been conducted in the following areas: ACRV model construction, water test facility identification, and stabilization control systems. The fidelity of the model has been established from geometric and dynamic characteristic tests performed on the model.
Hosterman, Kenneth C.↗
Experimental Characterization of an Electric Ducted Fan for the SUSAN 25% Scale Research Vehicle
An electric ducted fan (EDF) was tested in the NASA Langley 12-Foot Low-Speed Tunnel for the SUbsonic Single Aft eNgine (SUSAN) Electrofan 25% scale research vehicle, which incorporates distributed electric fans along the wings and serves as a scaled electrified transport aircraft testbed. The commercial-off-the-shelf EDF was selected as a propulsor that can meet the 25% scale vehicle geometry constraints, along with the performance requirements throughout the flight profile. The test included a series of one-factor-at-a-time (OFAT) and design of experiments (DOE) approaches that were implemented across a range of fan speed, voltage, freestream dynamic pressure, and incidence angle settings to characterize the performance of the EDF. Several test matrix designs and modeling approaches were considered. System identification methods were used to develop a static motor model, a dynamic motor model, an EDF thrust model, and a power consumption model. The model predictive capabilities were then evaluated with validation data not used in the modeling process. The results provide a comprehensive set of models developed to characterize the fan, and offer general insight into EDF modeling approaches.
electric ducted fan↗
Adaptive model reduction for continuous systems via recursive rational interpolation
A method for adaptive identification of reduced-order models for continuous stable SISO and MIMO plants is presented. The method recursively finds a model whose transfer function (matrix) matches that of the plant on a set of frequencies chosen by the designer. The algorithm utilizes the Moving Discrete Fourier Transform (MDFT) to continuously monitor the frequency-domain profile of the system input and output signals. The MDFT is an efficient method of monitoring discrete points in the frequency domain of an evolving function of time. The model parameters are estimated from MDFT data using standard recursive parameter estimation techniques. The algorithm has been shown in simulations to be quite robust to additive noise in the inputs and outputs. A significant advantage of the method is that it enables a type of on-line model validation. This is accomplished by simultaneously identifying a number of models and comparing each with the plant in the frequency domain. Simulations of the method applied to an 8th-order SISO plant and a 10-state 2-input 2-output plant are presented. An example of on-line model validation applied to the SISO plant is also presented.
Lilly, John H.↗
Land-use analysis using infrastructure representations and high-resolution flood inundation mapping techniques
In the face of climate change and population growth in coastal regions, land-use analysis efforts are more challenging than ever. Land-use decision-makers in coastal communities are burdened with the difficult choices of where to place new homes versus other assets. While there has been an increased focus on hazard mitigation and disaster resilience in the field of planning, evidence points towards continued development in risk-prone areas including flood zones. Residential development within flood zones specifically continues to be a major issue. To help counter this trend, this study introduces a novel land-use analysis method, coupling topographic flood inundation mapping techniques with digital elevation model (DEM) adaptations. This Topographic Model Scenario Generation workflow can be used by planners early in the land-use decision making process and provides an alternative to high-computational hydraulic models. The analysis also includes the identification of strengths and weaknesses of topographic models' recognition of built infrastructure assets, adding to a limited body of knowledge addressing recommended uses of such models. Levees and canals prove particularly functional in this context while detention ponds less so, likely due to a lack of total water mass accountability. Lastly, we provide a functional demonstration in Southeast Texas to illustrate the workflow's ability to create multiple infrastructure scenarios and visualize their effects across different flood events.
42 ENGINEERING↗
Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model
The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.
54 ENVIRONMENTAL SCIENCES↗
Performance Evaluation and Parameter Identification on DROID III
The DROID III project consisted of two main parts. The former, performance evaluation, focused on the performance characteristics of the aircraft such as lift to drag ratio, thrust required for level flight, and rate of climb. The latter, parameter identification, focused on finding the aerodynamic coefficients for the aircraft using a system that creates a mathematical model to match the flight data of doublet maneuvers and the aircraft s response. Both portions of the project called for flight testing and that data is now available on account of this project. The conclusion of the project is that the performance evaluation data is well-within desired standards but could be improved with a thrust model, and that parameter identification is still in need of more data processing but seems to produce reasonable results thus far.
Plumb, Julianna J.↗
Comparison of frequency-domain and time-domain rotorcraft vibration control methods
Active control of rotor-induced vibration in rotorcraft has received significant attention recently. Two classes of techniques have been proposed. The more developed approach works with harmonic analysis of measured time histories and is called the frequency-domain approach. The more recent approach computes the control input directly using the measured time history data and is called the time-domain approach. The report summarizes the results of a theoretical investigation to compare the two approaches. Five specific areas were addressed: (1) techniques to derive models needed for control design (system identification methods), (2) robustness with respect to errors, (3) transient response, (4) susceptibility to noise, and (5) implementation difficulties. The system identification methods are more difficult for the time-domain models. The time-domain approach is more robust (e.g., has higher gain and phase margins) than the frequency-domain approach. It might thus be possible to avoid doing real-time system identification in the time-domain approach by storing models at a number of flight conditions. The most significant error source is the variation in open-loop vibrations caused by pilot inputs, maneuvers or gusts. The implementation requirements are similar except that the time-domain approach can be much simpler to implement if real-time system identification were not necessary.
Gupta, N. K.↗
Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.
This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.
42 ENGINEERING↗
Parameterized Linear Longitudinal Airship Model
A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics
Kulczycki, Eric↗
Discovery of TAK-981, a First-in-Class Inhibitor of SUMO-Activating Enzyme for the Treatment of Cancer
SUMOylation is a reversible post-translational modification that regulates protein function through covalent attachment of small ubiquitin-like modifier (SUMO) proteins. The process of SUMOylating proteins involves an enzymatic cascade, the first step of which entails the activation of a SUMO protein through an ATP-dependent process catalyzed by SUMO-activating enzyme (SAE). Here, we describe the identification of TAK-981, a mechanism-based inhibitor of SAE which forms a SUMO–TAK-981 adduct as the inhibitory species within the enzyme catalytic site. Optimization of selectivity against related enzymes as well as enhancement of mean residence time of the adduct were critical to the identification of compounds with potent cellular pathway inhibition and ultimately a prolonged pharmacodynamic effect and efficacy in preclinical tumor models, culminating in the identification of the clinical molecule TAK-981.
60 APPLIED LIFE SCIENCES↗
Model verification of large structural systems
A computer program for the application of parameter identification on the structural dynamic models of space shuttle and other large models with hundreds of degrees of freedom is described. Finite element, dynamic, analytic, and modal models are used to represent the structural system. The interface with math models is such that output from any structural analysis program applied to any structural configuration can be used directly. Processed data from either sine-sweep tests or resonant dwell tests are directly usable. The program uses measured modal data to condition the prior analystic model so as to improve the frequency match between model and test. A Bayesian estimator generates an improved analytical model and a linear estimator is used in an iterative fashion on highly nonlinear equations. Mass and stiffness scaling parameters are generated for an improved finite element model, and the optimum set of parameters is obtained in one step.
Lee, L. T.↗
Parameter identification of material constants in a composite shell structure
One of the basic requirements in engineering analysis is the development of a mathematical model describing the system. Frequently comparisons with test data are used as a measurement of the adequacy of the model. An attempt is typically made to update or improve the model to provide a test verified analysis tool. System identification provides a systematic procedure for accomplishing this task. The terms system identification, parameter estimation, and model correlation all refer to techniques that use test information to update or verify mathematical models. The goal of system identification is to improve the correlation of model predictions with measured test data, and produce accurate, predictive models. For nonmetallic structures the modeling task is often difficult due to uncertainties in the elastic constants. A finite element model of the shell was created, which included uncertain orthotropic elastic constants. A modal survey test was then performed on the shell. The resulting modal data, along with the finite element model of the shell, were used in a Bayes estimation algorithm. This permitted the use of covariance matrices to weight the confidence in the initial parameter values as well as confidence in the measured test data. The estimation procedure also employed the concept of successive linearization to obtain an approximate solution to the original nonlinear estimation problem.
Martinez, David R.↗
The human controller in car following
The man machine interface between the human driver and his automobile during car following tasks was examined. A direct connection between models of the human operator and the theory of optimal control was established for car following situations involving both linear and nonlinear car dynamics. Results obtained from several types of mathematical models are discussed. Conventional parameter identification techniques were used to obtain the parameters of these models by comparing their performance to data obtained by aerial photogrammetry. The results indicate that there are two general classes of model structures: models assumed to have preview information and models without preview.
Burnham, G. O.↗
A Review of System Identification Methods Applied to Aircraft
Airplane identification, equation error method, maximum likelihood method, parameter estimation in frequency domain, extended Kalman filter, aircraft equations of motion, aerodynamic model equations, criteria for the selection of a parsimonious model, and online aircraft identification are addressed.
Klein, V.↗
VESIcal Part I: An open-source thermodynamic model engine for mixed volatile (H2O-CO2) solubility in silicate melts
Thermodynamics has been fundamental to the interpretation of geologic data and modeling of geologic systems for decades. However, more recent advancements in computational capabilities and a marked increase in researchers’ accessibility to computing tools has outpaced the functionality and extensibility of currently available modeling tools. Here we present VESIcal (Volatile Equilibria and Saturation Identification calculator): the first comprehensive modeling tool for H 2 O, CO 2 , and mixed (H 2 O-CO 2 ) solubility in silicate melts that: a) allows users access to seven commonly used models, plus easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an excel spreadsheet for simple post-modeling analysis; e) integrates advanced plotting capabilities directly within the tool; and f) provides all of these within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python. The tool is presented within this manuscript, which is a Jupyter notebook containing worked examples accessible to python users with a range of skill levels. The basic functions of VESIcal can also be access via a web app (https://vesical.anvil.app). The VESIcal python library is open-source and available for download at https://github.com/kaylai/VESIcal.
K. Iacovino↗
Anomaly Detection and Identification Using a Leave-One-Variable-Out Method
At nuclear power plants (NPPs), anomaly detection and identification (i.e., determining the causes of anomalies) are important tasks for ensuring the safe and efficient operation of NPPs. These tasks are currently labor-intensive and costly, and are made more difficult by the size and complexity of NPP systems. An alternative approach to conducting these tasks is to automate them, such as via the reconstruction-based contribution method, which is a well-researched unsupervised machine learning method that uses a data-driven model of anomaly-free behavior to detect events and then identify each variable’s contributions to those events. The present effort developed a novel contribution approach that utilized a leave-one-variable-out (LOVO) model, with which each variable is predicted using all the other variables. The novelty lay in transforming this model into a reconstruction model and modifying the identification algorithm to work with the new reconstruction model. To evaluate this method in a controlled environment, a synthetic dataset based on spring-mass-damper (SMD) systems (commonly found in mechanical engineering references) was used, with known anomalies introduced into the system. The proposed method successfully detected the anomalies and afforded insights into their causes, thus enabling the appropriate identifications to be made.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE: Integrating Southwest Power Pool Wind Energy into Southeast Electricity Markets
Wind power development in the United States is outpacing previous estimates for many regions, particularly those with good wind resources. The pace of wind power deployment may soon outstrip regional capabilities to provide transmission and integration services to achieve the most economic power system operation. Conversely, regions such as the Southeastern United States do not have good wind resources and will have difficulty meeting proposed federal Renewable Portfolio Standards with local supply. There is a growing need to explore innovative solutions for collaborating between regions to achieve the least cost solution for meeting such a renewable energy mandate. The DOE-funded project 'Integrating Southwest Power Pool Wind Energy into Southeast Electricity Markets' aims to evaluate the benefits of coordination of scheduling and balancing for Southwest Power Pool (SPP) wind transfers to Southeastern Electric Reliability Council (SERC) Balancing Authorities (BAs). The primary objective of this project is to analyze the benefits of different balancing approaches with increasing levels of inter-regional cooperation. Scenarios were defined, modeled and investigated to address production variability and uncertainty and the associated balancing of large quantities of wind power in SPP and delivery to energy markets in the southern regions of the SERC. The primary analysis of the project is based on unit commitment (UC) and economic dispatch (ED) simulations of the SPP-SERC regions as modeled for the year 2022. The UC/ED models utilized for the project were developed through extensive consultation with the project utility partners, to ensure the various regions and operational practices are represented as accurately as possible realizing that all such future scenario models are quite uncertain. SPP, Entergy, Oglethorpe Power Company (OPC), Southern Company, and the Tennessee Valley Authority (TVA) actively participated in the project providing input data for the models and review of simulation results and conclusions. While other SERC utility systems are modeled, the listed SERC utilities were explicitly included as active participants in the project due to the size of their load and relative proximity to SPP for importing wind energy. The analysis aspects of the project comprised 4 primary tasks: (1) Development of SCUC/SCED model of the SPP-SERC footprint for the year 2022 with only 7 GW of installed wind capacity in SPP for internal SPP consumption with no intended wind exports to SERC. This model is referred to as the 'Non-RES' model as it does not reflect the need for the SPP or SERC BAs to meet a federal Renewable Energy Standard (RES). (2) Analysis of hourly-resolution simulation results of the Non-RES model for the year 2022 to provide project stakeholders with confidence in the model and analytical framework for a scenario that is similar to the existing system and more easily evaluated than the high-wind transfer scenarios that are analyzed subsequently. (3) Development of SCUC/SCED model of the SPP-SERC footprint for the year 2022 with sufficient installed wind capacity in SPP (approximately 48 GW) for both SPP and the participating SERC BAs to meet an RES of 20% energy. This model is referred to as the 'High-Wind Transfer' model with several different scenarios represented. The development of the High-Wind Transfer model not only included identification and allocation of SPP wind to individual SERC BAs, but also included the evaluation of various methods to allow the model to export the SPP wind to SERC without developing an actual transmission plan to support the transfers. (4) Analysis of hourly-resolution simulation results of several different High-Wind Transfer model scenarios for the year 2022 to determine balancing costs and potential benefits of collaboration among SPP and SERC BAs to provide the required balancing.
17 WIND ENERGY↗