Model Based Systems Engineering (MBSE)
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Interannual to Decadal Variability in Subarctic Atlantic Ocean Primary Productivity Historical Variability, Dynamics, and Response to Warming
Phytoplankton primary productivity in the Subarctic Atlantic Ocean sustains valuable fisheries and exports anthropogenic atmospheric carbon dioxide, but multiple Earth system models show that this productivity declines substantially in 21st century global warming scenarios. Prior studies have investigated the spatial and temporal dynamics of the seasonal cycle of the phytoplankton, which exhibit a prominent but spatially variable spring bloom that is caused by the closely related seasonal cycles in solar radiation and vertical mixing that modulate both phytoplankton growth and loss rates. However, recent work indicates that multi-decade declines in this spring bloom with global warming in multiple Earth system models are driven by reductions in circulation of nutrients from the subtropical and tropical thermocline, rather than local changes in vertical mixing or shortwave radiation in the Subarctic. It is unclear if current models of how phytoplankton productivity varies seasonally or over a century in global warming can be interpolated to explain the interannual to decadal variability. In this poster, I will quantify the interannual to decadal variability of phytoplankton chlorophyll using historical satellite ocean color observations and model simulations with the Community Earth System Model. I will then use the observations and model simulations to elucidate the mechanisms of interannual to decadal variability and how that variability is restructured in 21st century global warming scenarios.
nterannual↗
A COMPACT model reduction methodology for articulated, multi-flexible bodies structures
To simulate the dynamical motion of articulated, multiflexible body structures, one can use multibody simulation packages such as DISCOS. To this end, one need appropriate reduced-order models for all the flexible components involved. The component modes projection and assembly model reduction methodology is one way to construct these reduced-order component models. However, the generated reduced-order system models typically contain high frequency extraneous modes. The presence of high frequency extraneous modes in a reduced-order system model forces us to use a small stepsize in the numerical integration of that model, resulting in an increase in the elapsed time of the integration process. To eliminate these high-frequency modes, we first identify and discard the component modes that 'contributed' to the generations of these modes. A sensitivity analysis is then used to determine how the remaining component modes should be perturbed in order to still closely capture the selected system modes. The effectiveness of the proposed methodology has been successfully verified using a finite-element model of the Galileo spacecraft.
Lee, Allan Y.↗
Updates and Correlation of EMU System-Level Model (SINDA EMU)
During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. One of the primary methods of determining the likely cause of this failure was through a comparison of EVA 80 to other historical EVAs using an analytical approach. The Systems Improved Numerical Differential Analysis EMU model (SINDA EMU) is a system-level model of the EMU that was used in this investigation. SINDA EMU was initially developed and correlated to test data in the 1980s. Since its conception, SINDA EMU has been continually adjusted based on new test data and changes to the EMU design. To support the water in the helmet investigation, SINDA EMU needed to be further updated and recorrelated to ensure accurate results. These changes included changing the primary carbon dioxide (CO2) removal technology, implementing logic to allow for re-evaporation of sweat runoff from the liquid cooling and ventilation garment (LCVG), and improving the transient modeling capabilities. To validate the implementation of these adjustments, SINDA EMU was correlated to test data from the 1990s and human-in-the-loop (HITL) testing from 2014. These updates and correlation efforts proved that SINDA EMU is an effective tool for investigating the EVA 80 water in the helmet failure event.
Noah Lial Andersen↗
Identifying Bearing Rotordynamic Coefficients using an Extended Kalman Filter
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
Miller, Bard A.↗
Identifying Bearing Rotordynamic Coefficients using an Extended Kalman Filter
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
Miller, Brad A.↗
Identifying Bearing Rotodynamic Coefficients Using an Extended Kalman Filter
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter's performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
Miller, Brad A.↗
Optical systems integrated modeling
An integrated modeling capability that provides the tools by which entire optical systems and instruments can be simulated and optimized is a key technology development, applicable to all mission classes, especially astrophysics. Many of the future missions require optical systems that are physically much larger than anything flown before and yet must retain the characteristic sub-micron diffraction limited wavefront accuracy of their smaller precursors. It is no longer feasible to follow the path of 'cut and test' development; the sheer scale of these systems precludes many of the older techniques that rely upon ground evaluation of full size engineering units. The ability to accurately model (by computer) and optimize the entire flight system's integrated structural, thermal, and dynamic characteristics is essential. Two distinct integrated modeling capabilities are required. These are an initial design capability and a detailed design and optimization system. The content of an initial design package is shown. It would be a modular, workstation based code which allows preliminary integrated system analysis and trade studies to be carried out quickly by a single engineer or a small design team. A simple concept for a detailed design and optimization system is shown. This is a linkage of interface architecture that allows efficient interchange of information between existing large specialized optical, control, thermal, and structural design codes. The computing environment would be a network of large mainframe machines and its users would be project level design teams. More advanced concepts for detailed design systems would support interaction between modules and automated optimization of the entire system. Technology assessment and development plans for integrated package for initial design, interface development for detailed optimization, validation, and modeling research are presented.
Shannon, Robert R.↗
Systems Engineering Model and Training Application for Desktop Environment
Provide a graphical user interface based simulator for desktop training, operations and procedure development and system reference. This simulator allows for engineers to train and further understand the dynamics of their system from their local desktops. It allows the users to train and evaluate their system at a pace and skill level based on the user's competency and from a perspective based on the user's need. The simulator will not require any special resources to execute and should generally be available for use. The interface is based on a concept of presenting the model of the system in ways that best suits the user's application or training needs. The three levels of views are Component View, the System View (overall system), and the Console View (monitor). These views are portals into a single model, so changing the model from one view or from a model manager Graphical User Interface will be reflected on all other views.
May, Jeffrey T.↗
Control by model error estimation
Modern control theory relies upon the fidelity of the mathematical model of the system. Truncated modes, external disturbances, and parameter errors in linear system models are corrected by augmenting to the original system of equations an 'error system' which is designed to approximate the effects of such model errors. A Chebyshev error system is developed for application to the Large Space Telescope (LST).
Likins, P. W.↗
Modeling Entry Systems to Explore Our Solar System
Exploration of our Solar System is a foundational element of NASA’s identity. Delivering a scientific payload through an atmosphere to the surface of a planetary body requires safely navigating the extreme temperatures and stresses generated by flying many times the speed of sound. An entry system is the outer shell of a vehicle designed to protect the payload and, as a single point of failure for a mission, reliability is paramount. Unfortunately, it is not possible to fully replicate the flight environment in ground test facilities – so how do we confidently design a vehicle that needs to work the first time, every time? Modeling and simulation are critical tools for filling gaps in ground test capability and providing traceability from ground to flight. Modeling an entry system is a truly interdisciplinary effort, requiring knowledge of fluid dynamics, high-temperature chemistry, radiation, materials science, structural dynamics, guidance and control – and, finally, the mathematical and computing capability to pull it all together. In this talk, Dr. Michael Barnhardt will discuss the latest research in modeling entry systems and how it is being used in NASA’s exploration missions.
Entry systems↗
Frequency response approach to design of adaptive control systems via model of specifications
Frequency response approach to adaptive control systems design by translating from time to frequency domain specifications
Oda, N. T.↗
Modeling of linear isentropic flow systems
A modeling approach for linear isentropic flow systems based on the quasi-one-dimensional Euler equations of non-viscous, compressible flow are presented. Such systems are representative of certain high speed propulsion systems. Accurate models useful in control system studies are developed. A supersonic inlet is considered, and the resulting set of partial differential equations with boundary conditions is solved for a linear transfer matrix using Laplace transforms.
Sarantopoulos, Athan D.↗
Modeling of linear isentropic flow systems
A modeling approach for linear isentropic flow systems based on the quasi-one-dimensional Euler equations of non-viscous, compressible flow are presented. Such systems are representative of certain high speed propulsion systems. Accurate models useful in control system studies are developed. A supersonic inlet is considered, and the resulting set of partial differential equations with boundary conditions is solved for a linear transfer matrix using Laplace transforms.
Sarantopoulos, Athan D.↗
Single Lens Dual-Aperture 3D Imaging System: Color Modeling
In an effort to miniaturize a 3D imaging system, we created two viewpoints in a single objective lens camera. This was accomplished by placing a pair of Complementary Multi-band Bandpass Filters (CMBFs) in the aperture area. Two key characteristics about the CMBFs are that the passbands are staggered so only one viewpoint is opened at a time when a light band matched to that passband is illuminated, and the passbands are positioned throughout the visible spectrum, so each viewpoint can render color by taking RGB spectral images. Each viewpoint takes a different spectral image from the other viewpoint hence yielding a different color image relative to the other. This color mismatch in the two viewpoints could lead to color rivalry, where the human vision system fails to resolve two different colors. The difference will be closer if the number of passbands in a CMBF increases. (However, the number of passbands is constrained by cost and fabrication technique.) In this paper, simulation predicting the color mismatch is reported.
bipartite filter↗
Extravehicular Mobility Unit System-Level Model (SINDA EMU) Usage for Operational Mitigations in Support of US EVA 80
During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. Through a comparative analysis and Test, Teardown, and Evaluation (TT&E) of this EMU, the most likely cause of the US EVA 80 water failure was determined to be sublimator carryover caused by a comparatively high latent load (water vapor production by the crewmember). High latent load can be reduced by the crewmember adjusting the thermal control valve (TCV) setting on the EMU to prevent the onset of significant sweating. To reduce the risk of high latent load leading to water in the helmet, a potential warning system was developed using the Systems Improved Numerical Differencing Analyzer EMU model (SINDA EMU). The goal of this warning system is to alert the crewmember when they are producing a high latent load and recommend adjustment of the TCV to increase cooling. This warning system was designed to ensure high risk conditions are avoided while simultaneously preventing a system that warns the crewmember too frequently. Theoretical tests of the warning system through modeling calculated that if the warning system were used during US EVA 80, the total latent load could have been reduced by up to 33% which would have significantly reduced the risk of water in the helmet. This analysis also investigated the effectiveness of the warning system on EVAs that occurred after US EVA 80.
Noah Andersen↗
Demonstration of Effects on Tropical Cyclone Forecasts with a High Resolution Global Model from Variation in Cumulus Convection Parameterization
The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models that have been developed at Goddard Space Flight Center to support NASA's earth science research in data analysis, observing system modeling and design, climate and weather prediction, and basic research. The work presented used GEOS-5 with 0.25o horizontal resolution and 72 vertical levels (up to 0.01 hP) resolving both the troposphere and stratosphere, with closer packing of the levels close to the surface. The model includes explicit (grid-scale) moist physics, as well as convective parameterization schemes. Results will be presented that will demonstrate strong dependence in the results of modeling of a strong hurricane on the type of convective parameterization scheme used. The previous standard (default) option in the model was the Relaxed Arakawa-Schubert (RAS) scheme, which uses a quasi-equilibrium closure. In the cases shown, this scheme does not permit the efficient development of a strong storm in comparison with observations. When this scheme is replaced by a modified version of the Kain-Fritsch scheme, which was originally developed for use on grids with intervals of order 25 km such as the present one, the storm is able to develop to a much greater extent, closer to that of reality. Details of the two cases will be shown in order to elucidate the differences in the two modeled storms.
Miller, Timothy L.↗
Mass balances for a biological life support system simulation model
Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.
Volk, Tyler↗