System modeling and structure optimization using hybrid computer techniques
Automated modeling and structure optimization of linear dynamic systems and circuits, using hybrid computer techniques and time-domain test data
Beck, C. H.↗
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Results for “Model Optimization”
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Model reduction for the dynamics and control of large structural systems via neutral network processing direct numerical optimization
Three neural network processing approaches in a direct numerical optimization model reduction scheme are proposed and investigated. Large structural systems, such as large space structures, offer new challenges to both structural dynamicists and control engineers. One such challenge is that of dimensionality. Indeed these distributed parameter systems can be modeled either by infinite dimensional mathematical models (typically partial differential equations) or by high dimensional discrete models (typically finite element models) often exhibiting thousands of vibrational modes usually closely spaced and with little, if any, damping. Clearly, some form of model reduction is in order, especially for the control engineer who can actively control but a few of the modes using system identification based on a limited number of sensors. Inasmuch as the amount of 'control spillover' (in which the control inputs excite the neglected dynamics) and/or 'observation spillover' (where neglected dynamics affect system identification) is to a large extent determined by the choice of particular reduced model (RM), the way in which this model reduction is carried out is often critical.
Becus, Georges A.↗
The effects of multiplicative motor noise on the optimal human operator model
The effects of a multiplicative motor noise model on the optimal-control human operator model were analyzed. A study of the interaction between multiplicative motor noise variance, plant dynamics, and predicted operator response behavior shows that, in general, an increase in motor noise variance produces a decrease in operator gain and a decrease in high-frequency remnant. An increase in multiplicative motor noise variance is also reflected by an increase in the effective motor time constant; in the absence of a cost penalty on commanded control, the motor time constant equals the motor noise variance.
Caglayan, A. K.↗
Engineering Overview of a Multidisciplinary HSCT Design Framework Using Medium-Fidelity Analysis Codes
An objective of the HPCC Program at NASA Langley has been to promote the use of advanced computing techniques to more rapidly solve the problem of multidisciplinary optimization of a supersonic transport configuration. As a result, a software system has been designed and is being implemented to integrate a set of existing discipline analysis codes, some of them CPU-intensive, into a distributed computational framework for the design of a High Speed Civil Transport (HSCT) configuration. The proposed paper will describe the engineering aspects of integrating these analysis codes and additional interface codes into an automated design system. The objective of the design problem is to optimize the aircraft weight for given mission conditions, range, and payload requirements, subject to aerodynamic, structural, and performance constraints. The design variables include both thicknesses of structural elements and geometric parameters that define the external aircraft shape. An optimization model has been adopted that uses the multidisciplinary analysis results and the derivatives of the solution with respect to the design variables to formulate a linearized model that provides input to the CONMIN optimization code, which outputs new values for the design variables. The analysis process begins by deriving the updated geometries and grids from the baseline geometries and grids using the new values for the design variables. This free-form deformation approach provides internal FEM (finite element method) grids that are consistent with aerodynamic surface grids. The next step involves using the derived FEM and section properties in a weights process to calculate detailed weights and the center of gravity location for specified flight conditions. The weights process computes the as-built weight, weight distribution, and weight sensitivities for given aircraft configurations at various mass cases. Currently, two mass cases are considered: cruise and gross take-off weight (GTOW). Weights information is obtained from correlations of data from three sources: 1) as-built initial structural and non-structural weights from an existing database, 2) theoretical FEM structural weights and sensitivities from Genesis, and 3) empirical as-built weight increments, non-structural weights, and weight sensitivities from FLOPS. For the aeroelastic analysis, a variable-fidelity aerodynamic analysis has been adopted. This approach uses infrequent CPU-intensive non-linear CFD to calculate a non-linear correction relative to a linear aero calculation for the same aerodynamic surface at an angle of attack that results in the same configuration lift. For efficiency, this nonlinear correction is applied after each subsequent linear aero solution during the iterations between the aerodynamic and structural analyses. Convergence is achieved when the vehicle shape being used for the aerodynamic calculations is consistent with the structural deformations caused by the aerodynamic loads. To make the structural analyses more efficient, a linearized structural deformation model has been adopted, in which a single stiffness matrix can be used to solve for the deformations under all the load conditions. Using the converged aerodynamic loads, a final set of structural analyses are performed to determine the stress distributions and the buckling conditions for constraint calculation. Performance constraints are obtained by running FLOPS using drag polars that are computed using results from non-linear corrections to the linear aero code plus several codes to provide drag increments due to skin friction, wave drag, and other miscellaneous drag contributions. The status of the integration effort will be presented in the proposed paper, and results will be provided that illustrate the degree of accuracy in the linearizations that have been employed.
Weston, R. P.↗
Optical Communication Link Atmospheric Attenuation Model
The Space Communications and Navigation (SCaN) Center for Networking, Integration, and Communications (SCENIC) user interface, which provides web accessible space mission simulation and communication system analysis capabilities using verified and validated analysis algorithms, can execute analyses including, but not limited to, line-of-sight, orbit propagation, and dynamic link budget calculations between sets of missions and/or assets. SCENIC's purpose is to provide NASA civil servants and contractors a user-friendly tool, integrated with model data, that can simulate and analyze a range of space mission architectures without the need for repeated and redundant modeling. Given the abundance and further future development of free space optical (FSO) communication channels within modern space infrastructure, the availability of a reliable optical link analysis capability is crucial for SCENIC users. The efforts outlined in this paper aim to provide a model for atmospheric attenuation of FSO communication links, both due to absorption/scattering and turbulence, to increase the accuracy of SCENIC's optical link assessment capabilities. A previous model existed for optical absorption/scattering within the SCaN Link Budget Tool, but it was not location specific for the Earth ground-based nodes, nor was the model optimized for run-time. The new model utilizes years of National Oceanic and Atmospheric Administration (NOAA) visibility data from ground station locations around the world. Visibility, along with the wavelength of the optical signal, are input parameters to calculate the optical specific attenuation, which is a parameter in the calculation of the slant-path attenuation. A final FSO atmospheric attenuation value is comprised of the absorption/scattering attenuation and the turbulence attenuation. A run-time efficient algorithm for the model was then developed and programmed in MATLAB ® . Due to the simple model and vectorization possible in MATLAB, the algorithm has an average run-time of less than one fourth of the run-time of the previous implementation.
Jack L Green↗
Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem
The International Space Station National Lab (ISSNL) was established through Congressional authority in 2005 and has been managed by a nonprofit called the Center for the Advancement of Science in Space (CASIS) since 2011 to support research, development, education, and commercial activities in low-Earth orbit (LEO). NASA leadership is considering next steps for microgravity and orbital activities in LEO in preparation for the retirement of the International Space Station (ISS) and transition to Commercial LEO Destinations (CLDs) in the 2030 timeframe. Specifically, our study team within the NASA Office of Technology, Policy, and Strategy addressed the question: What are potential models for an ISS National Lab facilitating government-funded or subsidized activities on a commercial LEO platform after the transition of the ISS to one or more private platforms? To inform the trade space of potential models, we conducted over 40 discussions with stakeholders internal and external to NASA and reviewed over 35 documents related to LEO legislation, commercialization, models, and activities. Following the extensive literature review and discussions with diverse stakeholders, we defined and evaluated six models, in addition to the current ISSNL model. We assessed each model across three possible future scenarios (dynamic, steady, and limited growth of the commercial LEO market and activities) and across five stakeholder-driven model evaluation criteria (ability to meet NASA’s needs, adaptability, opportunity for collaboration, market sustainability, and equity and accessibility). The six models in the future trade space were: • Government Research Broker: Customizable research efforts on transport vehicles and CLDs • Innovation Campus: Modern terrestrial campus with workforce focus • Anchor Tenant: Long-term, substantial agreement for leasing space on a single CLD • Fee for Service: Free market approach with NASA-sponsored grants and service/data buys • Matchmaker: Neutral third-party connecting users to platforms • Institute Network: Network of separate but related efforts to enable commercial scaling The Government Research Broker model performed best across the scenarios, followed by Innovation Campus, Anchor Tenant, and Fee for Service. While Matchmaker and Institute Network exhibited positive aspects, the two models performed most favorably in future scenarios with well-established communities and markets. The six models presented in this study are representative of the potential trade space and are illustrative examples. NASA leadership can adjust models as desired to align to their priorities more closely by using combinations of the unique model features provided in our analysis. The optimal model is likely a combination of features from multiple models. Building upon this work to best position NASA and the diverse stakeholders of LEO activities for success post-ISS, further work will explore the near-term impact of preparing for the transition of the ISS to CLDs by identifying opportunities for modifying the current ISSNL-CASIS partnership. ACKNOWLEDGEMENTS We thank the many reviewers and discussants, internal and external to NASA, that contributed to the work.
Erica Rodgers↗
Range-Specific High-resolution Mesoscale Model Setup
This report summarizes the findings from an AMU task to determine the best model configuration for operational use at the ER and WFF to best predict winds, precipitation, and temperature. The AMU ran test cases in the warm and cool seasons at the ER and for the spring and fall seasons at WFF. For both the ER and WFF, the ARW core outperformed the NMM core. Results for the ER indicate that the Lin microphysical scheme and the YSU PBL scheme is the optimal model configuration for the ER. It consistently produced the best surface and upper air forecasts, while performing fairly well for the precipitation forecasts. Both the Ferrier and Lin microphysical schemes in combination with the YSU PBL scheme performed well for WFF in the spring and fall seasons. The AMU has been tasked with a follow-on modeling effort to recommended local DA and numerical forecast model design optimized for both the ER and WFF to support space launch activities. The AMU will determine the best software and type of assimilation to use, as well as determine the best grid resolution for the initialization based on spatial and temporal availability of data and the wall clock run-time of the initialization. The AMU will transition from the WRF EMS to NU-WRF, a NASA-specific version of the WRF that takes advantage of unique NASA software and datasets. 37
Watson, Leela R.↗
A manual optimal guidance scheme using a predictive model.
Manual optimal guidance scheme using predictive display applied to launch vehicles during boost for continuous generation of predicted fuel- optimal trajectory
MANUAL CONTROL↗
A manual optimal guidance scheme using a predictive model.
Manual optimal guidance scheme using predictive display applied to launch vehicles during boost for continuous generation of predicted fuel- optimal trajectory
Gilchrist, J. D.↗
The extension of the thermal-vacuum test optimization program to multiple flights
The thermal vacuum test optimization model developed to provide an approach to the optimization of a test program based on prediction of flight performance with a single flight option in mind is extended to consider reflight as in space shuttle missions. The concept of 'utility', developed under the name of 'availability', is used to follow performance through the various options encountered when the capabilities of reflight and retrievability of space shuttle are available. Also, a 'lost value' model is modified to produce a measure of the probability of a mission's success, achieving a desired utility using a minimal cost test strategy. The resulting matrix of probabilities and their associated costs provides a means for project management to evaluate various test and reflight strategies.
Williams, R. E.↗
Analysis and optimization of a queueing model of a real-time computer control system
Real time computer control system queueing model to optimize preemptible and nonpreemptible job priority assignment
Schrage, L.↗
Concepts and Challenges for Environmentally Friendly En Route Operations
Presented research on environmentally friendly en route traffic flow concepts incorporating models developed by basic climate research Developed an optimal contrail reduction trajectory concept. Integrated fuel flow, emissions and optimization models with FACET. Verified it against FAA emission models. Ability to conduct system level analysis of Traffic Flow Management concepts with minimal environmental impact.
Sridhar, Banavar↗
Optimal Experimental Design With Fast Neural Network Surrogate Models
Designing optimal experiments minimizes the uncertainty of results and maximizes the efficient use of resources. Herein, machine learning surrogate models and the approximate coordinate exchange (ACE) algorithm are used to determine optimum experimental designs over large or arbitrarily restrictive design spaces. Optimal experimental design is particularly salient in materials science where experiments are expensive and material properties must often be inferred indirectly. The proposed framework is demonstrated by finding optimal experiments with which the hidden constituent properties of composite materials can be most efficiently inferred from observable experimental outcomes. The optimum experimental design is given by an information-theoretic criteria, which maximizes the conditional mutual information between the hidden properties and the expected experimental outcomes. To perform tractable optimization a neural network is trained as a surrogate model to mimic a physics based simulation, which can calculate the expected experimental outcome based on a candidate experimental design and sampled constituent properties. The ACE algorithm is used to optimize over large design spaces with many tests and controlled parameters where an exhaustive search would be intractable even with the surrogate model. Using this approach, optimal experimental designs that are consistent with those produced by heuristic knowledge and established best practices are found; then optimal designs in larger design spaces where heuristic knowledge is unavailable are examined.
machine learning↗
Generalized mathematical models in design optimization
The theory of optimality conditions of extremal problems can be extended to problems continuously deformed by an input vector. The connection between the sensitivity, well-posedness, stability and approximation of optimization problems is steadily emerging. The authors believe that the important realization here is that the underlying basis of all such work is still the study of point-to-set maps and of small perturbations, yet what has been identified previously as being just related to solution procedures is now being extended to study modeling itself in its own right. Many important studies related to the theoretical issues of parametric programming and large deformation in nonlinear programming have been reported in the last few years, and the challenge now seems to be in devising effective computational tools for solving these generalized design optimization models.
Papalambros, Panos Y.↗
Model error estimation for large space systems
In-flight estimation of large structure model errors may have to be carried out in order to detect inevitable deficiencies in large structure controller/estimator models. These error estimates can most efficiently be obtained by the minimization of a quadratic functional of the model errors and on the subsequent analysis of the resulting optimal model error estimates. An integral operator approach to estimation leads to a geometrical interpretation of the model error estimation process. One of the significant insights gained with this interpretation is that the actual but unknown model errors can be decomposed as the sum of two distinct components that are orthogonal in some sense. One of these components is a so-called minimal error vector that retains many of the significant dynamics of the actual errors. The basic ideas in the model error estimation approach are first set forth with a two-dimensional analogy that has most of the essential features of the general estimation problem. The generalized results are then established and their application to a reference large structure model illustrated.
Rodriguez, G.↗
Inducing Bistability in Collapsible Tubular Masts Booms with Thin-Ply Composite Shells
Bistable rollable booms are favorable when a low strain energy requirement for the coiled state is imposed and have more controllable deployment when compared to monostable booms. An inextensional analytical model describing the bending deformation mechanics of Collapsible Tubular Mast (CTM) booms was used to determine how design variables induce bistability, or the existence of two strain energy wells in the rolled-up and unrolled states. The effects of varying lamina material, laminate layup, and shell arc geometries between different inner and outer shell segments on the second strain energy well and stiffness properties were determined for boom cross-sections formed by circular segments. The full design space for two-walled composite CTM booms was explored to evaluate the validity of the developed analytical model. Optimized CTM boom designs were experimentally characterized for comparisons against model results. The model under-predicted the stable coiled diameter of the co-cured two-walled booms by up to 8.9% and 23.4% for the individual thin shells wrapped alone.
Andrew J Lee↗
The role of optimization in structural model refinement
To evaluate the role that optimization can play in structural model refinement, it is necessary to examine the existing environment for the structural design/structural modification process. The traditional approach to design, analysis, and modification is illustrated. Typically, a cyclical path is followed in evaluating and refining a structural system, with parallel paths existing between the real system and the analytical model of the system. The major failing of the existing approach is the rather weak link of communication between the cycle for the real system and the cycle for the analytical model. Only at the expense of much human effort can data sharing and comparative evaluation be enhanced for the two parallel cycles. Much of the difficulty can be traced to the lack of a user-friendly, rapidly reconfigurable engineering software environment for facilitating data and information exchange. Until this type of software environment becomes readily available to the majority of the engineering community, the role of optimization will not be able to reach its full potential and engineering productivity will continue to suffer. A key issue in current engineering design, analysis, and test is the definition and development of an integrated engineering software support capability. The data and solution flow for this type of integrated engineering analysis/refinement system is shown.
Lehman, L. L.↗
Modeling, Analysis, and Optimization Issues for Large Space Structures
Topics concerning the modeling, analysis, and optimization of large space structures are discussed including structure-control interaction, structural and structural dynamics modeling, thermal analysis, testing, and design.
Pinson, L. D.↗