Analysis of a wheel-damped reaction boom control system
Hybrid satellite attitude control system deformation model, utilizing pivoted flexible boom with tip mass as actuator and inertia wheels to dampen gravity induced librations
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Hybrid satellite attitude control system deformation model, utilizing pivoted flexible boom with tip mass as actuator and inertia wheels to dampen gravity induced librations
The fatigue life of material under multifactor influence of broad band random excitations has been investigated. Parameters which affect the fatigue life are postulated to be peak stress, variance of stress and the natural frequency of the system. Experimental data were processed by the hybrid computer. Based on the experimental results and regression analysis a best predicting model has been found. All values of the experimental fatigue lives are within the 95% confidence intervals of the predicting equation.
A new computational approach for transient nonlinear thermal analysis of structures is proposed. It is a hybrid approach which combines the modeling versatility of contemporary finite elements in conjunction with transform methods and classical Bubnov-Galerkin schemes. The present study is limited to nonlinearities due to temperature-dependent thermophysical properties. Numerical test cases attest to the basic capabilities and therein validate the transfinite element approach by means of comparisons with conventional finite element schemes and/or available solutions.
The functions, characteristics, and benefits of autonomous control are outlined. An autonomous control functional architecture for future space vehicles that incorporates the concepts and characteristics described is presented. The controller is hierarchical, with an execution level (the lowest level), coordination level (middle level), and management and organization level (highest level). The general characteristics of the overall architecture, including those of the three levels, are explained, and an example to illustrate their functions is given. Mathematical models for autonomous systems, including 'logical' discrete event system models, are discussed. An approach to the quantitative, systematic modeling, analysis, and design of autonomous controllers is also discussed. It is a hybrid approach since it uses conventional analysis techniques based on difference and differential equations and new techniques for the analysis of the systems described with a symbolic formalism such as finite automata. Some recent results from the areas of planning and expert systems, machine learning, artificial neural networks, and the area restructurable controls are briefly outlined.
This viewgraph presentation provides a cost benefit analysis of three next-generation forward-looking turbulence sensing systems: X band turbulence radar system for convective turbulence, LIDAR based turbulence systems to sense clear air turbulence and a combined hybrid system. Parameters for the cost benefit analysis were established using a business model which considered injury rates, cost of injuries, indirect costs, market penetration rate estimates and product success characteristics. Topics covered include: study approach, business case equations, data acquisition, benchmark analysis. Data interpretation from the cost benefit analysis is presented. The researchers conclude that the market potential for these products is based primarily on injury cost reduction and that X band radar systems have the greatest chance for commercial success.
This report is intended to provide a broad knowledge of various topics associated with NASA's Aeronautics Research Mission Directorate (ARMD), with particular interest on the NASA SBIR contracts awarded from 2011-2012 executed by small companies. The content of this report focuses on the high-quality, cutting-edge research that will lead to revolutionary concepts, technologies, and capabilities that enable radical change to both the airspace system and the aircraft that fly within it, facilitating a safer, more environmentally friendly, and more efficient air transportation system.
Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.
Transitioning from fossil-fuel power generation to renewable energy generation and energy storage in remote locations has the potential to reduce both carbon emissions and cost. Here, this study presents a techno-economic analysis for implementation of a hybrid renewable energy system at the South Pole in Antarctica, which currently hosts several high-energy physics experiments with nontrivial power needs. A tailored model of resource availability and economics for solar photovoltaics, wind turbine generators, lithium-ion energy storage, and long-duration energy storage at this site is explored in different combinations with and without existing diesel energy generation. The Renewable Energy Integration and Optimization (REopt) platform is used to determine the optimal system component sizing and the associated system economics and environmental benefit. We find that the least-cost system includes all three energy generation sources and lithium-ion energy storage. For an example steady-state load of 170 kW, this hybrid system includes 180 kW-DC of photovoltaic panels, 570 kW of wind turbines, and a 3.4 MWh lithium-ion battery energy storage system. This system reduces diesel consumption by 95% compared to an all -diesel configuration, resulting in approximately 1200 metric tons of carbon footprint avoided annually. Over the course of a 15-year analysis period the reduced diesel usage leads to a net savings of 57 million United States dollars, with a time to payback of approximately two years. All the scenarios modeled show that the transition to renewables is highly cost effective under the unique economics and constraints of this extremely remote site.
Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.
NASA Environmentally Responsible Aviation (ERA) project and the Boeing Company are collabrating to advance the unitized damage arresting composite airframe technology with application to the Hybrid-Wing-Body (HWB) aircraft. The testing of a HWB fuselage section with Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) construction is presently being conducted at NASA Langley. Based on lessons learned from previous HWB structural design studies, improved finite-element models (FEM) of the HWB multi-bay and bulkhead assembly are developed to evaluate the performance of the PRSEUS construction. In order to assess the comparative weight reduction benefits of the PRSEUS technology, conventional cylindrical skin-stringer-frame models of a cylindrical and a double-bubble section fuselage concepts are developed. Stress analysis with design cabin-pressure load and scenario based case studies are conducted for design improvement in each case. Alternate analysis with stitched composite hat-stringers and C-frames are also presented, in addition to the foam-core sandwich frame and pultruded rod-stringer construction. The FEM structural stress, strain and weights are computed and compared for relative weight/strength benefit assessment. The structural analysis and specific weight comparison of these stitched composite advanced aircraft fuselage concepts demonstrated that the pressurized HWB fuselage section assembly can be structurally as efficient as the conventional cylindrical fuselage section with composite stringer-frame and PRSEUS construction, and significantly better than the conventional aluminum construction and the double-bubble section concept.
Abstract Plant height (PH) plays a very important role for plant breeding and also serves as a model trait to dynamic development study. The dynamic quantitative trait locus (QTL) analysis for PH of Agropyron Gaertn. was carried out in a cross‐pollination (CP) hybrid population of A. Gaertn. based on the phenotypic data of PH at different developmental stages in four year‐sites and the constructed single‐nucleotide polymorphism (SNP) genetic map. The results showed that 69 QTL and nine major QTL were detected by unconditional QTL mapping. A total of 107 QTL and 13 major QTL were found using conditional QTL mapping. Forty‐seven QTL were detected by two methods. Two unconditional QTL, Qph2‐5 and Qph3‐4, were expressed as major and stable QTL for PH. Four major stable conditional QTL for PH, cQph4‐1 , cQph4‐8, cQph6‐2 and cQph6‐7 , were detected. Two conditional PH QTL, cQph3‐5 and cQPh3‐7 , were identified in four environments over multiple stages. The gene/QTL controlling PH was expressed in a certain spatiotemporal manner. These results could also provide a reference for genetic and breeding research of related plant.
This progress report (Level 4 Milestone Number M4SF-23LL010301062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite International Collaborations Activity Number SF-23LL01030106. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. The focus of this milestone is the establishment of international collaborations for surface complexation modeling and the associated impacts of unlocking larger, community-based datasets. More specifically, we are developing a database framework for Spent Fuel and Waste and Science Technology (SFWST) that is aligned with the Helmholtz Zentrum Dresden Rossendorf (HZDR) sorption database development group in support of the database needs of the SFWST program. In our FY22 effort, we described a detailed analysis of U(VI) sorption to quartz through both traditional surface complexation modeling and through a hybrid ML framework. In FY23, effort was placed on publication of these results and expansion of the LLNL surface complexation and ion exchange database (L-SCIE) in order to assess mineral-based radionuclide retardation under a wider variety of geochemical conditions (e.g., ionic strength, varying electrolyte compositions). Efforts were initiated to expand L-SCIE to include radionuclide surface complexation and ion exchange to clays that are relevant to subsurface geochemical processes occurring at nuclear waste repositories. In particular, a large source of sorption data for clays resides at the Paul Scherrer Institute (PSI) (work primarily by Bradbury and Baeyens) and we initiated discussions on how to retrieve those data and apply FAIR principles to those datasets. In addition to L-SCIE development, two hybrid models that incorporate AI/ML were investigated and compared to discern the most promising approaches for accurate and precise estimations of radionuclide retardation. Key considerations for future model development include (1) the ability to reduce computational burden on determining retardation coefficients for PA and (2) the ability to quantify and predict radionuclide-mineral partitioning at a more efficient, rapid pace due to automated workflows. Upon the careful consideration of the most effective modeling approaches, we are identifying ways to implement these approaches into PA. Ultimately, the data science-based workflows will provide a major incentive for other institutions to adopt a FAIR-formatted, interoperable database. LLNL will play a key role in disseminating sorption data and acting as good data stewards by updating the database in a consistent format and assessing the quality of the newly assimilated data in an organized fashion. To this end, all data and workflows are open access and made available on the LLNL Seaborg research website (https://seaborg.llnl.gov/resources/geochemical-databases-modeling-codes).
A multidisciplinary effort is underway at the NASA Glenn Research Center to develop concepts for revolutionary, nontraditional fuel cell power and propulsion systems for aircraft applications. There is a growing interest in the use of fuel cells as a power source for electric propulsion as well as an auxiliary power unit to substantially reduce or eliminate environmentally harmful emissions. A systems analysis effort was initiated to assess potential concepts in an effort to identify those configurations with the highest payoff potential. Among the technologies under consideration are advanced proton exchange membrane (PEM) and solid oxide fuel cells, alternative fuels and fuel processing, and fuel storage. Prior to this effort, the majority of fuel cell analysis done at Glenn was done for space applications. Because of this, a new suite of models was developed. These models include the hydrogen-air PEM fuel cell; internal reforming solid oxide fuel cell; balance-of-plant components (compressor, humidifier, separator, and heat exchangers); compressed gas, cryogenic, and liquid fuel storage tanks; and gas turbine/generator models for hybrid system applications. Initial mass, volume, and performance estimates of a variety of PEM systems operating on hydrogen and reformate have been completed for a baseline general aviation aircraft. Solid oxide/turbine hybrid systems are being analyzed. In conjunction with the analysis efforts, a joint effort has been initiated with Glenn s Computer Services Division to integrate fuel cell stack and component models with the visualization environment that supports the GRUVE lab, Glenn s virtual reality facility. The objective of this work is to provide an environment to assist engineers in the integration of fuel cell propulsion systems into aircraft and provide a better understanding of the interaction between system components and the resulting effect on the overall design and performance of the aircraft. Initially, three-dimensional computer-aided design (CAD) models of representative PEM fuel cell stack and components were developed and integrated into the virtual reality environment along with an Excel-based model used to calculate fuel cell electrical performance on the basis of cell dimensions (see the figure). CAD models of a representative general aviation aircraft were also developed and added to the environment. With the use of special headgear, users will be able to virtually manipulate the fuel cell s physical characteristics and its placement within the aircraft while receiving information on the resultant fuel cell output power and performance. As the systems analysis effort progresses, we will add more component models to the GRUVE environment to help us more fully understand the effect of various system configurations on the aircraft.
The Hybrid Optimization and Performance Platform, HOPP, is a wind + solar + battery + X design software for optimizing co-located, utility-scale hybrid plants down to the component level for different markets and technoeconomic objectives. Key technology and financial inputs to the HOPP model that inform the objective to be optimized are presented. The layout and performance integration is combined with optimal dispatch and full financial modeling within an optimization framework. With an example scenario, optimal sizing and layout results are shown in a sensitivity analysis of prices for two hybrid configurations.
The National Aeronautics and Space Administration (NASA) Constellation Program (CxP) has identified a series of tests to provide insight into the design and development of the Crew Launch Vehicle (CLV) and Crew Exploration Vehicle (CEV). Ares I-X was selected as the first suborbital development flight test to help meet CxP objectives. The Ares I-X flight test vehicle (FTV) is an early operational model of CLV, with specific emphasis on CLV and ground operation characteristics necessary to meet Ares I-X flight test objectives. The in-flight part of the test includes a trajectory to simulate maximum dynamic pressure during flight and perform a stage separation of the Upper Stage Simulator (USS) from the First Stage (FS). The in-flight test also includes recovery of the FS. The random vibration response from the ARES 1-X flight will be reconstructed for a few specific locations that were instrumented with accelerometers. This recorded data will be helpful in validating and refining vibration prediction tools and methodology. Measured vibroacoustic environments associated with lift off and ascent phases of the Ares I-X mission will be compared with pre-flight vibration predictions. The measured flight data was given as time histories which will be converted into power spectral density plots for comparison with the maximum predicted environments. The maximum predicted environments are documented in the Vibroacoustics and Shock Environment Data Book, AI1-SYS-ACOv4.10 Vibration predictions made using statistical energy analysis (SEA) VAOne computer program will also be incorporated in the comparisons. Ascent and lift off measured acoustics will also be compared to predictions to assess whether any discrepancies between the predicted vibration levels and measured vibration levels are attributable to inaccurate acoustic predictions. These comparisons will also be helpful in assessing whether adjustments to prediction methodologies are needed to improve agreement between the predicted and measured flight data. Future assessment will incorporate hybrid methods in VAOne analysis (i.e., boundary element methods, BEM and finite element methods, FEM). These hybrid methods will enable the ability to import NASTRAN models providing much more detailed modeling of the underlying beams and support structure of the ARES 1-X test vehicle. Measured acoustic data will be incorporated into these analyses to improve correlation for additional post flight analysis.
Nonlinear-tapered flexbeam laminates from a full-size composite helicopter rotor hub flexbeam were tested under combined constant axial tension and cyclic bending loads. The two different graphite/glass hybrid configurations tested under cyclic loading failed by delamination in the tapered region. A 2-D finite element model was developed which closely approximated the flexbeam geometry, boundary conditions, and loading. The analysis results from two geometrically nonlinear finite element codes, ANSYS and ABAQUS, are presented and compared. Strain energy release rates (G) obtained from the above codes using the virtual crack closure technique (VCCT) at a resin crack location in the flexbeams are presented for both hybrid material types. These results compare well with each other and suggest that the initial delamination growth from the resin crack toward the thick region of the flexbeam is strongly mode II. The peak calculated G values were used with material characterization data to calculate fatigue life curves and compared with test data. A curve relating maximum surface strain to number of loading cycles at delamination onset compared reasonably well with the test results.
The 1990 Johnson Space Center (JSC) National Aeronautics and Space Administration (NASA)/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program was conducted by the University of Houston-University Park and Johnson Space Centers (JSC). A compilation of the final reports on the research projects is presented. The following topics are covered: the Space Shuttle; the Space Station; lunar exploration; mars exploration; spacecraft power supplies; mars rover vehicle; mission planning for the Space Exploration Initiative; instrument calibration standards; a lunar oxygen production plant; optical filters for a hybrid vision system; dynamic structural analysis; lunar bases; pharmacodynamics of scopolamine; planetary spacecraft cost modeling; and others.
Compositional verification techniques in the assume- guarantee style have been successfully applied to transition systems to efficiently reduce the search space by leveraging the compositional nature of the systems under consideration. We adapt these techniques to the domain of hybrid systems with affine dynamics. To build assumptions we introduce an abstraction based on location merging. We integrate the assume-guarantee style analysis with automatic abstraction refinement. We have implemented our approach in the symbolic hybrid model checker SpaceEx. The evaluation shows its practical potential. To the best of our knowledge, this is the first work combining assume-guarantee reasoning with automatic abstraction-refinement in the context of hybrid automata.