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At least 883 records · Page 49

Gaussian and Lognormal Models of Hurricane Gust Factors

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

Merceret, Frank↗

Revealing the Predominant Surface Facets of Rough Cu Electrodes under Electrochemical Conditions

Metal electrodes with rough surfaces are frequently found to convert CO or CO 2 to hydrocarbons and oxygenates with high selectivity and at high reaction rates in comparison with their smooth counterparts. The atomic-level morphology of a rough electrode is likely one key factor responsible for its comparatively high catalytic selectivity and activity. However, few methods are capable of probing the atomic-level structure of rough metal electrodes under electrocatalytic conditions. As a result, the nuances in the atomic-level surface morphology that control the catalytic characteristics of these electrodes have remained largely unexplored. Because the C≡O stretching frequency of atop-bound CO (CO atop ) depends on the coordination of the underlying metal atom, the IR spectrum of this reaction intermediate on the copper electrode could, in principle, provide structural information about the catalytic surface during electrolysis. However, other effects, such as dynamic dipole coupling, easily obscure the dependence of the frequency on the surface morphology. Further, in the limit of low CO atop coverage, where coupling effects are small, the C≡O stretching frequencies of CO atop on Cu(111) and Cu(100) facets are virtually identical. Therefore, on the basis of the C≡O stretching frequency, it is not straightforward to distinguish between these two ubiquitous surface facets, which exhibit vastly different CO reduction activities. Herein, we show that key features of the atomic-level surface morphology of rough copper electrodes can be inferred from the potential dependence of the line shape of the C≡O stretching band of CO atop . Specifically, we compared two types of rough copper thin-film electrodes that are routinely employed in the context of surface-enhanced infrared absorption spectroscopy (SEIRAS). We found that copper films that are electrochemically deposited on Si-supported Au films (CuAu–Si) are poor catalysts for the reduction of CO to ethylene in comparison to copper films (Cu–Si) that are electrolessly deposited onto Si crystals. As quantified by differential electrochemical mass spectrometry (DEMS), the onset potential for ethylene is ~200 ± 65 mV more cathodic for CuAu–Si than that for Cu–Si. To reveal the origin of the disparate catalytic properties of Cu–Si and CuAu–Si, we probed the surfaces of the electrodes with cyclic voltammetry (CV) and SEIRAS. The CV characterization suggests that the (111) surface facet predominates on CuAu–Si, whereas the (100) facet is more common on Cu–Si. SEIRAS reveals that the line shape of the C≡O stretching of CO atop is composed of two bands that are attributable to CO atop on terrace and defect sites. The different surface structures manifest themselves in the form of starkly different potential dependences of the line shape of the C≡O stretching mode of CO atop on the two types of electrodes. With a simple Boltzmann model that considers the different adsorption energies of CO atop on terrace and defect sites, and the resulting CO atop populations on terrace and defect sites, we deduced that the observed electrode-specific potential dependence of the line shape is consistent with the presence of different predominant terrace sites on the two types of films. This strategy for assessing the atomic-level morphology is not restricted to SEIRAS but could also be applied to the C≡O stretching bands recorded with surface-enhanced Raman spectroscopy (SERS), which is suitable for probing a wide range of rough copper electrodes. Therefore, with this work, we establish the potential dependence of the C≡O stretching band of CO atop as a probe of the atomic-level surface structure of rough metal electrodes under electrochemical conditions. When it is coupled with complementary techniques, this methodology provides essential structural information for further improvement in the reaction selectivity of rough metal electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Abstract Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil–plant–atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

Antiferromagnetic ordering and possible lattice response to dynamic uranium valence in U 3 O 8

Determining the correct electronic structure of U 3 O 8 remains a formidable experimental and theoretical challenge. In the low-temperature phase, two crystallographic U sites are separated into a distinct 2U(V)+1U(VI) oxidation configuration. At low temperatures, the U(V) sites form a distorted honeycomb lattice, but the U(VI) sit on a triangular sublattice, suggesting potential for magnetic frustration effects. The spin configuration of the unpaired f electrons on the U(V) sites is likely antiferromagnetic (AFM) from susceptibility measurements, but this has not been confirmed. Here in this paper, we present a neutron scattering investigation of the structure and dynamics of U 3 O 8 from 1.7 to 600 K. We confirm static AFM ordering onset at between 22 and 25 K, which is present down to at least 1.7 K with AFM peaks corresponding to [0.5 1 1] and [0.5 2 2] in the orthorhombic phase. These measurements rule out static AFM order along the a axis of the Amm2 phase, a configuration previously suggested by theory. Above 100 K a quasielastic scattering channel opens that we speculate arises from a lattice relaxation response to thermally activated electron hopping. This term does not conform to a magnetic form factor, so it is not related to spin relaxations. If correct, this mechanism stabilizes a continuous valence transition from 2U(V)+1U(VI) in the low-temperature (T<600 K) orthorhombic phase to the hexagonal phase that contains only one degenerate U site, wherein the U valence can be dynamically stabilized between U(V)↔U(VI) by phonon-assisted electron hopping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Frequency response modeling and control of flexible structures: Computational methods

The dynamics of vibrations in flexible structures can be conventiently modeled in terms of frequency response models. For structural control such models capture the distributed parameter dynamics of the elastic structural response as an irrational transfer function. For most flexible structures arising in aerospace applications the irrational transfer functions which arise are of a special class of pseudo-meromorphic functions which have only a finite number of right half place poles. Computational algorithms are demonstrated for design of multiloop control laws for such models based on optimal Wiener-Hopf control of the frequency responses. The algorithms employ a sampled-data representation of irrational transfer functions which is particularly attractive for numerical computation. One key algorithm for the solution of the optimal control problem is the spectral factorization of an irrational transfer function. The basis for the spectral factorization algorithm is highlighted together with associated computational issues arising in optimal regulator design. Options for implementation of wide band vibration control for flexible structures based on the sampled-data frequency response models is also highlighted. A simple flexible structure control example is considered to demonstrate the combined frequency response modeling and control algorithms.

Bennett, William H.↗

MSC/NASTRAN Stress Analysis of Complete Models Subjected to Random and Quasi-Static Loads

Space payloads, such as those which fly on the Space Shuttle in Spacelab, are designed to withstand dynamic loads which consist of combined acoustic random loads and quasi-static acceleration loads. Methods for computing the payload stresses due to these loads are well known and appear in texts and NASA documents, but typically involve approximations such as the Miles' equation, as well as possible adjustments based on "modal participation factors." Alternatively, an existing capability in MSC/NASTRAN may be used to output exact root mean square [rms] stresses due to the random loads for any specified elements in the Finite Element Model. However, it is time consuming to use this methodology to obtain the rms stresses for the complete structural model and then combine them with the quasi-static loading induced stresses. Special processing was developed as described here to perform the stress analysis of all elements in the model using existing MSC/NASTRAN and MSC/PATRAN and UNIX utilities. Fail-safe and buckling analyses applications are also described.

Hampton, Roy W.↗

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

The dynamics of particle disks. III - Dense and spinning particle disks

The kinetic theory of planetary rings developed by Araki and Tremaine (1986) and Araki (1988) is extended and refined, with a focus on the implications of finite particle size: (1) nonlocal collisions and (2) finite filling factors. Consideration is given to the derivation of the equations for the local steady state, the low-optical-depth limit, and the steady state at finite filling factors (including the effects of collision inelasticity, spin degrees of freedom, and self-gravity). Numerical results are presented in extensive graphs and characterized in detail. The importance of distinguishing effects (1) and (2) at low optical depths is stressed, and the existence of vertical density profiles with layered structures at high filling factors is demonstrated.

Araki, Suguru↗

Advanced Deployable Shell-Based Composite Booms for Small Satellite Structural Applications Including Solar Sails

State of the art deployable structures are mainly being designed for medium to large size satellites. The lack of reliable deployable structural systems for low cost, small volume, rideshare-class spacecraft severely constrains the potential for using small satellite platforms for affordable deep space science and exploration precursor missions that could be realized with solar sails. There is thus a need for reliable, lightweight, high packaging efficiency deployable booms that can serve as the supporting structure for a wide range of small satellite systems including solar sails for propulsion. The National Air and Space Administration (NASA) is currently investing in the development of a new class of advanced deployable shell-based composite booms to support future deep space small satellite missions using solar sails. The concepts are being designed to: meet the unique requirements of small satellites, maximize ground testability, permit the use of low-cost manufacturing processes that will benefit scalability, be scalable for use as elements of hierarchical structures (e.g. trusses), allow long duration storage, have high deployment reliability, and have controlled deployment behavior and predictable deployed dynamics. This paper will present the various rollable boom concepts that are being developed for 5-20 m class size deployable structures that include solar sails with the so-called High Strain Composites (HSC) materials. The deployable composite booms to be presented are being developed to expand the portfolio of available rollable booms for small satellites and maximize their length for a given packaged volume. Given that solar sails are a great example of volume and mass optimization, the booms were designed to comply with nominal solar sail system requirements for 6U CubeSats, which are a good compromise between those of smaller form factors (1U, 2U and 3U CubeSats) and larger ones (12 U and 27 U future CubeSats, and ESPA-class microsatellites). Solar sail missions for such composite boom systems are already under consideration and development at NASA, as well as mission studies that will benefit from planned scaled-up versions of the composite boom technologies to be introduced. The paper presents ongoing research and development of thin-shell rollable composite booms designed under the particular stringent and challenging system requirements of relatively large solar sails housed on small satellites. These requirements will be derived and listed. Several new boom concepts are proposed and other existing ones are improved upon using thin-ply composite materials to yield unprecedented compact deployable structures. Some of these booms are shown in Fig. 1. For every boom to be introduced the scalable fabrication process developed to keep the overall boom system cost down will be shown. Finally, the initial results of purposely designed boom structural characterization test methods with gravity off-loading will be presented to compare their structural performance under expected and general load cases.

Fernandez, Juan M.↗

Alternative Vegetation States in Tropical Forests and Savannas: The Search for Consistent Signals in Diverse Remote Sensing Data

Globally, the spatial distribution of vegetation is governed primarily by climatological factors (rainfall and temperature, seasonality, and inter-annual variability). The local distribution of vegetation, however, depends on local edaphic conditions (soils and topography) and disturbances (fire, herbivory, and anthropogenic activities). Abrupt spatial or temporal changes in vegetation distribution can occur if there are positive (i.e., amplifying) feedbacks favoring certain vegetation states under otherwise similar climatic and edaphic conditions. Previous studies in the tropical savannas of Africa and other continents using the MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF) satellite data product have focused on discontinuities in the distribution of tree cover at different rainfall levels, with bimodal distributions (e.g., concentrations of high and low tree cover) interpreted as alternative vegetation states. Such observed bimodalities over large spatial extents may not be evidence for alternate states, as they may include regions that have different edaphic conditions and disturbance histories. In this study, we conduct a systematic multi-scale analysis of diverse MODIS data streams to quantify the presence and spatial consistency of alternative vegetation states in Sub-Saharan Africa. The analysis is based on the premise that major discontinuities in vegetation structure should also manifest as consistent spatial patterns in a range of remote sensing data streams, including, for example, albedo and land surface temperature (LST). Our results confirm previous observations of bimodal and multimodal distributions of estimated tree cover in the MODIS VCF. However, strong disagreements in the location of multimodality between VCF and other data streams were observed at 1 km scale. Results suggest that the observed distribution of VCF over vast spatial extents are multimodal, not because of local-scale feedbacks and emergent bifurcations (the definition of alternative states), but likely because of other factors including regional scale differences in woody dynamics associated with edaphic, disturbance, and/or anthropogenic processes. These results suggest the need for more in-depth consideration of bifurcation mechanisms and thus the likely spatial and temporal scales at which alternative states driven by different positive feedback processes should manifest.

Savanna↗

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

Perennial grass bioenergy cropping systems: Impacts on soil fauna and implications for soil carbon accrual

ABSTRACT Perennial grass energy crop production is necessary for the successful and sustainable expansion of bioenergy in North America. Numerous environmental advantages are associated with perennial grass cropping systems, including their potential to promote soil carbon accrual. Despite growing research interest in the abiotic and biotic factors driving soil carbon cycling within perennial grass cropping systems, soil fauna remain a critical yet largely unexplored component of these ecosystems. By regulating microbial activity and organic matter decomposition dynamics, soil fauna influence soil carbon stability with potentially significant implications for soil carbon accrual. We begin by reviewing the diverse, predominantly indirect effects of soil fauna on soil carbon dynamics in the context of perennial grass cropping systems. Since the impacts of perennial grass energy crop production on soil fauna will mediate their potential contributions to soil carbon accrual, we then discuss how perennial grass energy crop traits, diversity, and management influence soil fauna community structure and activity. We assert that continued research into the interactions of soil fauna, microbes, and organic matter will be important for advancing our understanding of soil carbon dynamics in perennial grass cropping systems. Furthermore, explicit consideration of soil faunal effects on soil carbon can improve our ability to predict changes in soil carbon following perennial grass cropping system establishment. We conclude by addressing the major knowledge gaps that should be prioritized to better understand and model the complex connections between perennial grass bioenergy systems, soil fauna, and carbon accrual.

sustainability↗

The internal dynamics of slowly rotating biological systems

The structure and the dynamics of biological systems are complex. Steady gravitational forces that act on organisms cause hydrostatic pressure gradients, stress in solid components, and ordering of movable subsystems according to density. Rotation induces internal motion; it also stresses and or deforms regions of attachment and containment. The disrupted gravitationally ordered layers of movable entities are replaced by their orbital movements. New ordering geometries may arise also, especially if fluids of various densities occur. One novel result obtained concerns the application of scheduled variation of clinostat rotation rates to the management of intracellular particle trajectories. Rotation and its consequences are discussed in terms of scaling factors for parameters such as time, derived from mathematical models for simple rotating mechanical systems.

Kessler, John O.↗

Assessing the Relationships Between Sensorimotor Biomarkers and Post-Landing Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study was to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts were recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests included assessments of sensory dependency and adaptability. Visual dependency involved treadmill walking while viewing a moving virtual visual scene. Vestibular perceptual thresholds were measured while seated during lateral translations. Proprioception dependency was measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability was performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms (adaptive Functional Mobility Test, aFMT). The neuroimaging tests characterized individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests utilized saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Thirty ISS crewmembers were recruited, including 12 first-time fliers, 6F, and mission durations lasting 185.5 ± 45.5 days, mean ± std. We utilized a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There was considerable variability among all post-flight performance outcomes. Based on an ordinal scale survey, 72% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. Understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

biomarkers↗

Ion transport in polymerized lyotropic liquid crystals containing ionic liquid

In this work, we investigate the effect of morphology and segmental dynamics on ion transport in polymerized lyotropic liquid crystals (polyLLCs) containing 1-butyl-3-methylimidazolium tetrafluoroborate as ionic liquid (IL). We demonstrate that two important factors, which affect ion conduction in polyLLCs, are grain size and chain density at the interface. The polyLLC with large grain size (70 nm) shows significant reduction in ion conductivity (one order of magnitude) compared to its homopolymer/IL mixture. However, the polyLLC with small grain size (20 nm) has little difference in ion conductivity compared to its homopolymer/IL mixture. It is observed that decreasing the chain density enhances the interaction of IL with polymer chains and consequently slows the relaxation of polymer chains. Finally, in addition, comparing the dynamics of polymer chains in mixtures of homopolymer/IL and templated LLC mesophases shows that the confinement in LLC structure prolongs the relaxation of polymer chains.

36 MATERIALS SCIENCE↗

Exponential Water Uptake in Ionomer Membranes Results from Polymer Plasticization

Water content is the most influential factor in the performance of ion-exchange membranes (IEMs), controlling their mechanical rigidity, ionic conductivity, and degradation rates. Membranes absorb water exponentially at high water activity (a w ), making that region of the sorption isotherm the most influential on membrane properties. Plasticization of the polymer by water has been proposed to cause this exponential uptake at high a w . However, an integrated microscopic picture of the structure, thermodynamic, and mechanical properties of IEMs as a function of a w has remained elusive. In this work, we use large-scale molecular simulations validated with experimental measurements to compute the sorption isotherms, Young’s modulus, polymer dynamics, and structure of IEMs. The simulations unveil that the exponential increase in water uptake (WU) coincides in all cases with the glass to rubber transition of the membrane, as measured through its Young’s modulus and segmental polymer dynamics. Functionalization of the polymer with alkyl groups further contributes to its plasticization, increasing the WU at a given a w and ion-exchange capacity (IEC). The alkyl chains act synergistically with water to plasticize the polymer matrix and allow water penetration in the membrane. The simulations reveal that the width of the water channels depends on the ratio λ of water to ions in the polymer but is independent of its IEC. We conclude that differences in the polymer matrix–not the water channels–are responsible for the distinct uptake response of IEMs to the thermodynamic driving force of water activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Component modes damping assignment methodology for articulated, multiflexible body structures

To simulate the dynamical motion of articulated, multiflexible body structures, one can use multibody simulation packages such as DISCOS. To this end, one must supply appropriate reduced-order models for all of the flexible components involved. The component modes projection and assembly model reduction (COMPARE) methodology is one way to construct these reduced-order component models, which when reassembled capture important system input-to-output mapping of the full-order model at multiple system configurations of interest. In conjunction, we must also supply component damping matrices which when reassembled generate a system damping matrix that has certain desirable properties. The problem of determining the damping factors of components' modes to achieve a given system damping matrix is addressed here. To this end, we must establish from first principles a matrix-algebraic relation between the system's modal damping matrix and the components' modal damping matrices. An unconstrained/constrained optimization problem can then be formulated to determine the component modes' damping factors that best satisfy that matrix-algebraic relation. The effectiveness of the developed methodology, called ModeDamp, has been successfully demonstrated on a high-order, finite element model of the Galileo spacecraft.

Lee, Allan Y.↗