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We present a general framework which allows for a novel set of linear solutions to the pose estimation problem for both n points and n lines. We present a number of simulations which compare our results to two other recent linear algorithm as well as to iterative approaches.
A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.
It is widely assumed that human exploration beyond Earth's orbit will require vehicles capable of providing long duration habitats that simulate an Earth-like environment - consistent artificial gravity, breathable atmosphere, and sufficient living space- while requiring the minimum possible launch mass. This paper examines how the qualities of digital cellular solids - high-performance, repairability, reconfigurability, tunable mechanical response - allow the accomplishment of long-duration habitat objectives at a fraction of the mass required for traditional structural technologies. To illustrate the impact digital cellular solids could make as a replacement to conventional habitat subsystems, we compare recent proposed deep space habitat structural systems with a digital cellular solids pressure vessel design that consists of a carbon fiber reinforced polymer (CFRP) digital cellular solid cylindrical framework that is lined with an ultra-high molecular weight polyethylene (UHMWPE) skin. We use the analytical treatment of a linear specific modulus scaling cellular solid to find the minimum mass pressure vessel for a structure and find that, for equivalent habitable volume and appropriate safety factors, the use of digital cellular solids provides clear methods for producing structures that are not only repairable and reconfigurable, but also higher performance than their conventionally manufactured counterparts.
A campaign of wall-modeled large-eddy simulations (WMLES) using structured curvilinear overlapping grids has been performed with the Launch Ascent and Vehicle Aerodynamics(LAVA) computational fluid dynamics (CFD) software to predict jet noise for single-stream axisymmetric round jets. The simulations address the new Prediction Uncertainty Reduction(PUR) technical challenge within the context of NASA’s Commercial Supersonic Technology(CST) project. The goal of PUR is to quantify and reduce uncertainties from scale-resolving simulations to assess noise characteristics of next generation quiet supersonic commercial jets during takeoff and landing conditions where the noise from the exhaust jet dominates. The focus of this effort is to generate a simulation database for single-stream axisymmetric round nozzles at several conditions both for static (no ambient co-flow), which is the focus of this article, and in-flight (flight stream co-flow) conditions, which are beyond the current scope. Nine different flow conditions ranging in jet exit Mach number from 0.38 to 1.0 with nozzle temperature ratios (NTR) from 0.84 to 2.7 have been conducted. Details of the structured overset grids, numerical discretization and wall-model are provided. Near-field comparisons to PIV data show great agreement for both velocity and normal stresses, however a systematic TKE overshoot at the nozzle exit is seen in the lip line shear-layer. A permeable Ffowcs Williams Hawkings (FWH) surface, enclosing the jet, is used to predict far-field noise from the simulated flow-field. Comparison of CFD predictions to microphone array measurements demonstrate excellent agreement within the resolved frequency range. A systematic under-prediction of far-aft observer angles larger than 150 degrees has been observed across all simulations. We achieved a cost reduction of an order of magnitude for these WMLES compared to an earlier study of this configuration due to algorithmic and software improvements. The accuracy of the results and short turnaround time demonstrate that WMLES within the LAVA framework is a cost-effective approach for jet noise predictions that could soon be incorporated into the design cycle of jet noise reduction technologies.
In recent years, there has been a growing recognition of the significance of Land-Atmosphere (L-A) interactions and feedback mechanisms in understanding and predicting Earth’s water and energy cycles. Soil moisture plays a critical role in mediating the strength of L-A interactions and is important for understanding the complex and governing processes across this interface. This study aims to identify the significance of soil moisture in identifying L-A coupling strength within the Convective Triggering Potential (CTP) and Humidity Index (HI) framework. To address this, a consistent and reliable dataset of atmospheric profiles is created by merging CTP and HI using Triple Collocation (TC) with three reanalysis datasets. The merged CTP and HI product demonstrates enhanced performance globally as compared to the individual datasets when validated with radiosonde and satellite observations. This merged product of CTP and HI is then used to compare the L-A coupling strength based on Soil Moisture Active Passive Level 3 (SMAPL3) and SMAP Level 4 (SMAPL4) over two decades (2003-2022) where L-A coupling strength is defined as the persistence probability within the dry and wet coupling regimes. Results indicate that the persistency-based coupling strength is related to the ability of soil moisture to predict future atmospheric humidity and dry vs. wet coupling state. The coupling strength in SMAPL4 is consistently stronger than in SMAPL3 and is likely due to its reliance on a land surface model and reduced susceptibility to random noise. The difference in coupling strength based on the same CTP-HI underscores the importance of soil moisture data in estimating coupling strength within the CTP-HI framework. These findings lay the groundwork for understanding the role of L-A interactions and drought evolution due to soil moisture variations, by providing insight into the quantification of coupling strength and its role in drought monitoring and forecast efforts.
Lightning is a hazard globally, particularly in lesser-developed countries. Cloud-to-ground lightning strikes are a threat to human safety, motivating a desire to monitor location-based lightning risk to mitigate harm. A lightning risk assessment for human safety was created that uses a combination of probabilistic risk calculation and spatial lightning mapping data to produce a risk magnitude. This risk magnitude evolves with time and changing conditions and is compared to tolerability thresholds in order to evaluate safety. The risk assessment using lightning mapping array (LMA) flash extent density (FED) data was found to perform comparatively (with respect to issuing lightning warnings) to a more standard method of monitoring lightning safety where National Lightning Detection Network (NLDN) flashes were monitored within a 5 nautical mile radius of a location of interest. This research investigates the replacement of LMA FED with FED from the Geostationary Lightning Mapper (GLM) within the risk assessment framework. Using GLM FED would allow for risk to be calculated outside of LMA domains and anywhere within the GLM field of view, including areas outside of the United States (US). A few applications of the risk method with GLM FED are shown and discussed for locations both in and outside of the US. Additionally, the performance of the risk method is compared based on the type of lightning input source (LMA vs GLM). The end goal of this work is to provide forecasters and end users with a tool to help monitor lightning risk in decision support scenarios.
Deployable Entry Vehicles (DEVs) enable in-situ scientific exploration at destinations with atmospheres across the solar system. Because they stow in a compact form and deploy only when ready to enter the atmosphere, DEVs relax the volume constraint imposed by rigid aeroshells. This work seeks to do for a DEV what the Wright Brothers did to propel modern day aviation: develop the guidance and control (G&C) methods that will make maneuvering and precision landing of DEV a reality. The Pterodactyl project objective is to deliver an integrated G&C methodology for a DEV, based on a detailed analysis that utilizes a Multi-disciplinary, Design, Analysis and Optimization (MDAO) framework. The current state-of-the-art for blunt body entry, G&C is rooted in the precision landing of vehicles such as Mars Science Laboratory (MSL) and Apollo, which used a propulsive reaction control system (RCS) to steer. Recent research has taken a particular interest in non-propulsive control for DEVs, including direct force control (angle of attack modulation via control surfaces or mass movement) and drag modulation (discrete change in ballistic coefficient). Using the MDAO framework that includes a guidance and control model to explore multiple control concepts for a DEV will shed light on the best design approach for these vehicles. In Pterodactyl, we will complete this study for a novel DEV concept, and then we will fabricate a functional prototype to help validate the design. The project is expected to down-select to a final control architecture by the end of 2018, and complete fabrication of the prototype by the end of 2019.The DEV chosen for detailed study in this project is the Adaptable Deployable Entry and Placement Technology (ADEPT). ADEPT uses a revolutionary 3D-woven carbon fabric that is foldable, can serve as primary structure, and can survive the extreme heating environment of atmospheric entry. The specific configuration of ADEPT under investigation is called Lifting Nano-ADEPT (LNA). LNA is designed for secondary payloads missions that require precision landing either for scientific objectives at a target destination or for payload recovery at Earth.The MDAO framework being created through this research, called COBRA-Pt (Composite Beam Roll-Up Solar Array-Prototype), will combine three critical elements of the system design: a guidance algorithm with Monte Carlo, a parametric control model, and vehicle geometry details. Novel control models being studied are deployable aerodynamic surfaces as well as shape morphing. These concepts will be compared at the system level with a more traditional propulsive RCS by comparing several key performance parameters. Upon completion of the design study, a functional prototype of LNA will be fabricated that will include the integration of guidance software and relevant control actuators. We expect this study will provide critical data that could feed into the development of an Earth-based flight test of LNA. The COBRA-Pt framework will provide a modular system by which to study any DEV concept in any atmosphere.
An accurate numerical analysis of the flows associated with rotor-stator configurations in turbomachinery can be very helpful in optimizing the performance of turbomachinery. In this study the unsteady, thin-layer, Navier-Stokes equations are solved using a system of patched and overlaid grids for a rotor-stator configuration of an axial turbine. The equations necessary for an accurate transfer of information between the several grids are briefly described within the framework of an iterative, implicit algorithm. Results in the form of Mach number contours, time-averaged pressures, unsteady pressures, amplitudes, and phase are presented. The numerical results are also compared with experimental data and the agreement is found to be good.
A detailed study on the effect of convection on crystal quality was carried out by growing lead bromide crystals in transparent Bridgman furnace. Direct observations were made on the solid-liquid interface and a new kind of instability was observed. This could be explained on the basis of toroidal flow in the AgBr-doped lead bromide sample. With the increasing translation velocity, the interface changed from flat to depressed, and then formed a cavity in the center of the growth tube. The crystal grown at the lowest thermal Rayleigh number showed the highest quality and crystal grown at the largest thermal Rayleigh number showed the worst quality. Numerical studies were carried out to provide a framework for interpreting the observed convective and morphological instabilities, and to determine the critical (limiting) concentration of dopant for a particular growth velocity and gravity level. Theoretical instability diagrams were compared with data obtained from the experimental studies. These studies provided basic data on convective behavior in doped lead bromide crystals grown by the commercially important Bridgman process.
Clarissa, an experimental voice enabled procedure browser that has recently been deployed on the International Space Station, is as far as we know the first spoken dialog system in space. We describe the objectives of the Clarissa project and the system's architecture. In particular, we focus on three key problems: grammar-based speech recognition using the Regulus toolkit; methods for open mic speech recognition; and robust side-effect free dialogue management for handling undos, corrections and confirmations. We first describe the grammar-based recogniser we have build using Regulus, and report experiments where we compare it against a class N-gram recogniser trained off the same 3297 utterance dataset. We obtained a 15% relative improvement in WER and a 37% improvement in semantic error rate. The grammar-based recogniser moreover outperforms the class N-gram version for utterances of all lengths from 1 to 9 words inclusive. The central problem in building an open-mic speech recognition system is being able to distinguish between commands directed at the system, and other material (cross-talk), which should be rejected. Most spoken dialogue systems make the accept/reject decision by applying a threshold to the recognition confidence score. NASA shows how a simple and general method, based on standard approaches to document classification using Support Vector Machines, can give substantially better performance, and report experiments showing a relative reduction in the task-level error rate by about 25% compared to the baseline confidence threshold method. Finally, we describe a general side-effect free dialogue management architecture that we have implemented in Clarissa, which extends the "update semantics'' framework by including task as well as dialogue information in the information state. We show that this enables elegant treatments of several dialogue management problems, including corrections, confirmations, querying of the environment, and regression testing.
When they are applicable, gradient based optimization algorithms are the most efficient way to solve design optimization problems. Although gradient based methods are generally efficient, they can be made significantly more so through the usage of analytic techniques to compute the necessary total derivatives. The traditional forward (direct) and reverse (adjoint) analytic techniques have computational costs that scale linearly with the number of design variables and the number of constraints, respectively. In this work, we present an application of a graph coloring algorithm to the analytic techniques for computing total derivative Jacobians in order to achieve much better computational scaling than the pure analytic methods can provide alone. A detailed theoretical explanation of how coloring algorithms interact with analytic derivative methods is presented that illustrates specific types of sparsity patterns that must be present in total derivative Jacobians in order for this coloring technique to be effective. The new technique has been implemented as a feature in the OpenMDAO framework and the implementation is demonstrated on two example problems. The performance on the example problems up to 50% reduction in compute cost for optimizations with bi-directional coloring compared to traditional constraint aggregation. Additionally, the results show how coloring technique alleviates some of the numerical difficulties that constraint aggregation can cause, leading to the ability to solve larger problems. It is expected that the new method will have wide applicability to multidisciplinary optimization problems, and that its availability in OpenMDAO will offer significant computational savings for users without the need for them to implement the coloring algorithm themselves.
The enigmatic control of the occurrence frequency of Jupiter's decametric emissions by the satellite Io is explained theoretically on the basis of its strong electrodynamic interaction with the corotating Jovian magnetosphere leading to field aligned currents connecting Io with the Jovian ionosphere. Direct measurements of the perturbation magnetic fields due to this current system were obtained by the magnetic field experiment on Voyager 1 on 5 March 1979 when it passed within 20,500 km south of Io. An interpretation in the framework of Alfven waves radiated by Io leads to current estimates of 2.8 million amps. A mass density of 7400 to 13600 proton mass units per Cu cm is derived which compares very favorably with independent observations of the torus composition characterized by 7-9 proton mass units per electron for a local electron density of 1050 to 1500 per cu cm. The power dissipated in the current system may be important for heating the Io heavy ion torus, inner magnetosphere, Jovian ionosphere, and possibly the ionosphere or even the interior of Io.
Proof testing was a useful supplement to conventional nondestructive evaluation (NDE) of space shuttle main engine (SSME) components. Since many of these components involve thin sections and high toughness materials, such as Inconel 718, conventional single-cycle proof test logic is not applicable due to the propensity for stable crack growth during the proof tests. Experience with five-cycle proof testing of SSME components is summarized and a framework is outlined for understanding multi-cycle proof testing using the fracture mechanics concept of a resistance curve. Extreme value statistics are also used to propose an empirical approach to compare the advantages and disadvantages of single- versus multi-cycle proof testing. The importance of the initial flaw size distribution and specimen thickness in such a comparison is also discussed.
The Subsonic Ultra Green Aircraft Research (SUGAR) Phase III was led by Dr. Rakesh K. Kapania and Dr. Joseph A. Schetz at the Multidisciplinary Analysis and Design Center for Advanced Vehicles, Department of Aerospace and Ocean Engineering, Virginia Tech, Blacksburg VA. The research was performed from December 2014 to December 2015. Three major areas were investigated: Multidisciplinary Design Optimization (MDO) studies of truss braced wing (TBW) and strut braced wing (SBW) vehicles at cruise Mach numbers of 0.7 and 0.8 for a flight mission similar to current market single aisle configurations. The performance and the characteristics of the optimized vehicles were compared to the SUGAR Phase II TBW vehicle. These results were obtained without applying any of the extended transonic aerodynamic and aeroelastic tools that will be discussed later. It was found that the cruise Mach number has a large effect on the best “truss” configuration. At Mach 0.7, an SBW has a better fuel consumption and better take-off gross weight (TOGW). However, at Mach 0.8, the TBW is superior because the jury strut aids in satisfying the flutter constraint; Two-dimensional, steady, transonic aerodynamic analysis of the Boeing Airfoil J (BACJ) airfoil was performed for a range of thickness ratios, Mach numbers and lift coefficients. Reynolds-averaged Navier-Stokes (RANS) equations were solved to obtain the lift-curve slope, wave drag coefficient, the location of the center of pressure and to predict the separation at the trailing edge, which may lead to buffeting. One of the goals was to develop a database of lift-curve slope and the location of center of pressure, which could be used in a transonic aeroelastic analysis. Another goal was to compare the wave drag coefficients to those predicted by Lock’s fourth-power law and also to compare the transonic effects obtained from RANS simulations to those predicted by the Korn equations. A third goal was to develop a buffet boundary, which can be integrated into the MDO framework to prevent the optimized designs from probable buffeting; A state-space transonic aeroelastic analysis tool was developed, which can incorporate the nonlinear transonic effects in the unsteady aerodynamics but is yet computationally cheap when used within the VT MDO framework. The aeroelastic analysis uses Leishman- Beddoes (LB) indicial functions, which generated a state-space representation of the aeroelastic system. The indicial functions allow the incorporation of data for steady lift-curve slope and location of the center of pressure. Thus, the steady transonic effects are included, and the unsteady aerodynamic responses are a linearization about the steady results. The aeroelastic approach discretizes the wing into numerous strips, which results in a large eigenvalue problem as each strip has eight augmented aerodynamic states as per the LB theory. Thus, to reduce the computation expense, a reduced order model (ROM) was developed. The approach was validated using a few examples.
Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of 2 relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with a geometric diameter up to 20 µm (PM20) is approximately 5000 Tg yr−1, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded datasets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this dataset is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.
An ensemble Kalman filter is used to assimilate Advanced Microwave Scanning Radiometer-2 (AMSR2) observations of passive microwave (PMW) brightness temperatures (spectral differences, ΔT b ) into land surface model estimates of snow mass over northwestern high mountain Asia (HMA). Trained support vector machines serve as the observation operator and map the geophysical modeled variables into ΔT b space within the assimilation framework. Evaluation of the assimilation routine is carried out through comparison of assimilated snow mass estimates with an in situ dataset. The assimilation framework helps improve the land surface model estimates through PMW ΔT b assimilation, particularly in terms of decreasing the domain-wide bias. The assimilation framework proved more effective during the (dry) snow accumulation season and decreased the bias and root-mean-square error (RMSE) in snow mass estimates at 76% and 58% of the comparative pixels, respectively. During the snow ablation season, the PMW brightness temperature signal contained less information related to snow mass due to the presence of other concurrent geophysical features that effectively serve as noise during the snow mass update. The utilization of PMW ΔT b for accurate snow mass estimation in complex terrain such as HMA is dependent on a multitude of factors for optimal results; however, it does add utility to the land surface model if the relevant pitfalls are taken into consideration prior to the state variable update.
This research effort is a joint program between the Departments of Aerospace and Mechanical Engineering and the Computer Science and Engineering Department at the University of Notre Dame. The purpose of the project was to develop a framework and systematic methodology to facilitate the application of Multidisciplinary Design Optimization (MDO) to a diverse class of system design problems. For all practical aerospace systems, the design of a systems is a complex sequence of events which integrates the activities of a variety of discipline "experts" and their associated "tools". The development, archiving and exchange of information between these individual experts is central to the design task and it is this information which provides the basis for these experts to make coordinated design decisions (i.e., compromises and trade-offs) - resulting in the final product design. Grant efforts focused on developing and evaluating frameworks for effective design coordination within a MDO environment. Central to these research efforts was the concept that the individual discipline "expert", using the most appropriate "tools" available and the most complete description of the system should be empowered to have the greatest impact on the design decisions and final design. This means that the overall process must be highly interactive and efficiently conducted if the resulting design is to be developed in a manner consistent with cost and time requirements. The methods developed as part of this research effort include; extensions to a sensitivity based Concurrent Subspace Optimization (CSSO) NMO algorithm; the development of a neural network response surface based CSSO-MDO algorithm; and the integration of distributed computing and process scheduling into the MDO environment. This report overviews research efforts in each of these focus. A complete bibliography of research produced with support of this grant is attached.
A Lunar Crane with a suspension system based on a three cable mechanism is investigated to provide a stable end-effector for hoisting, positioning, and assembling large components during construction and servicing of a Lunar Base. The three cable suspension mechanism consists of a structural framework of three cables pointing to a common point that closely coincides with the suspended payload's center of gravity. The vibrational characteristics of this three cable suspension system are investigated by comparing a simple 2-D symmetric suspension model and a swinging pendulum in terms of their analytical natural frequency equations. A study is also made of actively controlling the dynamics of the crane using two different actuator concepts. Also, Lyapunov-based control algorithms are developed to determine two regulator-type control laws performing the system vibrational suppression for both system dynamics. Simulations including initial-valued dynamic responses as well as control performances for two different system dynamics are also presented.