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At least 1,585 records · Page 88

The UK Met Office GCM with a Sophisticated Radiation Scheme Applied to the Hot Jupiter HD 209458b

To study the complexity of hot Jupiter atmospheres revealed by observations of increasing quality, we have adapted the UK Met Office Global Circulation Model (GCM), the Unified Model (UM), to these exoplanets. The UM solves the full 3D Navier-Stokes equations with a height-varying gravity, avoiding the simplifications used in most GCMs currently applied to exoplanets. In this work we present the coupling of the UM dynamical core to an accurate radiation scheme based on the two-stream approximation and correlated-k method with state-of-the-art opacities from ExoMol. Our first application of this model is devoted to the extensively studied hot Jupiter HD 209458b. We derive synthetic emission spectra and phase curves, and compare them to both previous models also based on state-of-the-art radiative transfer, and to observations. We find a reasonable a agreement between observations and both our days side emission and hot spot offset, however, our night side emissions is too large. Overall our results are qualitatively similar to those found by Showman et al. (2009) with the SPARCMIT gcm, however, we note several quantitative differences: Our simulations show significant variation in the position of the hottest part of the atmosphere with pressure, as expected from simple timescale arguments, and in contrast to the vertical coherency found by Showman et al. (2009). We also see significant quantitative differences in calculated synthetic observations. Our comparisons strengthen the need for detailed intercomparisons of dynamical cores, radiation schemes and post-processing tools to understand these differences. This effort is necessary in order to make robust conclusions about these atmospheres based on GCM results.

radiation↗

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

activity analysis↗

Ultrasonic Lamb Wave Inspection of Composite Defects

Composites have been extensively used in aerospace engineering due to their advantages of light weight, high strength, and engineering design flexibility. Manufacturing defects such as wrinkle and porosity can affect the performance of the composites and may lead to failure in the end, while damage such as delamination, fiber fraction, and matrix cracking can directly cause failure of the composites. In this paper, a Lamb wave based nonintrusive nondestructive evaluation system, which employs piezoelectric transducer for actuation and scanning laser Doppler vibrometer for wavefield sensing, is presented for typical composite defect and damage inspection and evaluation. Two composite panels with different geometry (flat or curved) and with various embedded defects (wrinkle and delamination) are inspected using the nonintrusive Lamb wave system. Both the wrinkles and delamination are detected from the wavefield and approximately quantified through wavefield imaging methods.

Wrinkles↗

Solid-state Architecture Batteries for Enhanced Rechargeability and Safety for Electric Aircraft

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria. The performance metrics for eVTOL craft are at least 2 times greater than those of electric automobiles. Furthermore, safety is essential for operation of commercial electric aerovehicles. Preliminary systems level analysis has indicated that there are five key properties which must be optimized for successful implementation of battery systems. Those five key criteria are: safety, energy density, power, packaging design and scalability. Current state-of-the-art (SOA) lithium-ion batteries meet or exceed the requirements for electric aviation in the areas of power and scalability, yet are insufficient in the key performance criteria of energy, safety and packaging design. The SABERS concept proposes a battery that meets all five key performance criteria through development of a solid-state architecture battery utilizing high energy density and power density sulfur-selenium cathode with a lithium metal anode. The combination of sulfur and selenium offers a balanced energy-to-power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This cathode will be developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. A solid-state electrolyte will be used as a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. This solid-state lithium-sulfur-selenium cell will be designed into a serial stacking configuration to enable dense packaging of the battery cells. The serial stacking configuration is termed a bipolar stack, which has the advantages of reducing overall cell weight, reducing the amount of interfaced connections for the cell, and minimizing the cooling requirements for the cell. Lastly, optimization of battery components will occur through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a fully solid-state battery with operational temperatures from 0 °C to 150 °C which provides the required energy density, discharge rates, and inherent safety to meet the strict aerospace performance criteria. This presentation will show initial results that demonstrate the SABERS Team has developed a composite carbon-sulfur cathode which exceeds 1100 Wh/kg at a discharge rate of 0.4C, and 804 Wh/kg at a discharge rate of 1C. Additionally, this presentation will show the SABERS Team multiscale computational modeling approach and has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM is on the 1-10 µm scale and provides electromechanical and grain interactions for predictive design guidelines for the experimental team to follow.

Urban Air Mobility (UAM) Vehicles↗

Solid-state Architecture Batteries for Enhanced Rechargeability and Safety (SABERS) for Extended Deep Space Applications

Extended duration deep space missions as well as permanent space habitats face numerous technical challenges, key among them is energy generation and energy storage. There are considerable monetary and technical barriers to the generation of power in space. Therefore, it is important to store and be able to access power in an efficient and safe manner over a large number of cycles. Energy storage and in particular, batteries, are vital to the operation of next-generation extraterrestrial shuttles, rovers, habitats and extravehicular activity (EVA) space suits. The performance metrics for extended duration space missions are at least 2 times greater than those set for terrestrial applications such as electric automobiles. Furthermore, safety is essential for operation of space missions particularly involving astronauts such as shuttles, habitats and EVA space suits. Preliminary systems level analysis has indicated that there are five key properties which must be optimized for successful implementation of battery systems. Those five key criteria are: safety, energy density, power, packaging design and scalability. Current state-of-the-art (SOA) lithium-ion batteries can meet or exceed the requirements for certain space applications in the areas of power and scalability, yet are insufficient in the key performance criteria of energy, safety and packaging design. The SABERS concept proposes a battery that meets all five key performance criteria through development of a solid-state architecture battery utilizing high capacity sulfur-selenium cathode and lithium metal anode. The combination of sulfur and selenium offers a balanced energy-to-power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This hybrid cathode will be developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. A solid-state electrolyte will be used as a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. This solid-state lithium-sulfur/selenium cell will be designed into a serial stacking configuration to enable dense packaging of the battery cells. The serial stacking configuration is termed a bipolar stack, which has the advantages of reducing overall cell weight, simplifying the interfaced connections for the cell, and minimizing the cooling requirements for the cell. Lastly, optimization of battery components will occur through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a fully solid-state battery with operational temperatures up to 150 °C which provides the required energy density, discharge rates, and inherent safety to meet the strict space mission performance criteria. In particular, the wide operational temperature window is required for the large temperature ranges which are experienced across a broad range of potential space missions. This presentation will show initial results that demonstrate the SABERS team has developed a composite carbon-sulfur cathode which exceeds 1100 Wh/kg at a discharge rate of 0.4C, and 804 Wh/kg at a discharge rate of 1C. Additionally, this presentation will show the SABERS team multiscale computational modeling approach and has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM is on the 1-10 µm scale and provides electromechanical and grain interactions for predictive design guidelines for the experimental team to follow.

Urban Air Mobility (UAM) Vehicles↗

Mars Small Spacecraft Studies: Overview

NASA’s Mars Exploration Program is studying a potential Mars Sample Return (MSR) campaign consisting of a series of missions over the next decade that would return samples collected at Mars for analyses in terrestrial laboratories. It is anticipated that during such a campaign, many in the Mars science community would seek to continue high-priority science investigations in parallel to those provided by geological and astrobiological sample return investigations. To respond to this anticipated desire of the science community, JPL is performing a study of small spacecraft mission concepts to Mars that could bridge the gap between MSR and other desired science investigations at Mars. The goal of the study is to utilize smaller, affordable missions in performing highpriority science investigations as defined in the National Academy of Sciences Decadal Survey, Mars Exploration Program Analysis Group (MEPAG) goals, and Human Exploration and Operations (HEO) Strategic Knowledge Gaps. The study targets the use of small spacecraft with greater science capability than currently achievable with CubeSats. The target spacecraft wet mass is approximately 100 to 350 kilograms. Methods of access to Mars considered in this study include a self-propelled transit from Earth geosynchronous transfer orbit (GTO) to Mars as a secondary payload in a rideshare configuration. The study investigates mission concepts, science objectives, mission designs, concept of operations, enhancing technologies, and mission costs, along with launch vehicle interfaces. The cost estimates of the mission concepts studied range from below $100 million to less than $300 million for development through launch. This paper concludes with an outline of several examples of small spacecraft mission concepts to Mars that demonstrate significant scientific capability, are technically feasible, and fit within the desired cost range.

Edwards, Charles D.↗

Computational Modeling Development of Solid-state Architecture Batteries for Enhanced Rechargeability and Safety for Electric Aircraft

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria. The performance metrics for eVTOL craft are at least 2 times greater than those of electric automobiles. Furthermore, safety is essential for operation of commercial electric aerovehicles. Preliminary systems level analysis has indicated that there are five key properties which must be optimized for successful implementation of battery systems. Those five key criteria are: safety, energy density, power, packaging design and scalability. Current state-of-the-art (SOA) lithium-ion batteries meet or exceed the requirements for electric aviation in the areas of power and scalability, yet are insufficient in the key performance criteria of energy, safety and packaging design. The SABERS concept proposes a battery that meets all five key performance criteria through development of a solid-state architecture battery utilizing high energy density and power density sulfur-selenium cathode with a lithium metal anode. The combination of sulfur and selenium offers a balanced energy-to-power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This cathode will be developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. A solid-state electrolyte will be used as a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. This solid-state lithium-sulfur-selenium cell will be designed into a serial stacking configuration to enable dense packaging of the battery cells. The serial stacking configuration is termed a bipolar stack, which has the advantages of reducing overall cell weight, reducing the amount of interfaced connections for the cell, and minimizing the cooling requirements for the cell. Lastly, optimization of battery components will occur through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a fully solid-state battery with operational temperatures from 0 °C to 150 °C which provides the required energy density, discharge rates, and inherent safety to meet the strict aerospace performance criteria. This presentation will show initial results that demonstrate the SABERS Team has developed a composite carbon-sulfur cathode which exceeds 1100 Wh/kg at a discharge rate of 0.4C, and 804 Wh/kg at a discharge rate of 1C. Additionally, this presentation will show the SABERS Team multiscale computational modeling approach and has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM is on the 1-10 µm scale and provides electromechanical and grain interactions for predictive design guidelines for the experimental team to follow.

Urban Air Mobility (UAM) Vehicles↗

Computationally Guided Development of Components for High Energy Density Solid-State Lithium-Sulfur Batteries

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria1. The performance metrics for eVTOL craft, such as specific energy, specific power, and safety, exceed those of electric automobiles by a factor of two to four. Current state-of-the-art (SOA) lithium-ion batteries are incapable of meeting the key performance criteria of energy and safety for eVTOL. Therefore, next generation advanced chemistries and designs must be developed to meet required performance metrics for electric aviation2. Beyond lithium-ion chemistries, such as lithium-sulfur, show promise in their high energy, while limitations exist in their power and cyclability due to low electrical conductivity and high intermediate solubility in organic liquid electrolytes. Several strategies to overcome the low electrical conductivity involve the use of selenium as a dopant in the active sulfur material, along with the incorporation of 2-dimensional electron-conducting holey-graphene to improve the composite cathodes electronic conductivity. Furthermore, combining this chemistry with a solid-electrolyte avoids the components’ dissolution issues3. However, the development of composite solid-state cathodes is non-trivial as several components must be intimately mixed so that the active component has sufficient access to both electrons and lithium ions to undergo full electrochemical conversion. Mathematical modeling of battery components can assist experimental design through a robust and rigorous combination of computational modeling techniques covering multiple length scales. The objective is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build and test solid state lithium-sulfur cells and packs. A NASA-based cross-organizational team of high-powered experts combined integrated computational predictive modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. This presentation will show a multiscale computational modeling approach that has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM modeling targets the 1-10 µm scale structures and provides electromechanical and grain interactions for predictive design guidelines for the manufacturing of solid-state components. Parameters such as particle size and volume fraction of the constituent materials were modeled and experimentally fabricated to optimize electrochemical performance through improved microstructure design. Experimental feedback was provided through ionic and electronic conductivity assessment and structural analysis of developed materials and cell components.

battery↗

A Galerkin method for linear PDE systems in circular geometries with structural acoustic applications

A Galerkin method for systems of PDE's in circular geometries is presented with motivating problems being drawn from structural, acoustic, and structural acoustic applications. Depending upon the application under consideration, piecewise splines or Legendre polynomials are used when approximating the system dynamics with modifications included to incorporate the analytic solution decay near the coordinate singularity. This provides an efficient method which retains its accuracy throughout the circular domain without degradation at singularity. Because the problems under consideration are linear or weakly nonlinear with constant or piecewise constant coefficients, transform methods for the problems are not investigated. While the specific method is developed for the two dimensional wave equations on a circular domain and the equation of transverse motion for a thin circular plate, examples demonstrating the extension of the techniques to a fully coupled structural acoustic system are used to illustrate the flexibility of the method when approximating the dynamics of more complex systems.

Smith, Ralph C.↗

A hybrid perturbation Galerkin technique with applications to slender body theory

A two step hybrid perturbation-Galerkin method to solve a variety of applied mathematics problems which involve a small parameter is presented. The method consists of: (1) the use of a regular or singular perturbation method to determine the asymptotic expansion of the solution in terms of the small parameter; (2) construction of an approximate solution in the form of a sum of the perturbation coefficient functions multiplied by (unknown) amplitudes (gauge functions); and (3) the use of the classical Bubnov-Galerkin method to determine these amplitudes. This hybrid method has the potential of overcoming some of the drawbacks of the perturbation method and the Bubnov-Galerkin method when they are applied by themselves, while combining some of the good features of both. The proposed method is applied to some singular perturbation problems in slender body theory. The results obtained from the hybrid method are compared with approximate solutions obtained by other methods, and the degree of applicability of the hybrid method to broader problem areas is discussed.

Geer, James F.↗

A hybrid perturbation Galerkin technique with applications to slender body theory

A two-step hybrid perturbation-Galerkin method to solve a variety of applied mathematics problems which involve a small parameter is presented. The method consists of: (1) the use of a regular or singular perturbation method to determine the asymptotic expansion of the solution in terms of the small parameter; (2) construction of an approximate solution in the form of a sum of the perturbation coefficient functions multiplied by (unknown) amplitudes (gauge functions); and (3) the use of the classical Bubnov-Galerkin method to determine these amplitudes. This hybrid method has the potential of overcoming some of the drawbacks of the perturbation method and the Bubnov-Galerkin method when they are applied by themselves, while combining some of the good features of both. The proposed method is applied to some singular perturbation problems in slender body theory. The results obtained from the hybrid method are compared with approximate solutions obtained by other methods, and the degree of applicability of the hybrid method to broader problem areas is discussed.

Geer, James F.↗

Subsonic Aircraft With Regression and Neural-Network Approximators Designed

At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.

Patnaik, Surya N.↗

Nonlinear system approximations

The approximation of a nonlinear system by a feedback linearizable system instead of a linear system is considered. Two approaches presently exist in the literature. One involves the concept of involutivity to a certain order, and the other considers a canonical expansion and pure feedback approximation. The relationship between these two methods is shown. This provides insight into lower-order invariants in the equivalence problem for two nonlinear systems. The output time responses for a nonlinear system and its feedback linearizable approximation are outlined.

Goldthwait, Richard G.↗

Multivariate spline methods in surface fitting

The use of spline functions in the development of classification algorithms is examined. In particular, a method is formulated for producing spline approximations to bivariate density functions where the density function is decribed by a histogram of measurements. The resulting approximations are then incorporated into a Bayesiaan classification procedure for which the Bayes decision regions and the probability of misclassification is readily computed. Some preliminary numerical results are presented to illustrate the method.

Guseman, L. F., Jr.↗

Linear approximations of nonlinear systems

The development of a method for designing an automatic flight controller for short and vertical take off aircraft is discussed. This technique involves transformations of nonlinear systems to controllable linear systems and takes into account the nonlinearities of the aircraft. In general, the transformations cannot always be given in closed form. Using partial differential equations, an approximate linear system called the modified tangent model was introduced. A linear transformation of this tangent model to Brunovsky canonical form can be constructed, and from this the linear part (about a state space point x sub 0) of an exact transformation for the nonlinear system can be found. It is shown that a canonical expansion in Lie brackets about the point x sub 0 yields the same modified tangent model.

Hunt, L. R.↗

A Unified Development of Basis Reduction Methods for Rotor Blade Analysis

The axial foreshortening effect plays a key role in rotor blade dynamics, but approximating it accurately in reduced basis models has long posed a difficult problem for analysts. Recently, though, several methods have been shown to be effective in obtaining accurate,reduced basis models for rotor blades. These methods are the axial elongation method,the mixed finite element method, and the nonlinear normal mode method. The main objective of this paper is to demonstrate the close relationships among these methods, which are seemingly disparate at first glance. First, the difficulties inherent in obtaining reduced basis models of rotor blades are illustrated by examining the modal reduction accuracy of several blade analysis formulations. It is shown that classical, displacement-based finite elements are ill-suited for rotor blade analysis because they can't accurately represent the axial strain in modal space, and that this problem may be solved by employing the axial force as a variable in the analysis. It is shown that the mixed finite element method is a convenient means for accomplishing this, and the derivation of a mixed finite element for rotor blade analysis is outlined. A shortcoming of the mixed finite element method is that is that it increases the number of variables in the analysis. It is demonstrated that this problem may be rectified by solving for the axial displacements in terms of the axial forces and the bending displacements. Effectively, this procedure constitutes a generalization of the widely used axial elongation method to blades of arbitrary topology. The procedure is developed first for a single element, and then extended to an arbitrary assemblage of elements of arbitrary type. Finally, it is shown that the generalized axial elongation method is essentially an approximate solution for an invariant manifold that can be used as the basis for a nonlinear normal mode.

Ruzicka, Gene C.↗

Diffusion approximation for large absorption in radiative transfer

A new diffusion model is developed for radiative transfer in particulate media. It includes the effects of higher Legendre moments while avoiding the mathematical complexities of solving multiple coupled differential moment equations and satisfying higher-order boundary conditions. The method accurately extrapolates the conventional Eddington approximation to problems involving large absorption. Although the simplifying assumptions limit the model to nonbeam incidence and spatial homogeneity of the scattering material, they are nonrestrictive with regard to the size and shape of the medium, the character of background reflections, and the type of phase function.

Meador, W. E.↗

Towards Formalization of Advanced Linear Algebra with Applications to Dynamical Systems using PVS

Linear Algebra is essential for numerous aerospace problems of interest. Formal reasoning about hybrid systems that contain variables modeled by differential equations rely on concepts from Linear Algebra such as eigenvalues, matrix decompositions, and matrix valued functions. For example, the long-term dynamics of a system of differential equations depend on the stability/instability of its equilibrium points, which often reduces to an eigenvalue problem. This talk will embark on a quest to formalize theorems and results about eigenvalues and eigenvectors using PVS. We shall start our journey with 2 x 2 complex matrices, where we will apply our PVS code to a simple example of a dynamical system. Since it can be difficult or impossible to give simple expressions of eigenvalues for larger matrices (i.e. 5 x 5 or higher), we then move towards specifying the power method for verified computation of eigenvalue approximations in PVS. This effort requires development of multivariate complex arithmetic. At the end of the day, having such additions to the PVS NASA libraries will help move towards the use of formal methods to verify concepts of control theory and system level verification.

Linear Algebra↗