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At least 163 records · Page 9

Fast Fuzzy Arithmetic Operations

In engineering applications of fuzzy logic, the main goal is not to simulate the way the experts really think, but to come up with a good engineering solution that would (ideally) be better than the expert's control, In such applications, it makes perfect sense to restrict ourselves to simplified approximate expressions for membership functions. If we need to perform arithmetic operations with the resulting fuzzy numbers, then we can use simple and fast algorithms that are known for operations with simple membership functions. In other applications, especially the ones that are related to humanities, simulating experts is one of the main goals. In such applications, we must use membership functions that capture every nuance of the expert's opinion; these functions are therefore complicated, and fuzzy arithmetic operations with the corresponding fuzzy numbers become a computational problem. In this paper, we design a new algorithm for performing such operations. This algorithm is applicable in the case when negative logarithms - log(u(x)) of membership functions u(x) are convex, and reduces computation time from O(n(exp 2))to O(n log(n)) (where n is the number of points x at which we know the membership functions u(x)).

Hampton, Michael↗

Validating Drag and Heating Coefficients for Hollow Reentry Objects in Continuum Flow Using a Mach 7 Ludwieg Tube

Drag and heating coefficient databases and models are crucial to destructive reentry simulation. The NASA Orbital Debris Program Office (ODPO) develops, maintains, and performs analysis with the Object Reentry Survival Analysis Tool (ORSAT), which comprises drag and heating models for free molecular, transitional, and continuum flow regimes. These models have, in the past, only included solid, convex, blunt shapes (such as boxes, spheres, and cylinders). Previous work led by ODPO includes the extension of these models to hollow cylinders and square boxes in free molecular and transitional flow using the Direct Simulation Monte Carlo (DSMC) method. Since 2019, the ODPO has continued its program of DSMC simulations and extended the project to include analyses with the NASA Data Parallel Line Relaxation (DPLR) program on hollow cylinders and boxes (with varying wall thickness-diameter ratio). In fall 2022, the ODPO began a collaboration with the University of Texas San Antonio (UTSA) to use the Mach 7 Ludwieg Tube facility to validate the model built using numerical simulations. This facility can replicate (at a scale of approximately 100:1) the conditions seen by reentering objects near typical demise altitudes. We present here the drag and heating coefficients derived from the continued DSMC simulations, the new DPLR simulations, and the 26-test series at UTSA.

Chris Ostrom↗

Validating Drag and Heating Coefficients for Hollow Reentry Objects in Continuum Flow Using a Mach 7 Ludwieg Tube

Drag and heating coefficient databases and models are crucial to destructive reentry simulation. The NASA Orbital Debris Program Office (ODPO) develops, maintains, and performs analysis with the Object Reentry Survival Analysis Tool (ORSAT), which comprises drag and heating models for free molecular, transitional, and continuum flow regimes. These models have, in the past, only included solid, convex, blunt shapes (such as boxes, spheres, and cylinders). Previous work led by ODPO includes the extension of these models to hollow cylinders and square boxes in free molecular and transitional flow using the Direct Simulation Monte Carlo (DSMC) method. Since 2019, the ODPO has continued its program of DSMC simulations and extended the project to include analyses with the NASA Data Parallel Line Relaxation (DPLR) program on hollow cylinders and boxes (with varying wall thickness-diameter ratio). In fall 2022, the ODPO began a collaboration with the University of Texas San Antonio (UTSA) to use the Mach 7 Ludwieg Tube facility to validate the model built using numerical simulations. This facility can replicate (at a scale of approximately 100:1) the conditions seen by reentering objects near typical demise altitudes. We present here the drag and heating coefficients derived from the continued DSMC simulations, the new DPLR simulations, and the 26-test series at UTSA.

Chris Ostrom↗

Numerical optimization in Hilbert space using inexact function and gradient evaluations

Trust region algorithms provide a robust iterative technique for solving non-convex unstrained optimization problems, but in many instances it is prohibitively expensive to compute high accuracy function and gradient values for the method. Of particular interest are inverse and parameter estimation problems, since function and gradient evaluations involve numerically solving large systems of differential equations. A global convergence theory is presented for trust region algorithms in which neither function nor gradient values are known exactly. The theory is formulated in a Hilbert space setting so that it can be applied to variational problems as well as the finite dimensional problems normally seen in trust region literature. The conditions concerning allowable error are remarkably relaxed: relative errors in the gradient error condition is automatically satisfied if the error is orthogonal to the gradient approximation. A technique for estimating gradient error and improving the approximation is also presented.

Carter, Richard G.↗

RegularizedOptimization.jl: A Julia framework for regularized and nonsmooth optimization

RegularizedOptimization.jl is a Julia package that implements families of quadratic regularization and trust-region methods for solving the nonsmooth optimization problem $^{\textrm{minimize}}_{𝑥∈ℝ^𝑛}$ 𝑓(𝑥) + ℎ(𝑥) subject to 𝑐(𝑥) = 0, (1) where 𝑓 ∶ ℝ 𝑛 → ℝ and 𝑐 ∶ ℝ 𝑛 → ℝ 𝑚 are continuously differentiable, and ℎ ∶ ℝ 𝑛 → ℝ∪{+∞} is lower semi-continuous. The nonsmooth objective ℎ can be a regularizer, such as a sparsity inducing penalty, model simple constraints, such as 𝑥 belonging to a simple convex set, or can be a combination of both. All 𝑓, ℎ, and 𝑐 can be nonconvex. RegularizedOptimization.jl provides a modular and extensible framework for solving (1), and developing novel solvers. Currently, the following solvers are implemented: • Trust-region solvers TR and TRDH (Aravkin et al., 2022; Leconte & Orban, 2025) • Quadratic regularization solvers R2, R2DH and R2N (Aravkin et al., 2022; Diouane, Habiboullah, et al., 2024) • Levenberg-Marquardt solvers LM and LMTR (Aravkin et al., 2024) used when 𝑓 is a least-squares residual. • Augmented Lagrangian solver AL (De Marchi et al., 2023). All solvers rely on first derivatives of 𝑓 and 𝑐, and optionally on their second derivatives in the form of Hessian-vector products. If second derivatives are not available, quasi-Newton approximations can be used. In addition, the proximal mapping of the nonsmooth part ℎ, or adequate models thereof, must be evaluated. At each iteration, a step is computed by solving a subproblem of the form (1) inexactly, in which 𝑓, ℎ, and 𝑐 are replaced with appropriate models around the current iterate. The solvers R2, R2DH, and TRDH are particularly well suited to solve the subproblems, though they are general enough to solve (1). All solvers are allocation-free, so re-solves incur no additional allocations. To illustrate our claim of extensibility, a first version of the AL solver was implemented by an external contributor. Furthermore, a nonsmooth penalty approach, described in Diouane, Gollier, et al. (2024), is currently being developed, that relies on the library to efficiently solve the subproblems.

Gollier, Maxence [Polytechnique Montréal, QC (Cana↗

Computed stress fields in GaAs during vertical Bridgman growth

The thermoelastic stress field of GaAs crystals grown by the vertical Bridgman method has been approximated using a linear elastic, axisymmetric stress model. The model included the effects due to the thermal field and the gravitational field, as well as the interaction with the ampoule, but did not fully account for the elastic anisotropy of the crystal. Realistic thermal fields for different furnace temperatures and insulation zone thicknesses were computed with a similar model. The difference between the Von Mises stress and the critical resolved shear stress (CRSS) was used as a measure of the number of dislocations present. Different sets of growth parameters were examined to determine which produced the lowest amount of stress in the crystal. Results show that the crystal-ampoule interaction is the most important parameter in dislocation generation. In addition, for the same sticking boundary conditions, concave interfaces have lower stress than convex interfaces.

Rosch, William↗

Discontinuous Galerkin Methods for NonLinear Differential Systems

This talk considers simplified finite element discretization techniques for first-order systems of conservation laws equipped with a convex (entropy) extension. Using newly developed techniques in entropy symmetrization theory, simplified forms of the discontinuous Galerkin (DG) finite element method have been developed and analyzed. The use of symmetrization variables yields numerical schemes which inherit global entropy stability properties of the PDE (partial differential equation) system. Central to the development of the simplified DG methods is the Eigenvalue Scaling Theorem which characterizes right symmetrizers of an arbitrary first-order hyperbolic system in terms of scaled eigenvectors of the corresponding flux Jacobian matrices. A constructive proof is provided for the Eigenvalue Scaling Theorem with detailed consideration given to the Euler equations of gas dynamics and extended conservation law systems derivable as moments of the Boltzmann equation. Using results from kinetic Boltzmann moment closure theory, we then derive and prove energy stability for several approximate DG fluxes which have practical and theoretical merit.

Barth, Timothy↗

Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented.

state estimation↗

First-principles analysis of the Al-rich corner of Al-Li-Cu phase diagram

The phase diagram of Al-Li-Cu system in the Al-rich region was determined by means of first-principles calculations and statistical mechanics. The mixing enthalpies of many configurations for different lattices in the whole Al-Li-Cu system were determined by density functional theory simulations to find the stable phases in the convex hull. They were fitted with a cluster expansion to calculate the free energy of the configurations with different compositions as a function of temperature in the Al-rich region (Al content > 40 at.%) by means of Monte Carlo simulations. It was found that the ground state phases in the Al-rich part of the Al-Li-Cu phase diagram were α-Al, θ' (Al 2 Cu), $δ$' (Al 3 Li), $δ$ (AlLi) and T 1 (Al 6 Cu 4 Li 3 ), while θ'' (Al 3 Cu), T 1' (Al 2 CuLi) and Al 3 Cu 2 Li were found on the lowest mixing enthalpy surfaces of their lattices and were metastable. α-Al, $δ$ and T 1 are stable phases in the whole temperature range while $δ$' becomes metastable at very low temperature and θ (Al 2 Cu) replaces θ' as the stable phase at approximately 550 K due to the vibrational entropic contribution. In addition, the phase diagram in the Al-rich region was built and it was shown in isothermal sections from 100 to 900 K. They were in good agreement with the limited experimental data in the literature and provided new information regarding the stability, solubility and stoichiometry of the different phases. This information is important to understand the precipitation mechanisms during high temperature aging.

36 MATERIALS SCIENCE↗

Numerical computation of aerodynamics and heat transfer in a turbine cascade and a turn-around duct using advanced turbulence models

The objective of this research is to develop turbulence models to predict the flow and heat transfer fields dominated by the curvature effect such as those encountered in turbine cascades and turn-around ducts. A Navier-Stokes code has been developed using an explicit Runge-Kutta method with a two layer k-epsilon/ARSM (Algebraic Reynolds Stress Model), Chien's Low Reynolds Number (LRN) k-epsilon model and Coakley's LRN q-omega model. The near wall pressure strain correlation term was included in the ARSM. The formulation is applied to Favre-averaged N-S equations and no thin-layer approximations are made in either the mean flow or turbulence transport equations. Anisotropic scaling of artificial dissipation terms was used. Locally variable timestep was also used to improve convergence. Detailed comparisons were made between computations and data measured in a turbine cascade by Arts et al. at Von Karman Institute. The surface pressure distributions and wake profiles were predicted well by all the models. The blade heat transfer is predicted well by k-epsilon/ARSM model, as well as the k-epsilon model. It's found that the onset of boundary layer transition on both surfaces is highly dependent upon the level of local freestream turbulence intensity, which is strongly influenced by the streamline curvature. Detailed computation of the flow in the turn around duct has been carried out and validated against the data by Monson as well as Sandborn. The computed results at various streamwise locations both on the concave and convex sides are compared with flow and turbulence data including the separation zone on the inner well. The k-epsilon/ARSM model yielded relatively better results than the two-equation turbulence models. A detailed assessment of the turbulence models has been made with regard to their applicability to curved flows.

Lakshminarayana, B.↗

Icelandic Pseudocraters as Analogs to some Volcanic Cones on Mars

Pseudocraters are rootless vents formed by the interaction of lava flows with surface or near-surface water. This interaction can produce mild explosions and the accumulation of scoria and spatter into small constructs. Pseudocraters in several localities in Iceland were examined in the field and compared to similar appearing features observed on Mars. The Icelandic pseudocrater cones in this study range in size from 6 to 70 m in diameter, have summit craters which range from 2 to 28 m in diameter (many cones lack craters entirely), and have flanks that am either concave- up or convex-up. The size and spacing of Icelandic pseudo-craters might be a function of the availability of water, in which larger, closely spaced features result from efficient lava-water interaction, as suggested by the environments in which the features formed. Possible Martian pseudocrater cones in Amamnis Planitia range in diameter from 30 to 180 m and have craters 12 to 80 m in diameter. A numerical model for volcanic explosions was adapted to study the formation of pseudocraters under terrestrial and Martian conditions. The results suggest that explosions forming Martian cones require significantly less water (calculated masses am less by a factor of 4 to 16) than those forming Icelandic pseudokers, despite their larger sizes, This is attributed to the low gravity and atmospheric pressure in the Mars environment and is consistent with the likely lower abundance of water, which might be present as interstitial ice at shallow depths in the regolith. Locations of potential pseudocraters on Mars at latitudes as low as approximately 8 degrees N, imply the presence of crustal ice stores at the time of their formation.

Greeley, Ronald↗

The Delta x B = 0 Constraint Versus Minimization of Numerical Errors in MHD Simulations

The MHD equations are a system of non-strictly hyperbolic conservation laws. The non-convexity of the inviscid flux vector resulted in corresponding Jacobian matrices with undesirable properties. It has previously been shown by Powell et al. (1995) that an 'almost' equivalent MHD system in non-conservative form can be derived. This non-conservative system has a better conditioned eigensystem. Aside from Powell et al., the MHD equations can be derived from basic principles in either conservative or non-conservative form. The Delta x B = 0 constraint of the MHD equations is only an initial condition constraint, it is very different from the incompressible Navier-Stokes equations in which the divergence condition is needed to close the system (i.e., to have the same number of equations and the same number of unknown). In the MHD formulations, if Delta x B = 0 initially, all one needs is to construct appropriate numerical schemes that preserve this constraint at later time evolutions. In other words, one does not need the Delta x B condition to close the MHD system. We formulate our new scheme together with the Cargo & Gallice (1997) form of the MHD approximate Riemann solver in curvilinear grids for both versions of the MHD equations. A novel feature of our new method is that the well-conditioned eigen-decomposition of the non-conservative MHD equations is used to solve the conservative equations. This new feature of the method provides well-conditioned eigenvectors for the conservative formulation, so that correct wave speeds for discontinuities are assured. The justification for using the non-conservative eigen-decomposition to solve the conservative equations is that our scheme has a better control of the numerical error associated with the divergence of the magnetic condition. Consequently, computing both forms of the equations with the same eigen-decomposition is almost equivalent. It will be shown that this approach, using the non-conservative eigensystem when solving the conservative equations, also works well in the context of standard shock-capturing schemes.

Yee, H. C.↗

Adjoint Formulation for an Embedded-Boundary Cartesian Method

Many problems in aerodynamic design can be characterized by smooth and convex objective functions. This motivates the use of gradient-based algorithms, particularly for problems with a large number of design variables, to efficiently determine optimal shapes and configurations that maximize aerodynamic performance. Accurate and efficient computation of the gradient, however, remains a challenging task. In optimization problems where the number of design variables dominates the number of objectives and flow- dependent constraints, the cost of gradient computations can be significantly reduced by the use of the adjoint method. The problem of aerodynamic optimization using the adjoint method has been analyzed and validated for both structured and unstructured grids. The method has been applied to design problems governed by the potential, Euler, and Navier-Stokes equations and can be subdivided into the continuous and discrete formulations. Giles and Pierce provide a detailed review of both approaches. Most implementations rely on grid-perturbation or mapping procedures during the gradient computation that explicitly couple changes in the surface shape to the volume grid. The solution of the adjoint equation is usually accomplished using the same scheme that solves the governing flow equations. Examples of such code reuse include multistage Runge-Kutta schemes coupled with multigrid, approximate-factorization, line-implicit Gauss-Seidel, and also preconditioned GMRES. The development of the adjoint method for aerodynamic optimization problems on Cartesian grids has been limited. In contrast to implementations on structured and unstructured grids, Cartesian grid methods decouple the surface discretization from the volume grid. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin e t al. developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation.

Nemec, Marian↗

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Experimental study of void formation during aluminum solidification in reduced gravity

Void formation due to volumetric shrinkage and liquid/vapor reorientation during aluminum solidification was observed in real time by using a radiographic viewing system in normal and reduced gravity. An end-chill directional solidification furnace with water quench was designed and constructed to solidify aluminum samples during the approximately 16 sec of reduced gravity (+/-0.02g) achieved by flying an aircraft through a parabolic trajectory. In the first series of tests the aluminum was contained in a vacuum sealed, pyrolytic boron nitride crucible. An ullage space was present during each test. Void formation was recorded for two cases: a nonwetting system, and a wetting system where wetting occurred between the aluminum and the crucible lid. The void formation in the nonwetting case was similar in normal and reduced gravity, with a single vapor cavity forming at the top of the crucible. In the wetting case during reduced gravity surface tension caused two voids to form in the top corners of the crucible, but during normal gravity only one large void formed across the top. In the second series of tests the aluminum was contained in a pyrolytic boron nitride crucible that was placed in a stainless steel container and sealed in an environment of argon plus 4 percent hydrogen. An ullage space was present during each test. Void formation was recorded for two cases: a nonwetting system, and a wetting system where wetting occurred between the aluminum and one side wall and the lid. The void for nation in the nonwetting case was similar in normal and reduced gravity, with a single vapor cavity forming at the top of the crucible, although the meniscus became more convex in reduced gravity. In the wetting case the aluminum did not climb up the corners in 1g, and one large symmetric void resulted at the top when the aluminum had solidified. In the wetting case during reduced gravity the molten aluminum was drawn up the wetted wall and partially across the lid by a capillary underpressure; however, on the nonwetting wall the aluminum moved down. One void resulted along the nonwetting side of the container continuing to the top on the same side.

Chiaramonte, Francis Paul, III↗

Stochastic exciton-scattering theory of optical line shapes: Renormalized many-body contributions

Spectral line shapes provide a window into the local environment coupled to a quantum transition in the condensed phase. In this paper, we build upon a stochastic model to account for non-stationary background processes produced by broad-band pulsed laser stimulation, as distinguished from those for stationary phonon bath. In particular, we consider the contribution of pair-fluctuations arising from the full bosonic many-body Hamiltonian within a mean-field approximation, treating the coupling to the system as a stochastic noise term. Herein, using the Itô transformation, we consider two limiting cases for our model, which lead to a connection between the observed spectral fluctuations and the spectral density of the environment. In the first case, we consider a Brownian environment and show that this produces spectral dynamics that relax to form dressed excitonic states and recover an Anderson–Kubo-like form for the spectral correlations. In the second case, we assume that the spectrum is Anderson–Kubo like and invert to determine the corresponding background. Using the Jensen inequality, we obtain an upper limit for the spectral density for the background. The results presented here provide the technical tools for applying the stochastic model to a broad range of problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long Focal Length Large Mirror Fabrication System

The goals of this ambitious program are (1) to develop systems to make large superpolished optical mirrors, (2) to develop low scatter polishing techniques using centrifugal elutriation, (3) to develop a means of measuring scatter at any point on the mirror, (4) to polish a Hindle sphere to measure the optical figure of a one meter diameter convex mandrel, and (5) to fabricate low scatter, large adaptive optic graphite filled, cyanate ester replica transfer mirrors using these mandrels. Deliverables are a 30 cm diameter superpolished composite AO mirror. We fabricated a 1/3rd meter superpolished zerodur flat mandrel and with the support of our major subcontractor, Composite Mirror Applications Inc (CMA) we have demonstrated a 30 cm lightweight cyanate ester mirror with an rms microroughness between 0.6 and 0.8 nm and 8 faceplate influence function of 5 cm. The influence function was chosen to be comparable to the atmospheric correlation coefficient r(sub 0) which is about 5 cm at sea level. There was no print-thru of the graphite fibers in the cyanate ester surface (the bane of many previous efforts to use cyanate ester mirrors). Our subcontractor has devised a means for developing a 30-50 nm thick layer of graphite free pure ester resin on the surface of the mirrors. This graphite fiber filled material has a thermal expansion coefficient in the 10(exp -8) centimeter per Kelvin range (the same range of expansion coefficient as Zerodur and ULE glasses) and does not take up water and swell, so it is a nearly ideal mirror material in these areas. Unfortunately for these 0.8mm thick faceplates, the number of plies is not enough to result in isometric coverage. Isolated figure irregularities can appear, making it necessary to go to thicker faceplates. The influence function will then only approximate the length of r(sub 0), at higher altitudes or longer wavelengths. The influence function goes as the cube of the thickness, so we are now making a faceplate optimized for an infrared wavelength, possibly that used for the AO system of the Keck telescope, instead of 0.63 microns. We have polished a 55 cm diameter mandrel to better than 1/20th wave optical figure in the visible using centrifugal elutriation. CMA has just told us that it needs to retool to get optimum mirror faceplate quality in this size, so implementing the 55 cm AO mirror may be delayed somewhat. We expect to complete our 1/3 rd meter AO mirror on time using novel piezoelectric actuators with a throw of one micrometer per volt, as compared to 0.005 micrometers per volt for conventional piezoelectric actuators. We will then demonstrate its AO performance interferometrically.

Bennett, H. E.↗