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At least 1,297 records · Page 72

Methodology and method and apparatus for signaling with capacity optimized constellations

Communication systems having transmitter, includes a coder configured to receive user bits and output encoded bits at an expanded output encoded bit rate, a mapper configured to map encoded bits to symbols in a symbol constellation, a modulator configured to generate a signal for transmission via the communication channel using symbols generated by the mapper. In addition, the receiver includes a demodulator configured to demodulate the received signal via the communication channel, a demapper configured to estimate likelihoods from the demodulated signal, a decoder that is configured to estimate decoded bits from the likelihoods generated by the demapper. Furthermore, the symbol constellation is a capacity optimized geometrically spaced symbol constellation that provides a given capacity at a reduced signal-to-noise ratio compared to a signal constellation that maximizes d.sub.min.

Barsoum, Maged F.↗

Methodology and method and appartus for signaling with capacity optimized constellations

Communication systems are described that use geometrically shaped constellations that have increased capacity compared to conventional constellations operating within a similar SNR band. In several embodiments, the geometrically shaped is optimized based upon a capacity measure such as parallel decoding capacity or joint capacity. In many embodiments, a capacity optimized geometrically shaped constellation can be used to replace a conventional constellation as part of a firmware upgrade to transmitters and receivers within a communication system. In a number of embodiments, the geometrically shaped constellation is optimized for an Additive White Gaussian Noise channel or a fading channel.

Barsoum, Maged F.↗

Methodology and Method and Apparatus for Signaling With Capacity Optimized Constellations

Communication systems are described that use geometrically shaped constellations that have increased capacity compared to conventional constellations operating within a similar SNR band. In several embodiments, the geometrically shaped is optimized based upon a capacity measure such as parallel decoding capacity or joint capacity. In many embodiments, a capacity optimized geometrically shaped constellation can be used to replace a conventional constellation as part of a firmware upgrade to transmitters and receivers within a communication system. In a number of embodiments, the geometrically shaped constellation is optimized for an Additive White Gaussian Noise channel or a fading channel. In numerous embodiments, the communication uses adaptive rate encoding and the location of points within the geometrically shaped constellation changes as the code rate changes.

Barsoum, Maged F.↗

Method and Apparatus for Generating Flight-Optimizing Trajectories

An apparatus for generating flight-optimizing trajectories for a first aircraft includes a receiver capable of receiving second trajectory information associated with at least one second aircraft. The apparatus also includes a traffic aware planner (TAP) module operably connected to the receiver to receive the second trajectory information. The apparatus also includes at least one internal input device on board the first aircraft to receive first trajectory information associated with the first aircraft and a TAP application capable of calculating an optimal trajectory for the first aircraft based at least on the first trajectory information and the second trajectory information. The optimal trajectory at least avoids conflicts between the first trajectory information and the second trajectory information.

Ballin, Mark G.↗

Methodology and Method and Apparatus for Signaling with Capacity Optimized Constellations

Communication systems are described that use geometrically shaped constellations that have increased capacity compared to conventional constellations operating within a similar SNR band. In several embodiments, the geometrically shaped is optimized based upon a capacity measure such as parallel decoding capacity or joint capacity. In many embodiments, a capacity optimized geometrically shaped constellation can be used to replace a conventional constellation as part of a firmware upgrade to transmitters and receivers within a communication system. In a number of embodiments, the geometrically shaped constellation is optimized for an Additive White Gaussian Noise channel or a fading channel.

Barsoum, Maged F.↗

Lunar Terrain and Albedo Reconstruction from Apollo Imagery

Generating accurate three dimensional planetary models and albedo maps is becoming increasingly more important as NASA plans more robotics missions to the Moon in the coming years. This paper describes a novel approach for separation of topography and albedo maps from orbital Lunar images. Our method uses an optimal Bayesian correlator to refine the stereo disparity map and generate a set of accurate digital elevation models (DEM). The albedo maps are obtained using a multi-image formation model that relies on the derived DEMs and the Lunar- Lambert reflectance model. The method is demonstrated on a set of high resolution scanned images from the Apollo era missions.

Nefian, Ara V.↗

On Managing the Use of Surrogates in General Nonlinear Optimization and MDO

This paper is concerned with a trust region approximation management framework (AMF) for solving the nonlinear programming problem in general and multidisciplinary optimization problems in particular The intent of the AMF methodology is to facilitate the solution of optimization problems with high-fidelity models. While such models are designed to approximate the physical phenomena they describe to a high degree of accuracy, their use in a repetitive procedure, for example, iterations of an optimization or a search algorithm, make such use prohibitively expensive. An improvement in design with lower-fidelity, cheaper models, however, does not guarantee a corresponding improvement for the higher-fidelity problem. The AMF methodology proposed here is based on a class of multilevel methods for constrained optimization and is designed to manage the use of variable-fidelity approximations or models in a systematic way that assures convergence to critical points of the original high-fidelity problem.

Alexandrov, Natalia M.↗

Early Estimation of Solar Activity Cycle: Potential Capability and Limits

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and longterm sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Kitiashvili, Irina N.↗

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗

Using Data Assimilation Methods for Prediction of Solar Activity

The variability of solar magnetic activity known as the 11-­‐year solar cycles has the longest history of observations. These solar cycles dramatically affect conditions in the heliosphere and the Earth’s space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-­‐term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model complemented by the equation of magnetic helicity conservation and long-­‐term sunspot data series. This approach has allowed us to reproduce the general properties of the solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Solar Activity↗

Bio-inspired Surface Structures to Mitigate Interfacial Particle Adhesion and Erosion - A Review

Lunar dust known as regolith is a huge challenge for lunar exploration missions. Formed over millennia by a complex process involving impacts of meteoroids and micrometeoroids on the lunar surface, lunar dust is porous, highly abrasive with sharp jagged edges, chemically reactive, electrostatically charged and sometimes magnetic. The chemical composition and thickness of the dust layer also varies in different regions of the lunar surface. From samples obtained by previous lunar missions, the average particle size is below 100 microns. This dust has the tendency to strongly adhere to any exposed surfaces, and often degrades the material functionality to eventually cause failure. Any material on the lunar surface is also subject to harsh temperature cycles ranging from -178 ̊C to + 123 ̊C and extreme ultraviolet radiation. While on the lunar surface, different classes of materials would be required for different applications. Advanced materials have been and will be used throughout the lunar lander, habitat, and mission equipment. Examples include: polymeric materials for astronaut protective clothing; metals and ceramics for the lunar lander legs and habitats, and excavating equipment; and semiconductors for solar panels and on-board electronics. In all these applications, the surfaces of the materials are expected or understood to be exposed to the extreme lunar environment condition that includes the regolith dust. During the Apollo missions, the dust clung to and abraded the astronaut’s suits, degraded seals, optics, clogged sensors and reduced performance of thermal radiators. The lunar dust adheres to the surface by various mechanisms, which include electrostatic and Coulombic interactions, Van-der-Waals forces, magnetic forces, mechanical interlocking, chemical bonding and donor-acceptor interactions. There are three primary strategies for developing technologies to minimize the lunar dust adhesion: active, passive and a combination of active and passive. In the active approach, an external energy is needed to prevent or remove particles from collecting on the surface. Mechanically powered brushes and electrodynamic dust screens are two examples. In the passive approach, no external power is needed, and the material surface properties are able to mitigate dust adhesion. A well-known example of this strategy is the low work function coatings for non-stick surfaces. In most cases a combination of active and passive methods might be needed to optimally manage the lunar regolith. The passive method is significantly more attractive as it does not require any external power or an additional control subsystem. These approaches optimize the mission payload and reduce risk. Surface modification to minimize the dust adhesion is thus very important to lunar missions. Here, naturally evolved surface structures might provide guidance for solutions. There are several factors that have to be considered for minimizing particle adhesion to a surface. These include the substrate material properties, surface topography, chemistry, and the characteristics of the adhering particles. When engineering a surface, the substrate material chosen would be dependent on the needs of the application. Tailoring the surface microstructure or chemistry opens up more possibilities for its optimal utilization

Lunar Dust↗

Ultrasonic NDE Simulation for Composite Manufacturing Defects

The increased use of composites in aerospace components is expected to continue into the future. The large scale use of composites in aerospace necessitates the development of composite-appropriate nondestructive evaluation (NDE) methods to quantitatively characterize defects in as-manufactured parts and damage incurred during or post manufacturing. Ultrasonic techniques are one of the most common approaches for defect/damage detection in composite materials. One key technical challenge area included in NASA's Advanced Composite's Project is to develop optimized rapid inspection methods for composite materials. Common manufacturing defects in carbon fiber reinforced polymer (CFRP) composites include fiber waviness (in-plane and out-of-plane), porosity, and disbonds; among others. This paper is an overview of ongoing work to develop ultrasonic wavefield based methods for characterizing manufacturing waviness defects. The paper describes the development and implementation of a custom ultrasound simulation tool that is used to model ultrasonic wave interaction with in-plane fiber waviness (also known as marcelling). Wavefield data processing methods are applied to the simulation data to explore possible routes for quantitative defect characterization.

Leckey, Cara A. C.↗

Numerical Procedures for Inlet/Diffuser/Nozzle Flows

Two primitive variable, pressure based, flux-split, RNS/NS solution procedures for viscous flows are presented. Both methods are uniformly valid across the full Mach number range, Le., from the incompressible limit to high supersonic speeds. The first method is an 'optimized' version of a previously developed global pressure relaxation RNS procedure. Considerable reduction in the number of relatively expensive matrix inversion, and thereby in the computational time, has been achieved with this procedure. CPU times are reduced by a factor of 15 for predominantly elliptic flows (incompressible and low subsonic). The second method is a time-marching, 'linearized' convection RNS/NS procedure. The key to the efficiency of this procedure is the reduction to a single LU inversion at the inflow cross-plane. The remainder of the algorithm simply requires back-substitution with this LU and the corresponding residual vector at any cross-plane location. This method is not time-consistent, but has a convective-type CFL stability limitation. Both formulations are robust and provide accurate solutions for a variety of internal viscous flows to be provided herein.

Rubin, Stanley G.↗

Parallel and vector computation for stochastic optimal control applications

A general method for parallel and vector numerical solutions of stochastic dynamic programming problems is described for optimal control of general nonlinear, continuous time, multibody dynamical systems, perturbed by Poisson as well as Gaussian random white noise. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random atmospheric fluctuations. The numerical formulation is highly suitable for a vector multiprocessor or vectorizing supercomputer, and results exhibit high processor efficiency and numerical stability. Advanced computing techniques, data structures, and hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations.

Hanson, F. B.↗

Fuel-Optimal Trajectory Optimization of Mach 0.745 Transonic Truss-Braced Wing with Variable Camber Continuous Trailing Edge Flap

This paper describes a fuel-optimal trajectory optimization of the Mach 0.745 Transonic Truss-Braced Wing with the variable camber continuous trailing edge flaps (VCCTEF) capable of changing the chordwise pressure distribution and spanwise lift distribution to minimize drag. The trajectory optimization is posed as a minimization of the fuel burn over a fixed cruise range. The trajectory optimization is formulated by the adjoint method which results in a two-point boundary value problem. A numerical shooting method is implemented to solve the minimum-fuel trajectory optimization. The results indicates a fuel burn reduction of 793 lbs or 5.5% for a cruise range of 3000 miles. An approximate trajectory optimization is proposed using a single adjoint variable. This leads to a greatly simplified analytical solution of the adjoint solution. The results of the approximate trajectory optimization are in excellent agreement with those obtained by the shooting method. The approximate trajectory optimization produces a fuel burn reduction of 615 lbs or 4.3%.

Trajectory Optimization↗

Adjoint-Based Minimization of X-59 Sonic Boom Noise Via Control Surfaces

A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by a supersonic aircraft's sonic boom is presented. A gradient-based optimizer is coupled with a Cartesian Euler flow solver and an atmospheric propagation tool to forge a unique design capability. Adjoint formulations for both the flow solver and propagation tool are also coupled to provide sensitivities in an efficient manner. The design method is demonstrated on the X-59 Low-Boom Flight Demonstrator by optimizing control surface deflections to improve ground-level noise while maintaining trimmed cruise flight. Two noise minimization examples and a noise maximization are presented. All optimized designs result in measurable improvement in the ground-level noise objective. Extensive surveys of the design space confirm that the optimization method is effective in finding a local optimum. Moreover, repeated application of the method with varying initial design points also demonstrates the robustness of the method.

ARMD↗

Reference Command Optimization for the Transition Flight Mode of a Lift plus Cruise Vehicle

Advanced air mobility mainly utilizes vehicles that are capable of vertical takeoff and landing (VTOL) for the simplicity of operation and large-scale deployment. However, VTOL vehicles need specialized trajectory and command design for the transition phase, where the vehicles transition between rotor-borne flight and wing-borne flight. Since VTOL vehicles are commonly designed as over-actuated systems for redundancy, one challenge that arises is actuator ambiguity, where it is unclear how to uniquely command actuators for the VTOL vehicle to track a given trajectory. We propose a method to design optimal reference commands for the transition mode. By formulating an 𝑙 1 -norm cost function on the rotor thrusts of the vehicle, we can achieve economical operation of the rotors such that they only operate when necessary and efficiently utilize the aerodynamics to save energy from reduced rotor actuation. We validate our approach in simulations and show its benefit compared to the commonly used differential flatness-based method.

John L Bullock↗