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DOE OSTI2022

The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era

Sensors, enabling observations across vast spatial, spectral, and temporal scales, are major data generators for information technology (IT). Processing, storing, and communicating this ever-growing amount of data pose challenges for the current IT infrastructure. Edge computing—an emerging paradigm to overcome the shortcomings of cloud-based computing—could address these challenges. Furthermore, emerging technologies such as quantum computing, quantum sensing, and quantum communications have the potential to fill the performance gaps left by their classical counterparts. Here, we present the concept of an edge quantum computing (EQC) simulator—a platform for designing the next generation of edge computing applications. An EQC simulator is envisioned to integrate elements from both quantum technologies and edge computing to allow studies of quantum edge applications. The presented concept is motivated by the increasing demand for more sensitive and precise sensors that can operate faster at lower power consumption, generating both larger and denser datasets. These demands may be fulfilled with edge quantum sensor networks. Envisioning the EQC era, we present our view on how such a scenario may be amenable to quantification and design. Given the cost and complexity of quantum systems, constructing physical prototypes to explore design and optimization spaces is not sustainable, necessitating EQC infrastructure and component simulators to aid in co-design. We discuss what such a simulator may entail and possible use cases that invoke quantum computing at the edge integrated with new sensor infrastructures.

47 OTHER INSTRUMENTATION↗

NASA NTRS1975

Thermal/acoustical aircraft insulation material

Attempts made to improve the acoustical properties of low density Fiberfrax foam, an aircraft insulation material, are reported. Characterizations were also made of the physical and thermal properties. Two methods, optimization of fiber blend composition and modification of the foam fabrication process, were examined as possible means of improving foam acoustics. Flame impingement tests were also made; results show performance was satisfactory.

Struzik, E. A.↗

NASA NTRS1976

Specification of inputs and instrumentation for flutter testing of multivariable systems

The application of system identification methods in flutter testing of aeroelastic structure is discussed. The accuracy with which flutter parameters are estimated depends upon the test plan and on the algorithms used to reduce the data. The techniques for selecting the kinds and optimal positions of inputs and instrumentation, under typical test constraints, are presented. Identification results for both the input/output transfer function and the value of physical parameters are given. Numerical results on the optimal input spectrum and the accelerometer location for estimating flutter parameters of a two dimensional wing are obtained using these algorithms. Current work on applying system identification methods to high order three dimensional aeroelastic structures is reported.

Gupta, N. K.↗

NASA NTRS1981

Longitudinal grooves for bluff body drag reduction

Wind tunnel test results are presented for four axisymmetric bluff body configurations in order to determine their effect on form and pressure drag. It was found that drag reductions on the order of 40% are obtainable with an afterbody incorporating four longitudinal 'V' grooves. Although this effect may be due to the functioning of the grooves as longitudinal, continuous vortex generators, it is concluded that further research is needed to elucidate the physical basis of the test results. Optimization of the effect will be useful in base drag reduction for such vehicles as automobiles and cargo aircraft with sharply upswept afterbodies.

Quass, B.↗

NASA NTRS1988

Results of an integrated structure-control law design sensitivity analysis

Next generation air and space vehicle designs are driven by increased performance requirements, demanding a high level of design integration between traditionally separate design disciplines. Interdisciplinary analysis capabilities have been developed, for aeroservoelastic aircraft and large flexible spacecraft control for instance, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changess in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient that finite difference methods for the computation of the equivalent sensitivity information.

Gilbert, Michael G.↗

NASA NTRS1989

Results of an integrated structure/control law design sensitivity analysis

A design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations is discussed. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changes in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient than finite difference methods for the computation of the equivalent sensitivity information.

Gilbert, Michael G.↗

NASA NTRS1989

Aeroservoelastic modeling and applications using minimum-state approximations of the unsteady aerodynamics

The theoretical basis of flexible-aircraft modeling techniques encompassing aerodynamic, control, and elastic-structure effects is investigated analytically, with a focus on methods which employ minimum-state approximations for the unsteady aerodynamics. Rational-function approximations to generalized aerodynamic forces are reviewed; constraints and lag-coefficient optimization are explained; the problem of physical weighting in the minimum-state equations of motion is examined; and results of typical analyses from the NASA Active Flexible Wing project (Perry et al., 1988) are presented in extensive tables and graphs and discussed in detail. The minimum-state approach is shown to produce accurate models at significantly reduced computation costs.

Tiffany, Sherwood H.↗

NASA NTRS1991

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗

NASA NTRS1991

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models using test data has been developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗

NASA NTRS1993

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗

NASA NTRS1994

Calculation of near optimum design of InP/In(0.53)Ga(0.47)As monolithic tandem solar cells

An analysis of InP/GaAs tandem solar cell structure has been undertaken to allow for maximum AMO conversion efficiencies (space applications) while still taking into account both the theoretical and technological limitations. The dependence of intrinsic and extrinsic parameters such as diffusion lengths and generation-recombination (GR) lifetimes on N/P and P/N devices performances are clearly demonstrated. We also report for the first time the improvement attainable through the use of a new patterned tunnel junction as the inter cell ohmic interconnect. Such a design minimizes the light absorption in the interconnect region and leads to a noticeable increase in the cell efficiency. Our computations predict 27 percent AMO efficiency for N/P tandems with ideality factor gamma = 2 (GR lifetimes approximately equal 1 micron), and 36 percent for gamma = 1 (GR lifetimes approximately equals 100 microns). The method of optimization and the values of the physical and optical parameters are discussed.

Renaud, P.↗

NASA NTRS2003

Structured Uncertainty Bound Determination From Data for Control and Performance Validation

This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.

Lim, Kyong B.↗

NASA NTRS2009

Sonic Boom Research at NASA Dryden: Objectives and Flight Results from the Lift and Nozzle Change Effects on Tail Shock (LaNCETS) Project

The principal objective of the Supersonics Project is to develop and validate multidisciplinary physics-based predictive design, analysis and optimization capabilities for supersonic vehicles. For aircraft, the focus will be on eliminating the efficiency, environmental and performance barriers to practical supersonic flight. Previous flight projects found that a shaped sonic boom could propagate all the way to the ground (F-5 SSBD experiment) and validated design tools for forebody shape modifications (F-5 SSBD and Quiet Spike experiments). The current project, Lift and Nozzle Change Effects on Tail Shock (LaNCETS) seeks to obtain flight data to develop and validate design tools for low-boom tail shock modifications. Attempts will be made to alter the shock structure of NASA's NF-15B TN/837 by changing the lift distribution by biasing the canard positions, changing the plume shape by under- and over-expanding the nozzles, and changing the plume shape using thrust vectoring. Additional efforts will measure resulting shocks with a probing aircraft (F-15B TN/836) and use the results to validate and update predictive tools. Preliminary flight results are presented and are available to provide truth data for developing and validating the CFD tools required to design low-boom supersonic aircraft.

Moes, Timothy R.↗

NASA NTRS2009

Optimization of Layer Densities for Spacecraft Multilayered Insulation Systems

Numerous tests of various multilayer insulation systems have indicated that there are optimal densities for these systems. However, the only method of calculating this optimal density was by a complex physics based algorithm developed by McIntosh. In the 1970's much data were collected on the performance of these insulation systems with many different variables analyzed. All formulas generated included number of layers and layer density as geometric variables in solving for the heat flux, none of them was in a differentiable form for a single geometric variable. It was recently discovered that by converting the equations from heat flux to thermal conductivity using Fourier's Law, the equations became functions of layer density, temperatures, and material properties only. The thickness and number of layers of the blanket were merged into a layer density. These equations were then differentiated with respect to layer density. By setting the first derivative equal to zero, and solving for the layer density, the critical layer density was determined. Taking a second derivative showed that the critical layer density is a minimum in the function and thus the optimum density for minimal heat leak, this is confirmed by plotting the original function. This method was checked and validated using test data from the Multipurpose Hydrogen Testbed which was designed using McIntosh's algorithm.

Johnson, W. L.↗

NASA NTRS2014

Simulation Tool for Dielectric Barrier Discharge Plasma Actuators

Traditional approaches for active flow separation control using dielectric barrier discharge (DBD) plasma actuators are limited to relatively low speed flows and atmospheric conditions. This results in low feasibility of the DBDs for aerospace applications. For active flow control at turbine blades, fixed wings, and rotary wings and on hypersonic vehicles, DBD plasma actuators must perform at a wide range of conditions, including rarified flows and combustion mixtures. An efficient, comprehensive, physically based DBD simulation tool can optimize DBD plasma actuators for different operation conditions. Researchers are developing a DBD plasma actuator simulation tool for a wide range of ambient gas pressures. The tool will treat DBD using either kinetic, fluid, or hybrid models, depending on the DBD operational condition.

Likhanskii, Alexander↗

NASA NTRS2016

Solar Array (Radiated/Non-Radiated): Materials Characterization and Cryogenic Thermal Cycling Qualification for the Planned Europa Clipper Mission (ECM)

Two special instruments were custom built for our critical study and manufactured and employed to test the SA materials of interest to cryogenic temperature conditions. We have procured custom manufactured two independent systems such as Thermo -Mechanical Analyzer (TMA) with Three Point Bend Probe (TPBP) module and Dilatometer. TMA can be used to measure Young’ s modulus or elastic modulus (e -modulus). Dilatometer can be used to measure Co -efficient of Thermal Expansion (CTE). We have optimized the materials configuration to measure physical properties of radiated and non -radiated materials for CTE and e -modulus, which will be useful to assess materials and processes reliability for cryogenic temperature applications. We have successfully implemented for some materials that are of interest to solar panels for the planned ECM project to measure CTE and Young's modulus. Also a separate study was undertaken to thermal cycle qualify SAs for ECM project. One can do thermal cycling to temperatures of 50 K and 133 K using liquid Helium (Lq He). This is in reality exorbitantly too expensive and is also inefficient. Furthermore, this is not technically controllable test to 133 K and 50 K temperatures. This is also too expensive to accomplish. Therefore, a vacuum set -up was made along with a cryostat successfully. This is a closed loop system where we do not lose the Helium gas. We were able to get to 35 K for a given test coupon size. These temperatures are lower than what we would intend to qualify the solar array technologies. This will allow to have some margin at cold temperatures. We successfully completed the qualification of solar array technologies down to 50 K temperatures. This is the first time we are reporting this accomplishment. In this paper, we will present the solar array materials properties for cryogenic temperatures down to 20 K temperatures and the thermal cycling qualification test results from 133 K to 50 K for three times the mission life of 120 thermal cycles to meet JPL Design.

Ramesham, Rajeshuni↗

NASA NTRSDate not supplied

A NASA Perspective on Quantum AI, Error Correction, and Beyond

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. We discuss the prospects for quantum computing and AI, highlighting advances in algorithms, both near- and longer-term. Quantum error correction is critical to the realization of any such vision. The talk with touch on some recent exciting advanced in quantum error correction, particularly in dynamical codes. The talk will conclude with an example of how the combination of quantum computing and artificial intelligence can help probe fundamental aspect of quantum physics.

quantum optimization algorithms and sampling↗

NASA NTRSDate not supplied

An Optimization-Based Toolchain for Parametric Mechanism Design

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗