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NASA NTRS1999

Integration of a Decentralized Linear-Quadratic-Gaussian Control into GSFC's Universal 3-D Autonomous Formation Flying Algorithm

A decentralized control is investigated for applicability to the autonomous formation flying control algorithm developed by GSFC for the New Millenium Program Earth Observer-1 (EO-1) mission. This decentralized framework has the following characteristics: The approach is non-hierarchical, and coordination by a central supervisor is not required; Detected failures degrade the system performance gracefully; Each node in the decentralized network processes only its own measurement data, in parallel with the other nodes; Although the total computational burden over the entire network is greater than it would be for a single, centralized controller, fewer computations are required locally at each node; Requirements for data transmission between nodes are limited to only the dimension of the control vector, at the cost of maintaining a local additional data vector. The data vector compresses all past measurement history from all the nodes into a single vector of the dimension of the state; and The approach is optimal with respect to standard cost functions. The current approach is valid for linear time-invariant systems only. Similar to the GSFC formation flying algorithm, the extension to linear LQG time-varying systems requires that each node propagate its filter covariance forward (navigation) and controller Riccati matrix backward (guidance) at each time step. Extension of the GSFC algorithm to non-linear systems can also be accomplished via linearization about a reference trajectory in the standard fashion, or linearization about the current state estimate as with the extended Kalman filter. To investigate the feasibility of the decentralized integration with the GSFC algorithm, an existing centralized LQG design for a single spacecraft orbit control problem is adapted to the decentralized framework while using the GSFC algorithm's state transition matrices and framework. The existing GSFC design uses both reference trajectories of each spacecraft in formation and by appropriate choice of coordinates and simplified measurement modeling is formulated as a linear time-invariant system. Results for improvements to the GSFC algorithm and a multiple satellite formation will be addressed. The goal of this investigation is to progressively relax the assumptions that result in linear time-invariance, ultimately to the point of linearization of the non-linear dynamics about the current state estimate as in the extended Kalman filter. An assessment will then be made about the feasibility of the decentralized approach to the realistic formation flying application of the EO-1/Landsat 7 formation flying experiment.

Folta, David C.↗

DOE OSTI2025

Sylvester-preconditioned adaptive-rank implicit time integrators for advection-diffusion equations with variable coefficients

Here, we consider the adaptive-rank integration of multi-dimensional time-dependent advection-diffusion partial differential equations (PDEs) with variable coefficients. We employ a standard finite-difference method for spatial discretization coupled with high-order diagonally implicit Runge-Kutta temporal schemes. The discrete equation is a generalized Sylvester equation (GSE), which we solve with a projection-based adaptive-rank algorithm structured around two key strategies: (i) constructing dimension-wise subspaces using a novel atypical extended Krylov strategy, and (ii) efficiently solving the basis coefficient matrix with a preconditioned GMRES solver. The low-rank decomposition is performed in 2D using SVD and with high-order SVD (HOSVD) in 3D to represent the tensor in a compressed Tucker format. For d-dimensional problems (here, d = 2 or 3), the computational complexity and memory storage of the approach are found numerically to scale as and $\mathscr{O}(Nr^2) + \mathscr{O} (r^{d+1})$ and $\mathscr{O}(Nr) + \mathscr{O} (r^{d})$, respectively, with the one-dimensional resolution and the maximal rank during the Krylov iteration (which we find to be largely independent of on our numerical examples). We present numerical examples that illustrate the advertised properties of the algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Semi-implicit time integration of atmospheric flows with characteristic-based flux partitioning

Here, this paper presents a characteristic-based flux partitioning for the semi-implicit time integration of atmospheric flows. Nonhydrostatic models require the solution of the compressible Euler equations. The acoustic time scale is significantly faster than the advective scale, yet it is typically not relevant to atmospheric and weather phenomena. The acoustic and advective components of the hyperbolic flux are separated in the characteristic space. High-order, conservative additive Runge-Kutta methods are applied to the partitioned equations so that the acoustic component is integrated in time implicitly with an unconditionally stable method, while the advective component is integrated explicitly. The time step of the overall algorithm is thus determined by the advective scale. Benchmark flow problems are used to demonstrate the accuracy, stability, and convergence of the proposed algorithm. The computational cost of the partitioned semi-implicit approach is compared with that of explicit time integration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

SU-F-BRF-13: Investigating the Feasibility of Accurate Dose Measurement in a Deforming Radiochromic Dosimeter

Purpose: Presage-Def, a deformable radiochromic 3D dosimeter, has been previously shown to have potential for validating deformable image registration algorithms. This work extends this effort to investigate the feasibility of using Presage-Def to validate dose-accumulation algorithms in deforming structures. Methods: Two cylindrical Presage-Def dosimeters (8cm diameter, 4.5cm length) were irradiated in a water-bath with a simple 4-field box treatment. Isocentric dose was 20Gy. One dosimeter served as control (no deformation) while the other was laterally compressed during irradiation by 21%. Both dosimeters were imaged before and after irradiation with a fast (∼10 minutes for 1mm isotropic resolution), broad beam, high resolution optical-CT scanner. Measured dose distributions were compared to corresponding distributions calculated by a commissioned Eclipse planning system. Accuracy in the control was evaluated with 3D gamma (3%/3mm). The dose distribution calculated for the compressed dosimeter in the irradiation geometry cannot be directly compared via profiles or 3D gamma to the measured distribution, which deforms with release from compression. Thus, accuracy under deformation was determined by comparing integral dose within the high dose region of the deformed dosimeter distribution versus calculated dose. Dose profiles were used to study temporal stability of measured dose distributions. Results: Good dose agreement was demonstrated in the control with a 3D gamma passing rate of 96.6%. For the dosimeter irradiated under compression, the measured integral dose in the high dose region (518.0Gy*cm3) was within 6% of the Eclipse-calculated integral dose (549.4Gy*cm3). Elevated signal was noted on the dosimeter edge in the direction of compression. Change in dosimeter signal over 1.5 hours was ≤2.7%, and the relative dose distribution remained stable over this period of time. Conclusion: Presage-Def is promising as a 3D dosimeter capable of accurately measuring dose in a deforming structure, and warrants further study to quantify comprehensive accuracy at different levels of deformation. This work was supported by NIH R01CA100835. John Adamovics is the president of Heuris Inc., which commercializes PRESAGE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals

We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in contrast to the work (Daubechies et al., Pure Appl. Math. 57(11), 1413–1457, 2004), where the single vector signal can be infinite-dimensional, and (Fornasier and Rauhut, SIAM J. Numer. Anal. 46(2), 577613, 2008), which extends the aforementioned work to the joint sparse recovery of finite number of infinite-dimensional vectors. In our case, to take account of the joint sparsity and promote the coupling of nonvanishing components, we employ a convex relaxation approach with mixed norm penalty ℓ 2,1 . This paper discusses the computation of the solutions of linear inverse problems with such relaxation by a forward-backward splitting algorithm. However, since the solution matrix possesses infinitely many columns, the arguments of Daubechies et al. (Pure Appl. Math. 57(11), 1413–1457, 2004) no longer apply. As such, we establish new strong convergence results for the algorithm, in particular when the set of jointly sparse vectors is infinite.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Advanced Shuttle Strategies for Parallel QCCD Architectures

Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Exploitation of Defects in High Entropy Ceramic Barrier Materials

A critical mission need exists to develop new materials that can withstand extreme environments and multiple sequential threats. High entropy materials, those containing 5 or more metals, exhibit many exciting properties which would potentially be useful in such situations. However, a particularly hard challenge in developing new high entropy materials is determining a priori which compositions will form the desired single phase material. The project outlined here combined several modeling and experimental techniques to explore several structure-property-relationships of high entropy ceramics in an effort to better understand the connection between their compositional components, their observed properties, and stability. We have developed novel machine learning algorithms which rapidly predict stable high entropy ceramic compositions, identified the stability interplay between configurational entropy and cation defects, and tested the mechanical stability of high entropy oxides using the unique capabilities at the Dynamic Compression Sector facility and the Saturn accelerator.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High Speed Data Acquisition for Real Time Feedback in a Light Duty Engine Combustion-Mode Switching Application

The paper describes the integration of a high-speed data acquisition and diagnostics controller used in an advanced engine platform. The controller enables ultra-low emissions and new benchmarks of engine efficiency while running a Gasoline Compression Ignition (GCI) cycle on a 2.2L, 4-cylinder engine. The system enables real-time combustion feedback and vibration analysis in engines. The paper focuses on: (1) the development of an interpolative sampling algorithm for transposition of time acquired data to the crank angle domain using a production crank sensor (60-2 tooth wheel); (2) the control unit, high-speed data acquisition, communication rates between the dedicated data acquisition and base controller to ensure cycle-to-cycle feedback; and, (3) validation exercises using cylinder pressure measurements. Here, the study shows how the algorithm resolves cylinder pressure information over an engine cycle, validating its robustness across acquisition rates of 50 and 200 kHz, with crank angle resolutions of 0.5° and 0.1°. Results show that the 50 kHz, 0.5° hardware yield combustion phasing and torque estimates within 0.1° and 1% torque of those attained with the 200 kHz, 0.1° hardware. Finally, study shows the dedicated controller and communication speeds allow for next-cycle fuel injection correction for speeds above 5000 rpm.

42 ENGINEERING↗

NASA NTRS1985

Developments in the simulation of separated flows using finite difference methods

Compressible viscous flow simulation using finite difference Navier-Stokes and viscous-inviscid interaction methods is described. Recent developments are reviewed that significantly improve the computational efficiency of approximately factored implicit Navier-Stokes algorithms. Compared to Navier-Stokes codes, modern viscous-inviscid interaction codes are more computationally efficient, but have restricted application and are more complicated to program. Therefore, less efficient but more general viscous-inviscid interaction methods are investigated that use forcing functions instead of boundary condition matching, and a simple, direct/inverse, three-dimensional, finite-difference, boundary layer code is presented.

Steger, J. L.↗

NASA NTRS1992

Three-dimensional shock-wave/boundary-layer interactions with bleed through a circular hole

Computations were performed to study three-dimensional (3-D), shock-wave/boundary-layer interactions on a flat plate in which fluid in the boundary layer was bled through a circular hole into a plenum to control shock-wave induced separation. Results are presented which show the details of the 3-D flowfield about the bleed hole and how bleed-hole placement relative to shock-wave impingement affect upstream, spanwise, and downstream influence lengths. This study revealed an underlying mechanisms by which bleed holes can affect shock-wave/boundary-layer interactions. This investigation is based on the ensemble-averaged, "full-compressible" Navier-Stokes equations closed by the Baldwin-Lomax turbulence model. Solutions to these equations were obtained by an implicit finite-volume method based on the partially-split, two-factored algorithm of Steger.

Rimlinger, M. J.↗

NASA NTRS1992

Volume 2: Explicit, multistage upwind schemes for Euler and Navier-Stokes equations

The objective of this study was to develop a high-resolution-explicit-multi-block numerical algorithm, suitable for efficient computation of the three-dimensional, time-dependent Euler and Navier-Stokes equations. The resulting algorithm has employed a finite volume approach, using monotonic upstream schemes for conservation laws (MUSCL)-type differencing to obtain state variables at cell interface. Variable interpolations were written in the k-scheme formulation. Inviscid fluxes were calculated via Roe's flux-difference splitting, and van Leer's flux-vector splitting techniques, which are considered state of the art. The viscous terms were discretized using a second-order, central-difference operator. Two classes of explicit time integration has been investigated for solving the compressible inviscid/viscous flow problems--two-state predictor-corrector schemes, and multistage time-stepping schemes. The coefficients of the multistage time-stepping schemes have been modified successfully to achieve better performance with upwind differencing. A technique was developed to optimize the coefficients for good high-frequency damping at relatively high CFL numbers. Local time-stepping, implicit residual smoothing, and multigrid procedure were added to the explicit time stepping scheme to accelerate convergence to steady-state. The developed algorithm was implemented successfully in a multi-block code, which provides complete topological and geometric flexibility. The only requirement is C degree continuity of the grid across the block interface. The algorithm has been validated on a diverse set of three-dimensional test cases of increasing complexity. The cases studied were: (1) supersonic corner flow; (2) supersonic plume flow; (3) laminar and turbulent flow over a flat plate; (4) transonic flow over an ONERA M6 wing; and (5) unsteady flow of a compressible jet impinging on a ground plane (with and without cross flow). The emphasis of the test cases was validation of code, and assessment of performance, as well as demonstration of flexibility.

Elmiligui, Alaa↗

NASA NTRS1990

Numerical solution of the incompressible Navier-Stokes equations

The current work is initiated in an effort to obtain an efficient, accurate, and robust algorithm for the numerical solution of the incompressible Navier-Stokes equations in two- and three-dimensional generalized curvilinear coordinates for both steady-state and time-dependent flow problems. This is accomplished with the use of the method of artificial compressibility and a high-order flux-difference splitting technique for the differencing of the convective terms. Time accuracy is obtained in the numerical solutions by subiterating the equations in psuedo-time for each physical time step. The system of equations is solved with a line-relaxation scheme which allows the use of very large pseudo-time steps leading to fast convergence for steady-state problems as well as for the subiterations of time-dependent problems. Numerous laminar test flow problems are computed and presented with a comparison against analytically known solutions or experimental results. These include the flow in a driven cavity, the flow over a backward-facing step, the steady and unsteady flow over a circular cylinder, flow over an oscillating plate, flow through a one-dimensional inviscid channel with oscillating back pressure, the steady-state flow through a square duct with a 90 degree bend, and the flow through an artificial heart configuration with moving boundaries. An adequate comparison with the analytical or experimental results is obtained in all cases. Numerical comparisons of the upwind differencing with central differencing plus artificial dissipation indicates that the upwind differencing provides a much more robust algorithm, which requires significantly less computing time. The time-dependent problems require on the order of 10 to 20 subiterations, indicating that the elliptical nature of the problem does require a substantial amount of computing effort.

Rogers, Stuart E.↗

DOE OSTI2025

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

Abstract Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining comparable accuracy (Tsoi et al 2024 EPJ Web Conf. 295 09036). These capabilities are highly valuable in environments with stringent computational resource constraints, such as high-energy physics experiments at the CERN Large Hadron Collider. However, finding compact expressions for high-dimensional datasets remains challenging due to the inherent limitations of genetic programming (GP), the search algorithm of most symbolic regression (SR) methods. Contrary to GP, the NN approach to SR offers scalability to high-dimensional inputs and leverages gradient methods for faster equation searching. Common ways of constraining expression complexity often involve multistage pruning with fine-tuning, which can result in significant performance loss. In this work, we propose S y m b o l N e t , a NN approach to SR specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom hardware such as FPGAs. This framework allows dynamic pruning of model weights, input features, and mathematical operators in a single training process, where both training loss and expression complexity are optimized simultaneously. We introduce a sparsity regularization term for each pruning type, which can adaptively adjust its strength, leading to convergence at a target sparsity ratio. Unlike most existing SR methods that struggle with datasets containing more than O ( 10 ) inputs, we demonstrate the effectiveness of our model on the LHC jet tagging task (16 inputs), MNIST (784 inputs), and SVHN (3072 inputs).

Tsoi, Ho Fung (ORCID:0000000225502184)↗

DOE OSTI2026

Lyapunov controlled counterdiabatic quantum optimization

We introduce a quantum algorithm that integrates counterdiabatic (CD) protocols with quantum Lyapunov control (QLC) to address combinatorial optimization problems. This approach offers versatility, allowing implementation as either a digital-analog or purely digital algorithm based on selected control strategies. By examining spin-glass Hamiltonians, we illustrate how the algorithm can explore alternative paths to enhance solution outcomes compared to conventional CD techniques. This method reduces dependence on extensive higher-order CD terms and on classical optimization techniques, making it more suitable for existing quantum computing platforms. The combination of digital compression via CD protocols and the adaptable nature of QLC methods positions this approach as a promising candidate for near-term quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

TU-F-17A-07: Real-Time Personalized Margins

Purpose: To maximize normal tissue sparing for treatments requiring motion encompassing margins. Motion mitigation techniques including DMLC or couch tracking can freeze tumor motion within the treatment aperture potentially allowing for smaller treatment margins and thus better sparing of normal tissue. To enable for a safe application of this concept in the clinic we propose adapting margins dynamically in real-time during radiotherapy delivery based on personalized tumor localization confidence. To demonstrate technical feasibility we present a phantom study. Methods: We utilize a realistic anthropomorphic dynamic thorax phantom with a lung tumor model embedded close to the spine. The tumor, a 3D-printout of a patient's GTV, is moved 15mm peak-to-peak by diaphragm compression and monitored by continuous EPID imaging in real-time. Two treatment apertures are created for each beam, one representing ITV -based and the other GTV-based margin expansion. A soft tissue localization (STiL) algorithm utilizing the continuous EPID images is employed to freeze tumor motion within the treatment aperture by means of DMLC tracking. Depending on a tracking confidence measure (TCM), the treatment aperture is adjusted between the ITV and the GTV leaf. Results: We successfully demonstrate real-time personalized margin adjustment in a phantom study. We measured a system latency of about 250 ms which we compensated by utilizing a respiratory motion prediction algorithm (ridge regression). With prediction in place we observe tracking accuracies better than 1mm. For TCM=0 (as during startup) an ITV-based treatment aperture is chosen, for TCM=1 a GTV-based aperture and for 0<TCM<1 a linear interpolation between the two apertures is chosen. Conclusions: We have proposed and demonstrated a concept to safely shrink treatment margins during radiotherapy and adapt to tracking confidence in real-time. Normal tissue sparing is maximized. The worst case scenario results in delivering a plan with standard margins used in the clinic today.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Equation Discovery Using Fast Function Extraction: a Deterministic Symbolic Regression Approach

Advances in machine learning (ML) coupled with increased computational power have enabled identification of patterns in data extracted from complex systems. ML algorithms are actively being sought in recovering physical models or mathematical equations from data. This is a highly valuable technique where models cannot be built using physical reasoning alone. In this paper, we investigate the application of fast function extraction (FFX), a fast, scalable, deterministic symbolic regression algorithm to recover partial differential equations (PDEs). FFX identifies active bases among a huge set of candidate basis functions and their corresponding coefficients from recorded snapshot data. This approach uses a sparsity-promoting technique from compressive sensing and sparse optimization called pathwise regularized learning to perform feature selection and parameter estimation. Furthermore, it recovers several models of varying complexity (number of basis terms). FFX finally filters out many identified models using non-dominated sorting and forms a Pareto front consisting of optimal models with respect to minimizing complexity and test accuracy. Numerical experiments are carried out to recover several ubiquitous PDEs such as wave and heat equations among linear PDEs and Burgers, Korteweg–de Vries (KdV), and Kawahara equations among higher-order nonlinear PDEs. Additional simulations are conducted on the same PDEs under noisy conditions to test the robustness of the proposed approach.

42 ENGINEERING↗

NASA NTRS1983

Modeling of turbulent separated flows for aerodynamic applications

Steady, high speed, compressible separated flows modeled through numerical simulations resulting from solutions of the mass-averaged Navier-Stokes equations are reviewed. Emphasis is placed on benchmark flows that represent simplified (but realistic) aerodynamic phenomena. These include impinging shock waves, compression corners, glancing shock waves, trailing edge regions, and supersonic high angle of attack flows. A critical assessment of modeling capabilities is provided by comparing the numerical simulations with experiment. The importance of combining experiment, numerical algorithm, grid, and turbulence model to effectively develop this potentially powerful simulation technique is stressed.

Marvin, J. G.↗

NASA NTRS1986

Modeling of turbulent separated flows for aerodynamic applications

Marvin, J. G.↗