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At least 1,261 records · Page 70

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Distributed Solution Approach for a Stackelberg Pricing Game of Aggregated Demand Response

Demand-side management is a fundamental up-to-date strategy that transforms the traditional power grid to a modern smart grid where the flexible pricing mechanisms play a critical role in its successful implementation. In this paper, the pricing-demand response between a distribution system operator (DSO) and load aggregators (LAs) is modeled as a Stackelberg game, where the DSO is the price maker that adjusts its strategy based on observed responses from LAs. With the concerns of computational cost and privacy protection, two distributed solution approaches, particle swarm optimization and pattern search algorithm, are conducted and compared with the classical centralized backward induction approach. Numerical results on a small case study demonstrate the effectiveness of the proposed distributed solution approaches in leveraging flexible demand response potential.

Chen, Yang↗

DOE OSTI2017

The computer-based model of quantum measurements

Quantum theory of measurements is an extremely important part of quantum mechanics. Currently perturbations by quantum measurements of observable quantities of atomic systems are rarely taken into account in computing algorithms and calculations. In the previous studies of the authors, constructive model of quantum measurements has been developed and implemented in the form of symbolic and numerical calculations for the hydrogen-like atoms. This work describes a generalization of these results to the alkali metal atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Robust Containment Queries over Collections of Rational Parametric Curves via Generalized Winding Numbers

Point containment queries for regions bound by watertight geometric surfaces, i.e., closed and without self-intersections, can be evaluated straightforwardly with a number of well-studied algorithms. When this assumption on domain geometry is not met, such methods are either unusable, or prone to misclassifications that can lead to cascading errors in downstream applications. More robust point classification schemes based on generalized winding numbers have been proposed, as they are indifferent to these imperfections. However, existing algorithms are limited to point clouds and collections of linear elements. We extend this methodology to encompass more general curved shapes with an algorithm that evaluates the winding number scalar field over unstructured collections of rational parametric curves. In particular, we evaluate the winding number for each curve independently, making the derived containment query robust to how the curves are arranged. We ensure geometric fidelity in our queries by treating each curve as equivalent to an adaptively constructed polyline that provably has the same generalized winding number at the point of interest. Our algorithm is numerically stable for points that are arbitrarily close to the model, and explicitly treats points that are coincident with curves. We demonstrate the improvements in computational performance granted by this method over conventional techniques as well as the robustness induced by its application.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Qualitative Analysis, Structure-Preserving Discretizations and Scalable Solvers for Multiphysics Problems. Final Technical Report

Many problems in physics, engineering, meteorology, computer science, and other fields involve a certain level of coupling between different physical quantities. With the development of advanced computational modeling, simulation, and hardware, simulations for many important multiphysics/multiscale coupling effects are now more tractable. In this project, we have developed robust, efficient, and practical numerical algorithms for such simulation software that are capable of tackling these complex mathematical models in many fundamental ways such as stability, wellposedness, and consistency. We expect that such an integrated theoretical and algorithmic framework will have a substantial impact on numerous multiscale and multiphysics modeling and simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Bilevel Parameter Optimization for Nonlocal Image Denoising Models

We propose a bilevel optimization approach for the determination of parameters in nonlocal image denoising. We consider both spatial weights in front of the fidelity term, as well as weights within the kernel of the nonlocal operator. In both cases we investigate the differentiability of the solution operator in function spaces and derive a first order optimality system that characterizes local minima. For the numerical solution of the problems, we propose a second-order optimization algorithm in combination with a finite element discretization of the nonlocal denoising models and a computational strategy for the solution of the resulting dense linear systems. Several experiments are run in order to show the suitability of our approach.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1972

An estimation algorithm with learning feature for an adaptive bit synchronizer.

Description of an on-line optimal (in the sense of linear minimum mean square error) sequential bit synchronizer assuming minimal a priori knowledge of the incoming data. The adaptive synchronization algorithms, implemented on a small computer, are capable of accurately estimating pulse transition time, pulse amplitude, and pulse width by invoking the powerful Gauss-Markov theorem. Numerous simulations indicate that the performance of the synchronizer is satisfactory from the point of view of the amount of data required and the speed of convergence.

Chow, L. R.↗

NASA NTRS1975

Special Perturbations Using Back-Correction Methods of Numerical Integration

A new class of linear multistep methods for numerical integration of differential equations is reported that permits satellite computation solutions to be corrected at certain points in the past as the integration advances in time. Algorithms have been developed for the solution of both first- and second-order differential equations. The back correction method appears to be more efficient than classical methods when dominant and perturbing forces can be separated.

Feagin, T.↗

NASA NTRS1983

A computational investigation of supersonic axisymmetric flow over boattails containing a centered propulsive jet

The influence of underexpanded jets on a supersonic afterbody flow field is investigated using computational techniques. The thin-shear-layer formulation of the compressible, Reynolds-averaged Navier-Stokes equations is solved using a time-dependent, implicit numerical algorithm. Solutions are obtained for supersonic flow over an axisymmetric conical afterbody containing a centered propulsive jet where the free-stream Mach number is 2.0 and the jet exit Mach number is 2.5. Exhaust-jet static pressures are considered in the range of 2 to 9 times the free-stream static pressure and with nozzle-exit half-angles from 15 deg to 43 deg. Comparisons are made with experimental results for base pressure, separation distance, afterbody pressure distribution, anf flow-field structure. Although good quantitative agreement with experimental separation distance and base pressure level is not observed, the parametric trends induced by exhaust-jet pressure level and nozzle-exit angle are well predicted, as are the flow-field details in the vicinity of the afterbody and in the exhaust plume.

Deiwert, G. S.↗

NASA NTRS1986

Concurrent processing in nonlinear structural stability

A concurrent processing algorithm is developed for materially nonlinear stability analysis of imperfect columns with biaxial partial rotational end restraints. The algorithm for solving the governing nonlinear ordinary differential equations is implemented on a multiprocessor computer called the 'Finite Element Machine', developed at the NASA Langley Research Center. Numerical results are obtained on up to nine concurrent processors. A substantial computational gain is achieved in using the parallel processing approach.

Darbhamulla, S. P.↗

NASA NTRS1996

The Development of Computational Techniques for the Nonlinear Analysis of Composite Structures at High Temperature

The objective of this research project was to develop robust and efficient computational tools for deformation and life analysis techniques. This included: development of viscoplastic continuum models, associated numerical integration techniques, suitable micromechanics models/methods, and coupled deformation and damage algorithms. The work was involved with models/methods applicable to composite structures on both microscale and macroscale levels. The microscale analysis utilized Aboudi's generalized method of cells (GMS) micromechanical model as well as finite element models of similar composite architectures, i.e., square and hexagonal fiber pack models.

Keith, Theo G., Jr.↗

NASA NTRS1998

Performance Analysis and Portability of the PLUM Load Balancing System

The ability to dynamically adapt an unstructured mesh is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult. To address this problem, we have developed PLUM, an automatic portable framework for performing adaptive numerical computations in a message-passing environment. PLUM requires that all data be globally redistributed after each mesh adaption to achieve load balance. We present an algorithm for minimizing this remapping overhead by guaranteeing an optimal processor reassignment. We also show that the data redistribution cost can be significantly reduced by applying our heuristic processor reassignment algorithm to the default mapping of the parallel partitioner. Portability is examined by comparing performance on a SP2, an Origin2000, and a T3E. Results show that PLUM can be successfully ported to different platforms without any code modifications.

Oliker, Leonid↗

DOE OSTI2021

Apprentice for Event Generator Tuning

Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

An in-line burn-up algorithm: proposal and preliminary analysis

A new burn-up algorithm is proposed for coupling neutronics and isotopic depletion. The algorithm is analogous to those proposed for enforcing xenon equilibrium and converging neutronics and thermal-hydraulics. During the corrector step of standard predictor-corrector methods, the corrector nuclide density is updated as neutronics converges. This is expected to improve stability while reducing computational expense compared to other implicit algorithms. The stability of the algorithm is investigated by Fourier analysis for a simple case whose results have been successfully compared with numerical experiments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians

In this study, we consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We assume for the objective that its evaluation, gradient, and Hessian are inaccessible, while one can compute their stochastic estimates by, for example, subsampling. We propose a stochastic algorithm based on sequential quadratic programming (SQP) that uses a differentiable exact augmented Lagrangian as the merit function. To motivate our algorithm design, we first revisit and simplify an old SQP method Lucidi developed for solving deterministic problems, which serves as the skeleton of our stochastic algorithm. Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified. Finally, we incorporate a recent stochastic line search procedure Paquette and Scheinberg into the non-adaptive stochastic SQP to adaptively select the random stepsizes, which leads to an adaptive stochastic SQP. The global "almost sure" convergence for both non-adaptive and adaptive SQP methods is established. Numerical experiments on nonlinear problems in CUTEst test set demonstrate the superiority of the adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Infinite quantum signal processing

Quantum signal processing (QSP) represents a real scalar polynomial of degree d using a product of unitary matrices of size 2 × 2 , parameterized by ( d + 1 ) real numbers called the phase factors. This innovative representation of polynomials has a wide range of applications in quantum computation. When the polynomial of interest is obtained by truncating an infinite polynomial series, a natural question is whether the phase factors have a well defined limit as the degree d → ∞ . While the phase factors are generally not unique, we find that there exists a consistent choice of parameterization so that the limit is well defined in the ℓ 1 space. This generalization of QSP, called the infinite quantum signal processing, can be used to represent a large class of non-polynomial functions. Our analysis reveals a surprising connection between the regularity of the target function and the decay properties of the phase factors. Our analysis also inspires a very simple and efficient algorithm to approximately compute the phase factors in the ℓ 1 space. The algorithm uses only double precision arithmetic operations, and provably converges when the ℓ 1 norm of the Chebyshev coefficients of the target function is upper bounded by a constant that is independent of d . This is also the first numerically stable algorithm for finding phase factors with provable performance guarantees in the limit d → ∞ .

Dong, Yulong [Department of Mathematics, Universit↗

DOE OSTI2025

A simple introduction to the SiMPL method for density-based topology optimization

We introduce a novel method for solving density-based topology optimization problems: Sigmoidal Mirror descent with a Projected Latent variable (SiMPL). The SiMPL method (pronounced as “the simple method”) optimizes a design using only first-order derivative information of the objective function. The bound constraints on the density field are enforced with the help of the (negative) Fermi–Dirac entropy, which is also used to define a non-symmetric distance function called a Bregman divergence on the set of admissible designs. This Bregman divergence leads to a simple update rule that is further simplified with the help of a so-called latent variable. Because the SiMPL method involves discretizing the latent variable, it produces a sequence of pointwise-feasible iterates, even when high-order finite elements are used in the discretization. Numerical experiments demonstrate that the method outperforms other popular first-order optimization algorithms. In conclusion, to outline the general applicability of the technique, we include examples with (self-load) compliance minimization and compliant mechanism optimization problems.

Calculus of Variations and Optimization↗

DOE OSTI2020

High order explicit local time stepping methods for hyperbolic conservation laws

In this paper we present and analyze a general framework for constructing high order explicit local time stepping (LTS) methods for hyperbolic conservation laws. In particular, we consider the model problem discretized by Runge-Kutta discontinuous Galerkin (RK-DG) methods and design LTS algorithms based on the strong stability preserving Runge-Kutta (SSP-RK) schemes, that allow spatially variable time step sizes to be used for time integration in different regions of the computational domain. The proposed algorithms are of predictor-corrector type, in which the interface information along the time direction is first predicted based on the SSP-RK approximations and Taylor expansions, and then the fluxes over the region of the interface are corrected to conserve mass exactly at each time step. Following the proposed framework, we detail the corresponding LTS schemes with accuracy up to the fourth order, and prove their conservation property and nonlinear stability for the scalar conservation laws. Numerical experiments are also presented to demonstrate excellent performance of the proposed LTS algorithms.

58 GEOSCIENCES↗

NASA NTRS1995

Computational analysis of forebody tangential slot blowing on the high alpha research vehicle

A numerical analysis of forebody tangential slot blowing as a means of generating side force and yawing moment is conducted using an aircraft geometry. The Reynolds-averaged, thin-layer, Navier-Stokes equations are solved using a partially flux-split, approximately-factored algorithm. An algebraic turbulence model is used to determine the turbulent eddy viscosity values. Solutions are obtained using both patched and overset grid systems. In the patched grid model, and actuator plane is used to introduce jet variables into the flow field. The overset grid model is used to model the physical slot geometry and facilitate modeling of the full aircraft configuration. A slot optimization study indicates that a short slot located close to the nose of the aircraft provided the most side force and yawing moment per unit blowing coefficient. Comparison of computed surface pressure with that obtained in full-scale wind tunnel tests produce good agreement, indicating the numerical method and grid system used in the study are valid. Full aircraft computations resolve the changes in vortex burst point due to blowing. A time-accurate full-aircraft solution shows the effect of blowing on the changes in the frequency of the aerodynamic loads over the vertical tails. A study of the effects of freestream Mach number and various jet parameters indicates blowing remains effective through the transonic Mach range. An investigation of the force onset time lag associated with forebody blowing shows the lag to be minimal. The knowledge obtained in this study may be applied to the design of a forebody tangential slot blowing system for use on flight aircraft.

Gee, Ken↗