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At least 847 records · Page 47

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DOE OSTI2025

Domain Decomposition for Integer Optimal Control with Total Variation Regularization

Total variation integer optimal control problems admit solutions and necessary optimality conditions via geometric variational analysis. In spite of the existence of said solutions, algorithms which solve the discretized objective suffer from high numerical cost associated with the combinatorial nature of integer programming. Hence, such methods are often limited to small and medium-sized problems. We propose a globally convergent, coordinate descent–inspired algorithm that allows tractable subproblem solutions restricted to a partition of the domain. Our decomposition method solves relatively small trust-region subproblems that modify the control variable on a subdomain only. Given nontrivial subdomain overlap, we prove that a global first-order necessary optimality condition is equivalent to a first-order necessary optimality condition per subdomain. We additionally show that a sufficient decrease is achieved on a single subdomain by way of a trust-region subproblem solver using geometric measure–theoretic arguments, which we integrate with a greedy patch selection to prove convergence of our algorithm. In conclusion, we demonstrate the practicality of our algorithm on a benchmark large-scale, PDE-constrained integer optimal control problem and find that our method is faster than the state of the art.

domain decomposition↗

DOE OSTI2016

Pitch-angle scattering of energetic charged particles in nearly constant magnitude magnetic turbulence

We use a method developed by Roberts that optimizes the phase angles of an ensemble of plane waves with amplitudes determined from a Kolmogorov-like power spectrum, to construct magnetic field vector fluctuations having nearly constant magnitude and large variances in its components. This is a representation of the turbulent magnetic field consistent with that observed in the solar wind. Charged-particle pitch-angle diffusion coefficients are determined by integrating the equations of motion for a large number of charged particles moving under the influence of forces from our predefined magnetic field. We tested different cases by varying the kinetic energy of the particles (E {sub p}) and the turbulent magnetic field variance (σ{sub B}{sup 2}). For each combination of E {sub p} and σ{sub B}{sup 2}, we tested three different models: (1) the so-called “slab” model, where the turbulent magnetic field depends on only one spatial coordinate and has significant fluctuations in its magnitude (b=√(δB{sub x}{sup 2}(z)+δB{sub y}{sup 2}(z)+B{sub 0}{sup 2})); (2) the slab model optimized with nearly constant magnitude b; and (3) the slab model turbulent magnetic field with nearly constant magnitude plus a “variance-conserving” adjustment. In the last case, this model attempts to conserve the variance of the turbulent components (σ{sub Bx}{sup 2}+σ{sub By}{sup 2}), which is found to decrease during the optimization with nearly constant magnitude. We found that there is little or no effect on the pitch-angle diffusion coefficient D{sub μμ} between models 1 and 2. However, the result from model 3 is significantly different. We also introduce a new method to accurately determine the pitch-angle diffusion coefficients as a function of μ.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Using a pruned, nondirect product basis in conjunction with the multi-configuration time-dependent Hartree (MCTDH) method

In this paper, we propose a pruned, nondirect product multi-configuration time dependent Hartree (MCTDH) method for solving the Schrödinger equation. MCTDH uses optimized 1D basis functions, called single particle functions, but the size of the standard direct product MCTDH basis scales exponentially with D, the number of coordinates. We compare the pruned approach to standard MCTDH calculations for basis sizes small enough that the latter are possible and demonstrate that pruning the basis reduces the CPU cost of computing vibrational energy levels of acetonitrile (D = 12) by more than two orders of magnitude. Using the pruned method, it is possible to do calculations with larger bases, for which the cost of standard MCTDH calculations is prohibitive. Pruning the basis complicates the evaluation of matrix-vector products. In this paper, they are done term by term for a sum-of-products Hamiltonian. When no attempt is made to exploit the fact that matrices representing some of the factors of a term are identity matrices, one needs only to carefully constrain indices. In this paper, we develop new ideas that make it possible to further reduce the CPU time by exploiting identity matrices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Effects of pressure on the structure and lattice dynamics of ammonium perchlorate: A combined experimental and theoretical study

Abstract not provided

Kroonblawd, Matthew P.↗

DOE OSTI2022

Metaplectic geometrical optics for ray-based modeling of caustics: Theory and algorithms

The optimization of radio frequency-wave (RF) systems for fusion experiments is often performed using ray-tracing codes, which rely on the geometrical-optics (GO) approximation. However, GO fails at caustics such as cutoffs and focal points, erroneously predicting the wave intensity to be infinite. This is a critical shortcoming of GO, since the caustic wave intensity is often the quantity of interest, e.g., RF heating. Full-wave modeling can be used instead, but the computational cost limits the speed at which such optimizations can be performed. Here, we have developed a less expensive alternative called metaplectic geometrical optics (MGO). Instead of evolving waves in the usual x (coordinate) or k (spectral) representation, MGO uses a mixed X$\equiv$Ax+Bk representation. By continuously adjusting the matrix coefficients A and B along the rays, one can ensure that GO remains valid in the X coordinates without caustic singularities. The caustic-free result is then mapped back onto the original x space using metaplectic transforms. Here, we overview the MGO theory and review algorithms that will aid the development of an MGO-based ray-tracing code. We show how using orthosymplectic transformations leads to considerable simplifications compared to previously published MGO formulas. We also prove explicitly that MGO exactly reproduces standard GO when evaluated far from caustics (an important property that until now has only been inferred from numerical simulations), and we relate MGO to other semiclassical caustic-removal schemes published in the literature. Finally this discussion is then augmented by an explicit comparison of the computed spectrum for a wave bounded between two cutoffs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Synchronized Phasor Measurement Unit-based Central Controller for Normal and Contingent Operation of a High-Capacity HVDC Macrogrid for the Continental US

This paper presents a Synchronized Phasor Measurement Unit (PMU) based controller to support the coordination and operation of a high-capacity high-voltage direct current (HVDC) macrogrid transmission for the continental US. The proposed controller allows for optimal scheduling of each segment of the multi-terminal HVDC network under normal and contingent conditions, while considering minimum levels of frequency response requirements. The performance of the proposed controller is tested on a 100,222-bus representation of the US Eastern and Western interconnections. Results show that a centralized PMU-based controller improves the frequency nadir of the HVDC macrogrid under contingency conditions by 25.9%. Furthermore, the primary frequency response (PFR) of the HVDC macrogrid is increased by 33.4%. The performance of each interconnection under the largest credible contingency conditions is also discussed.

Mohan, Nihal↗

DOE OSTI2019

Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration With Repair Crew and Mobile Power Source Dispatch

Repair crews (RCs) and mobile power sources (MPSs) are critical resources for distribution system (DS) outage management after a natural disaster. However, their logistics have not been well investigated. We propose a resilient scheme for disaster recovery logistics to co-optimize DS restoration with the dispatch of RCs and MPSs. A novel co-optimization model is formulated to route RCs and MPSs in the transportation network, schedule them in the DS, and reconfigure the DS for microgrid formation coordinately, etc. The model incorporates different timescales of DS restoration and RC/MPS dispatch, the coupling of transportation and power networks, etc. To ensure radiality of the DS with variable physical structure and MPS allocation, we also model topology constraints based on the concept of spanning forest. The model is convexified equivalently and linearized into a mixed-integer linear programming. To reduce its computation time, preprocessing methods are proposed to preassign a minimal set of repair tasks to depots and reduce the number of candidate nodes for MPS connection. Resilient recovery strategies thus are generated to enhance service restoration, especially by dynamic formation of microgrids that are powered by MPSs and topologized by repair actions of RCs and network reconfiguration of the DS. Case studies demonstrate the proposed methodology.

Disaster recovery logistics↗

DOE OSTI2018

pnnl/sven

This is a JavaScript library for a storyline layout algorithm. Storylines are adept at communicating complex change by encoding time on the x-axis and using the proximity of lines in the y direction to represent interaction between entities. The library in this disclosure takes as input a list of objects containing an id, time, and state. The output is a data structure that can be used to conveniently render a storyline visualization. Most importantly, the library computes the y-coordinate of the entities over time that decreases layout artifacts including crossings, wiggles, and whitespace. This is accomplished through multi-objective, multi-stage optimization problem, where the output of one stage produces input and constraints for the next stage.

Arendt, Dustin↗

DOE OSTI2016

Land-Atmosphere Feedback Experiment (LAFE) Science Plan

The Land-Atmosphere Feedback Experiment (LAFE; pronounced “la-fey”) deploys several state-of-the-art scanning lidar and remote sensing systems to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. These instruments will augment the ARM instrument suite in order to collect a data set for studying feedback processes between the land surface and the atmosphere. The novel synergy of remote-sensing systems will be applied for simultaneous measurements of land-surface fluxes and horizontal and vertical transport processes in the atmospheric convective boundary layer (CBL). The impact of spatial inhomogeneities of the soil-vegetation continuum on land-surface-atmosphere (LSA) feedback will be studied using the scanning capability of the instrumentation. The time period of the observations is August 2017, because large differences in surface fluxes between different fields and bare soil can be observed, e.g., pastures versus fields where the wheat has already been harvested. The remote sensing system synergy will consist of three components: 1) The SGP water vapor and temperature Raman lidar (SRL), the SGP Doppler lidar (SDL), and the National Center for Atmospheric Research (NCAR) water vapor differential absorption lidar (DIAL) (NDIAL) mainly in vertical staring modes to measure mean profiles and gradients of moisture, temperature, and horizontal wind. They will also measure profiles of higher-order turbulent moments in the water vapor and wind fields and profiles of the latent heat flux. 2) A novel scanning lidar system synergy consisting of the National Oceanic and Atmospheric Administration (NOAA) High-Resolution Doppler lidar (HRDL), the University of Hohenheim (UHOH) water-vapor differential absorption lidar (UDIAL), and the UHOH temperature Raman lidar (URL). These systems will perform coordinated range-height indicator (RHI) scans from just above the canopy level to the lower troposphere, including the interfacial layer of the CBL. The optimal azimuth is to the ENE of the SGP central facility, which takes advantage of both changes in the surface elevation and different crop types planted along that path. 3) The University of Wisconsin Space Science and Engineering Center Portable Atmospheric Research Center (SPARC) and the University of Oklahoma Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS) operating two vertically pointing atmospheric emitted radiance interferometers (AERIs) and two Doppler lidar (DL) systems scanning cross track to the central RHI for determining the surface friction velocity and the horizontal variability of temperature, moisture, and wind. Thus, both the variability of surface fluxes and CBL dynamics and thermodynamics over the SGP site will be studied for the first time. The combination of these three components will enable us to estimate both the divergence of the latent heat profile and the advection of moisture. Thus, the moisture budget in the SGP domain can be studied. Furthermore, the simultaneous measurements of surface and entrainment fluxes as well as the daily cycle of the CBL thermodynamic state will provide a unique data set for characterizing LSA interaction in dependence of large-scale and local conditions such as soil moisture and the state of the vegetation. The measurements will also be applied for the development of improved parameterizations of surface fluxes and turbulence in the CBL. The latter is possible because mean profiles, gradients, higher-order moments, and fluxes are measured simultaneously. The results will be used for the verification of simulations of LSA feedback in large-eddy simulation (LES) and mesoscale models, which are planned for the SGP site. Due to the strong connection between the pre-convective state of the CBL and the formation of clouds and precipitation, this new generation of experiments will strongly contribute to the improvement of their representation in weather, climate, and earth system models.

Southern Great Plains, atmospheric boundary layer,↗

DOE OSTI2021

Mass Property Calculator

A mass property calculator has been developed to compute the moment of inertia properties of an assemblage of parts that make up a system. The calculator can take input from spreadsheets or Creo mass property files or it can be interfaced with Phoenix Integration Model Center. The input must include the centroidal moments of inertia of each part with respect to its local coordinates, the location of the centroid of each part in the system coordinates and the Euler angles needed to rotate from the part coordinates to the system coordinates. The output includes the system total mass, centroid and mass moment of inertia properties. The input/output capabilities allow the calculator to interface with external optimizers. In addition to describing the calculator, this document serves as its user's manual. The up-to-date version of the calculator can be found in the Git repository https://cee-gitlab.sandia.gov/cj?ete/mass-properties-calculator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Modelling the Liquid Waste Operation at the Savannah River Site

Modeling Successes Dounreay – Site Closure Optimization and Risk Reduction Re-structuring and streamlining a complex project plan to achieve site decommissioning in reduced time and at reduced cost, through automated task prioritization. Idaho AMWTP – Multi-stream Optimization Speeding up a complex facility with many process lines, by utilizing all of the process lines more efficiently and reducing overall plant downtime, by coordinating repairs and shutdowns. AWE –Waste Repackaging and Relocation Relocating schedule for waste material from an old storage facility to a new purpose-built one, safely, and in a timely fashion that removed the need to reassure the safety of the old facility. Sellafield – Effluent, Sludge and HAW Treatment Improving a wide range of chemical engineered processes including aqueous effluent treatment, chemically-reactive sludge management and waste vitrification processing. Strategic Petroleum Reserve – Cavern Management Linking chemistry models of petroleum prediction, through engineering cavern management to financial modeling of gasoline sales to benefit US government

Jung, Andrew W.↗

NASA NTRS1983

Interception in three dimensions - An energy formulation

The problem of minimum-time interception of a target flying in three dimensional space is analyzed with the interceptor aircraft modeled through energy-state approximation. A coordinate transformation that uncouples the interceptor's extremals from the target motion in an open-loop sense is introduced, and the necessary conditions for optimality and the optimal controls are derived. Example extremals are shown.

Rajan, N.↗

NASA NTRS1985

Generative engineering databases - Toward expert systems

Engineering data management, incorporating concepts of optimization with data representation, is receiving increasing attention as the amount and complexity of information necessary for performing engineering operations increases and the need to coordinate its representation and use increases. Research in this area promises advantages for a wide variety of engineering applications, particularly those which seek to use data in innovative ways in the engineering process. This paper presents a framework for a comprehensive, relational database management system that combines a knowledge base of design constraints with a database of engineering data items in order to achieve a 'generative database' - one which automatically generates new engineering design data according to the design constraints stored in the knowledge base. The representation requires a database that is able to store all of the data normally associated with engineering design and to accurately represent the interactions between constraints and the stored data while guaranteeing its integrity. The representation also requires a knowledge base that is able to store all the constraints imposed upon the engineering design process.

Rasdorf, W. J.↗

NASA NTRS1990

Preconditioned upwind methods to solve 3-D incompressible Navier-Stokes equations for viscous flows

A computational method for calculating low-speed viscous flowfields is developed. The method uses the implicit upwind-relaxation finite-difference algorithm with a nonsingular eigensystem to solve the preconditioned, three-dimensional, incompressible Navier-Stokes equations in curvilinear coordinates. The technique of local time stepping is incorporated to accelerate the rate of convergence to a steady-state solution. An extensive study of optimizing the preconditioned system is carried out for two viscous flow problems. Computed results are compared with analytical solutions and experimental data.

Hsu, C.-H.↗

NASA NTRS1995

A comparison of design variables for control theory based airfoil optimization

This paper describes the implementation of optimization techniques based on control theory for airfoil design. In our previous work in the area it was shown that control theory could be employed to devise effective optimization procedures for two-dimensional profiles by using either the potential flow or the Euler equations with either a conformal mapping or a general coordinate system. We have also explored three-dimensional extensions of these formulations recently. The goal of our present work is to demonstrate the versatility of the control theory approach by designing airfoils using both Hicks-Henne functions and B-spline control points as design variables. The research also demonstrates that the parameterization of the design space is an open question in aerodynamic design.

Reuther, James↗

DOE OSTI2017

Pure JavaScript Storyline Layout Algorithm

Source record↗

DOE OSTI2023

Supramolecular Assembly of One-Dimensional Coordination Polymers for Efficient Separation of Xenon and Krypton

Efficient separation and purification of xenon (Xe) from krypton (Kr) represent an industrially crucial but challenging process. While the adsorption-based separation of these atomic gases represents an energy-efficient process, achieving highly selective adsorbents remains a difficult task. Here, we demonstrate a supramolecular assembly of coordination polymers, termed as M(II)-dhbq (M = Mg, Mn, Co, and Zn; dhbq = 2,5-dihydroxy-1,4-benzoquinone), with high-density open metal sites (5.3 nm –3 ) and optimal pore size (5.5 Å), which are able to selectively capture Xe among other chemically inert gases including Kr, Ar, N 2 , and O 2 . Among M(II)-dhbq materials, Mn-dhbq exhibits the highest Xe uptake capacity of 3.1 mmol/g and a Xe/Kr selectivity of 11.2 at 298 K and 1.0 bar, outperforming many state-of-the-art adsorbents reported so far. Remarkably, the adsorption selectivity of Mn-dhbq for Xe/O 2 , Xe/N 2 , and Xe/Ar at ambient conditions reaches as high as 70.0, 139.3, and 64.0, respectively. Direct breakthrough experiments further confirm that all M(II)-dhbq materials can efficiently discriminate Xe atoms from other inert gases. Furthermore, it is revealed from the density functional theory calculations that the strong affinity between Xe and the coordination polymer is mainly attributed to the polarization by open metal sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

For heavy-duty diesel engines, NO X emissions reduction is strongly constrained by fuel efficiency. This paper presents a hierarchical model predictive controller (H-MPC) for coordinated control of tailpipe NO X emissions and fuel consumption. The H-MPC uses the separation of slow and fast dynamics that exist in the engine and its aftertreatment system. The controller is synthesized with an architecture in which a high-level MPC uses a longer prediction horizon compared to the low-level predictive controller which tracks the high-level controller command and manages the thermal dynamics of the aftertreatment system. Engine load preview enables the high-level controller to estimate the desired catalyst temperature ahead of time and addresses the selective catalytic reduction (SCR) slow thermal dynamics. Calculated by the high-level controller, the intake manifold pressure, and the start of injection (SOI) crank angle is used as reference trajectories in the low-level controller that regulates fast dynamical behaviors such as engine out NO X emissions. Hardware-in-the-loop (HIL) validation of this integrated H-MPC on a rapid prototype controller shows that when the SCR catalyst temperature is above light-off temperature (warmed-up condition), the engine operation is shifted to operate with the best fuel economy since the warmed-up SCR can efficiently reduce the engine-out NO X emissions. Results indicate that up to 0.8% benefit in cycle averaged BSFC along with a 13% reduction in tailpipe NO X compared to a stock engine calibration can be achieved with the coordinated engine and aftertreatment system through H-MPC.

Engineering↗