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Results for “Linear Optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The value of in-reservoir energy storage for flexible dispatch of geothermal power

Geothermal systems making use of advanced drilling and well stimulation techniques have the potential to provide tens to hundreds of gigawatts of clean electricity generation in the United States by 2050. With near-zero variable costs, geothermal plants have traditionally been envisioned as providing “baseload” power, generating at their maximum rated output at all times. However, as variable renewable energy sources (VREs) see greater deployment in energy markets, baseload power is becoming increasingly less competitive relative to flexible, dispatchable generation and energy storage. Herein we conduct an analysis of the potential for future geothermal plants to provide both of these services, taking advantage of the natural properties of confined, engineered geothermal reservoirs to store energy in the form of accumulated, pressurized geofluid and provide flexible load-following generation. We develop a linear optimization model based on multi-physics reservoir simulations that captures the transient pressure and flow behaviors within a confined, engineered geothermal reservoir. We then optimize the investment decisions and hourly operations of a power plant exploiting such a reservoir against a set of historical and modeled future electricity price series. Further, we find that operational flexibility and in-reservoir energy storage can significantly enhance the value of geothermal plants in markets with high VRE penetration, with energy value improvements of up to 60% relative to conventional baseload plants operating under identical conditions. Across a range of realistic subsurface and operational conditions, our modeling demonstrates that confined, engineered geothermal reservoirs can provide large and effectively free energy storage capacity, with round-trip storage efficiencies comparable to those of leading grid-scale energy storage technologies. Optimized operational strategies indicate that flexible geothermal plants can provide both short- and long-duration energy storage, prioritizing output during periods of high electricity prices. Sensitivity analysis assesses the variation in outcomes across a range of subsurface conditions and cost scenarios.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Capturing thin structures in VOF simulations with two-plane reconstruction

A novel interface reconstruction strategy for volume of fluid (VOF) methods is introduced that represents the liquid-gas interface as two planes that co-exist within a single computational cell. In comparison to the piecewise linear interface calculation (PLIC), this new algorithm greatly improves the accuracy of the reconstruction, in particular when dealing with thin structures such as films. The placement of the two planes requires the solution of a non-linear optimization problem in six dimensions, which has the potential to be overly expensive. Further, an efficient solution to this optimization problem is presented here that exploits two key ideas: an algorithm for extracting multiple plane orientations from transported surface data, and an efficient and mass-conserving distance-finding algorithm that accounts for two planes with arbitrary orientation. Additionally, a simple and robust strategy is presented to accurately represent the surface tension forces produced at the interface of subgrid-thickness films. The performance of this new VOF reconstruction is demonstrated on several test cases that illustrate the capability to handle arbitrarily thin films.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Methodology and performance comparison of statistical learning pulse shape classifiers as demonstrated with organic liquid scintillator [Performance comparison of statistical learning pulse shape classifiers]

In this study, we present novel methods for automated pulse shape discrimination. The classifiers are trained using simple radionuclide sources and do not require ground truth labeling. We test their performance using labels derived from time of flight experiments and present the results in terms of energy-dependent Receiver Operating Characteristic (ROC) curves. In addition, we also train and test standard pulse shape discrimination methods on the same data for comparison. We find multiple methods that can yield similar false neutron and true neutron rates at 24 keVee as tail-to-total or Gatti’s optimal linear filter yield at 54 keVee.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Longitudinal train dynamics model for a rail transit simulation system

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of the model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.

42 ENGINEERING↗
DOE OSTI2020

Emergence of superconductivity in doped multiorbital Hubbard chains

Abstract We introduce a variational state for one-dimensional two-orbital Hubbard models that intuitively explains the recent computational discovery of pairing in these systems when hole doped. Our ansatz is an optimized linear superposition of Affleck–Kennedy–Lieb–Tasaki valence-bond states, rendering the combination a valence-bond liquid dubbed orbital resonant valence bond. We show that the undoped (one-electron/orbital) quantum state of two sites coupled into a global spin singlet is exactly written employing only spin-1/2 singlets linking orbitals at nearest-neighbor sites. Generalizing to longer chains defines our variational state visualized geometrically expressing our chain as a two-leg ladder, with one orbital per leg. As in Anderson’s resonating valence-bond state, our undoped variational state contains preformed singlet pairs that via doping become mobile, leading to superconductivity. Doped real materials with one-dimensional substructures, two near-degenerate orbitals, and intermediate Hubbard U / W strengths— W the carrier’s bandwidth—could realize spin-singlet pairing if on-site anisotropies are small. If these anisotropies are robust, spin-triplet pairing emerges.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Improving photovoltaic hosting capacity of distribution networks with coordinated inverter control: A case study of the EPRI J1 feeder

Abstract Adding photovoltaic (PV) systems in distribution networks, while desirable for reducing the carbon footprint, can lead to voltage violations under high solar‐low load conditions. The inability of traditional volt‐VAr control in eliminating all the violations is also well‐known. This article presents a novel coordinated inverter control methodology that leverages system‐wide situational awareness to significantly improve hosting capacity (HC). The methodology employs a real‐time voltage‐reactive power (VQ) sensitivity matrix in an iterative linear optimizer to calculate the minimum reactive power intervention from PV inverters needed for mitigating over‐voltage without resorting to active power curtailing or requiring step voltage regulator setting changes. The algorithm is validated using the EPRI J1 feeder under an extensive set of realistic use cases and is shown to provide 3x improvement in HC under all scenarios.

Dalal, Dhaval [School of Electrical, Computer, and↗
DOE OSTI2015

Reference Correlation for the Viscosity of Ethane

A new representation of the viscosity for the fluid phase of ethane includes a zero-density correlation and a contribution for the critical enhancement, initially both developed separately, but based on experimental data. The higher-density contributions are correlated as a function of the reduced density δ = ρ/ρ{sub c} and of the reciprocal reduced temperature τ = T{sub c}/T (ρ{sub c}—critical density and T{sub c}—critical temperature). The final formulation contains 14 coefficients obtained using a state-of-the-art linear optimization algorithm. The evaluation and choice of the selected primary data sets is reviewed, in particular with respect to the assessment used in earlier viscosity correlations. The new viscosity surface correlation makes use of the reference equation of state for the thermodynamic properties of ethane by Bücker and Wagner [J. Phys. Chem. Ref. Data 35, 205 (2006)] and is valid in the fluid region from the melting line to temperatures of 675 K and pressures of 100 MPa. The viscosity in the limit of zero density is described with an expanded uncertainty of 0.5% (coverage factor k = 2) for temperatures 290 < T/K < 625, increasing to 1.0% at temperatures down to 212 K. The uncertainty of the correlated values is 1.5% in the range 290 < T/K < 430 at pressures up to 30 MPa on the basis of recent measurements judged to be very reliable as well as 4.0% and 6.0% in further regions. The uncertainty in the near-critical region (1.001 < 1/τ < 1.010 and 0.8 < δ < 1.2) increases with decreasing temperature up to 3.0% considering the available reliable data. Tables of the viscosity calculated from the correlation are listed in an appendix for the single-phase region, for the vapor–liquid phase boundary, and for the near-critical region.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Ghost fringe removal techniques using Lissajous data presentation

A VISAR (Velocity Interferometer System for Any Reflector) is a Dopplervelocity interferometer which is an important optical diagnostic in shockwave experiments at the national laboratories, used to measureequation of state(EOS) of materials under extreme conditions. Unwanted reflection of laser light from target windows can produce an additional component to the VISAR fringe record that can distort and obscure the true velocity signal. When accurately removing this so-called ghost artifact component is essential for achieving high accuracy EOSmeasurements, especially when the true light signal is only weakly reflected from the shock front. Independent of the choice of algorithm for processing the raw data into a complex fringe signal, we have found it beneficial to plot this signal as a Lissajous and seek the proper center of this path, even under time varying intensity which can shift the perceived center. Moreover, the ghost contribution is then solved by a simple translation in the complex plane that recenters the Lissajous path. For continuous velocity histories, we find that plotting the fringe magnitude vs nonfringing intensity and optimizing linearity is an invaluable tool for determining accurate ghost offsets. For discontinuous velocity histories, we have developed graphically inspired methods which relate the results of two VISARs having different velocity per fringe proportionalities or assumptions of constant fringe magnitude to find the ghost offset. The technique can also remove window reflection artifacts in generic interferometers, such as in the metrology of surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Accelerating and stabilizing the convergence of vibrational self-consistent field calculations via the direct inversion of the iterative subspace (vDIIS) algorithm

The vibrational self-consistent field (VSCF) method yields anharmonic states and spectra for molecular vibrations, and it serves as the starting point for more sophisticated correlated-vibration methods. Convergence of the iterative, non-linear optimization in VSCF calculations can be erratic or altogether unsuccessful, particularly for chemical systems involving low-frequency motions. In this work, a vibrational formulation of the Direct Inversion of the Iterative Subspace method of Pulay is presented and investigated. This formulation accounts for distinct attributes of the vibrational and electronic cases, including the expansion of each single-mode vibrational wavefunction in its own basis set. The resulting Direct Inversion of the Iterative Subspace method is shown to substantially accelerate VSCF convergence in all convergent cases as well as rectify many cases where Roothaan-based methods fail. Performance across systems ranging from small, rigid molecules to weakly bound molecular clusters is investigated in this analysis.

Chemistry↗
DOE OSTI2026

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering↗
DOE OSTI2013

Atmospheric retrieval analysis of the directly imaged exoplanet HR 8799b

Directly imaged exoplanets are unexplored laboratories for the application of the spectral and temperature retrieval method, where the chemistry and composition of their atmospheres are inferred from inverse modeling of the available data. As a pilot study, we focus on the extrasolar gas giant HR 8799b, for which more than 50 data points are available. We upgrade our non-linear optimal estimation retrieval method to include a phenomenological model of clouds that requires the cloud optical depth and monodisperse particle size to be specified. Previous studies have focused on forward models with assumed values of the exoplanetary properties; there is no consensus on the best-fit values of the radius, mass, surface gravity, and effective temperature of HR 8799b. We show that cloud-free models produce reasonable fits to the data if the atmosphere is of super-solar metallicity and non-solar elemental abundances. Intermediate cloudy models with moderate values of the cloud optical depth and micron-sized particles provide an equally reasonable fit to the data and require a lower mean molecular weight. We report our best-fit values for the radius, mass, surface gravity, and effective temperature of HR 8799b. The mean molecular weight is about 3.8, while the carbon-to-oxygen ratio is about unity due to the prevalence of carbon monoxide. Our study emphasizes the need for robust claims about the nature of an exoplanetary atmosphere to be based on analyses involving both photometry and spectroscopy and inferred from beyond a few photometric data points, such as are typically reported for hot Jupiters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Two-nucleon 𝑆-wave interactions at the SU(3) flavor-symmetric point with 𝑚 𝑢⁢𝑑 ≈ 𝑚$^{phys}_𝑠$: A first lattice QCD calculation with the stochastic Laplacian Heaviside method

We report on the first application of the stochastic Laplacian Heaviside method for computing multiparticle interactions with lattice QCD to the two-nucleon system. Like the Laplacian Heaviside method, this method allows for the construction of interpolating operators which can be used to construct a set of positive-definite two-nucleon correlation functions, unlike nearly all other applications of lattice QCD to two nucleons in the literature. It also allows for a variational analysis in which optimal linear combinations of the interpolating operators are formed that couple predominantly to the eigenstates of the system. Utilizing such methods has become of paramount importance to help resolve the discrepancy in the literature on whether two nucleons in either isospin channel form a bound state at pion masses heavier than physical, with the discrepancy persisting even in the SU(3)-flavor-symmetric point with all quark masses near the physical strange quark mass. This is the first in a series of papers aimed at resolving this discrepancy. In the present work, we employ the stochastic Laplacian Heaviside method without a hexaquark operator in the basis at a lattice spacing of 𝑎 ≈0.086 fm, lattice volume of 𝐿 = 48⁢𝑎 ≈ 4.1 fm and pion mass 𝑚 𝜋 ≈ 714 MeV. With this setup, the observed spectrum of two-nucleon energy levels strongly disfavors the presence of a bound state in either the deuteron or dineutron channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Foreground-immune CMB lensing reconstruction with polarization

Extragalactic foregrounds are known to generate significant biases in temperature based CMB lensing reconstruction. Several techniques, which include "source hardening'" and "shear-only estimators'' have been proposed to mitigate contamination and have been shown to be very effective at reducing foreground-induced biases. Here we extend both techniques to polarization, which will be an essential component of CMB lensing reconstruction for future experiments and investigate the "large lens'' limit analytically to gain insight on the origin and scaling of foreground biases, as well as the sensitivity to their profiles. Furthermore, using simulations of polarized point sources, we estimate the expected bias to both Simons Observatory and CMB-S4 like (polarization-based) lensing reconstruction, finding that biases to the former are minuscule while those to the latter are potentially non-negligible at small scales ($L$ ~ $1000-2000$). In particular, we show that for a CMB-S4 like experiment, an optimal linear combination of point-source hardened estimators can reduce the (point-source induced) bias to the CMB lensing power spectrum by up to two orders of magnitude, at a ~ 4% noise cost relative to the global minimum variance estimator.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Coordinated Control Method of Voltage and Reactive Power for Active Distribution Networks Based on Soft Open Point

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The conventional voltage regulation devices limited by the physical constraints are difficult to meet the requirement of real-time voltage and VAR control (VVC) with high precision when DGs fluctuate frequently. But, soft open point (SOP), a flexible power electronic device, can be used as the continuous reactive power source to realize the fast voltage regulation. Considering the cooperation of SOP and multiple regulation devices, this paper proposes a coordinated VVC method based on SOP for ADNs. Firstly, a time-series model of coordi-nated VVC is developed to minimize operation costs and eliminate voltage violations of ADNs. Then, by applying the linearization and conic relaxation, the original nonconvex mixed-integer non-linear optimization model is converted into a mixed-integer second-order cone programming (MISOCP) model which can be efficiently solved to meet the requirement of voltage regulation rapidity. Here, we carried out some case studies on the IEEE 33-node system and IEEE 123-node system to illustrate the effectiveness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

How state transitions balance photosynthetic electron transport in plants – a quantitative study

In plants, the process of state transition regulates the allocation of sunlight energy between Photosystem II (PSII) and PSI. However, the implications of state transitions for harmonizing electron transport rates between photosystems, and a full quantitative picture of this process, remain underexplored. We integrated quantitative biology (biochemical and biophysical approaches) with in vivo spectroscopy on wild-type Arabidopsis and protein phosphorylation mutants. This combination facilitated monitoring of Chl redistribution and its functional implications for light harvesting and electron transport. Our findings demonstrate the reallocation of 12% of highly phosphorylated ‘extra’ light-harvesting complex II under state 2 from stacked to unstacked thylakoids. This reduces the number of Chls per PSII from 216 to 182, while increasing the number in PSI from 187 to 223. Such Chl redistribution compensates for differences in photosystem stoichiometry and photochemical quantum efficiencies, thereby precisely synchronizing electron transport rates in both photosystems. Mutant analyses corroborate that this regulatory mechanism involves reversible phosphorylation. We inferred that state transitions optimize linear electron transport, leaving no additional capacity for cyclic electron transport. Furthermore, the results suggest that the controversies about long-range migration of LHCII from stacked to unstacked thylakoid domains arise from differences in phosphorylation levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Joint Non-Parametric Correction Estimator for Excess Relative Risk Regression in Survival Analysis with Exposure Measurement Error

Summary Observational epidemiological studies often confront the problem of estimating exposure–disease relationships when the exposure is not measured exactly. We investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a non-parametric correction estimator by using data from the subcohort and further propose a joint non-parametric correction estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of the joint non-parametric correction and non-parametric correction is further developed. The estimators proposed are non-parametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses.

Wang, Ching-Yun↗
DOE OSTI2019

Topology Reconfiguration and distributed Volt Var Control (TR-dVVC) v1

Topology Reconfiguation is a simple algorithm to choose a network configuration with the least losses in a system with high penetration of renewable energy. It uses a linearized optimal power flow algorithm to identify the optimal setpoints of PV in a system, then performs an exhaustive search of switch configurations to find the loss minimizing solution, it repeats this process until convergence. At the end, the operator has a switch schedule for a 24 hour period that should minimize losses. VVC is a distributed algorithm in which PV units drive voltage at points within the network to 1 per unit through reactive power control. The VVC algorithm relies on extremum seeking control to provide the control. The software package is a simulation of VVC on a standard IEEE 34 bus three phase network.

MacDonald, Jason↗