State Estimation Model Reduction Through the Manifold Boundary Approximation Method
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Engineering↗
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Results for “Approximation methods”
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slimTrain---A Stochastic Approximation Method for Training Separable Deep Neural Networks
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Mathematics↗
Characterizing Approximation Methods for Digital Twins in Scientific Computing.
Abstract not provided.
Morrow, Zachary↗
Optimization models for integrated biorefinery operations
Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.
09 BIOMASS FUELS↗
Stochastic approximation methods-Powerful tools for simulation and optimization: A survey of some recent work on multi-agent systems and cyber-physical systems
Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Assessment of approximate computational methods for conical intersections and branching plane vectors in organic molecules
Quantum-chemical computational methods are benchmarked for their ability to describe conical intersections in a series of organic molecules and models of biological chromophores. Reference results for the geometries, relative energies, and branching planes of conical intersections are obtained using ab initio multireference configuration interaction with single and double excitations (MRCISD). They are compared with the results from more approximate methods, namely, the state-interaction state-averaged restricted ensemble-referenced Kohn-Sham method, spin-flip time-dependent density functional theory, and a semiempirical MRCISD approach using an orthogonalization-corrected model. It is demonstrated that these approximate methods reproduce the ab initio reference data very well, with root-mean-square deviations in the optimized geometries of the order of 0.1 Å or less and with reasonable agreement in the computed relative energies. A detailed analysis of the branching plane vectors shows that all currently applied methods yield similar nuclear displacements for escaping the strong non-adiabatic coupling region near the conical intersections. Our comparisons support the use of the tested quantum-chemical methods for modeling the photochemistry of large organic and biological systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Lyapunov and Sacker–Sell spectral stability theory for one-step methods
Approximation theory for Lyapunov and Sacker–Sell spectra based upon QR techniques is used to analyze the stability of a one-step method solving a time-dependent (nonautonomous) linear ordinary differential equation (ODE) initial value problem in terms of the local error. Integral separation is used to characterize the conditioning of stability spectra calculations. The stability of the numerical solution by a one-step method of a nonautonomous linear ODE using real-valued, scalar, nonautonomous linear test equations is justified. This analysis is used to approximate exponential growth/decay rates on finite and infinite time intervals and establish global error bounds for one-step methods approximating uniformly, exponentially stable trajectories of nonautonomous and nonlinear ODEs. A time-dependent stiffness indicator and a one-step method that switches between explicit and implicit Runge–Kutta methods based upon time-dependent stiffness are developed based upon the theoretical results.
97 MATHEMATICS AND COMPUTING↗
Core Combination Method of Approximation (CCMA) for Neutron Fluence Calculation
Neutron fluence, or accumulative neutron fluence rate, is a key parameter of the neutron irradiation resistance of materials (Wagner, Bergner et al. 2016). So we must try to obtain it during irradiation experiments. Neutron fluence is defined as the time integral of neutron fluence rate. To get the quantity, or to do this integral, we need to know how neutron fluence rate varied with time. The integral might not be difficult when we conduct a material irradiation experiment, because we can put certain kind of neutron detectors in the location of species, to measure neutron fluence rate (Tanaka, Endo et al. 2011). At this circumstance, the reactor power is usually maintained to be constant (Ferroukhi, Hollard et al. 2009; Dupre, Vasiliev et al. 2015). So the neutron fluence is equal to the product of neutron fluence rate and irradiation time. However, it's not the same case when we want to get the neutron fluence of structure materials used in the SPRR- 300 (Swimming Pool Research Reactor -300). This reactor is a light-water-moderated, enriched-uranium-fueled research reactor developed by China. Structural materials, such as graphite, are of great value for research (Asamoah, Gyampo et al. 2012). Graphite was used as reflector in reactor. It is a waste of material and a waste of money to dismantle it simply. However, to reuse post-irradiation graphite assemblies faces some challenges, such as neutron fluence calculation, radiation protection, etc. The former will be discussed in this paper, whereas the latter will remain to be studied for the following time. The problem is how to acquire neutron fluence distribution in structure materials, since specific measurement of neutron fluence rate were not conducted intentionally during historical reactor operation. So we need to figure it out by a method of calculation. Considering a large number of reactor refueling, we propose an approximate method, Core Combination Method of Approximation (CCMA), to calculate accumulative neutron fluence rate of key structure materials during a long period of irradiation time.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Comparing Capacity Credit Calculations for Wind: A Case Study in Texas
The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.
17 WIND ENERGY↗
A stochastic biomass blending problem in decentralized supply chains
Blending biomass materials of different physical or chemical properties provides an opportunity to adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the thermochemical conversion process at the mini-mum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass quality. The proposed CCP model ensures that process requirements, which are impacted by physical and chemical properties of biomass, are met most of the time. We consider two problem settings, a centralized and a decentralized supply chain. We propose a mixed-integer linear program to model the blending problem in the centralized setting and a bilevel program to model the blending problem in the decentralized setting. We use the sample average approximation method to approximate the chance constraints, and propose solution algorithms to solve this approximation. We develop a case study for South Carolina using data provided by the Billion Ton Study. Based on our results, the blends identified consist mainly of pine and softwood residues. The blends identified and the suppliers selected by both models are different. The cost of the centralized supply chain is 2%–6% lower. The implications of these results are twofold. First, these results could lead to improved collaborations in the supply chain. Second, these results provide an estimate of the approximation error from assuming centralized decision making in the supply chain.
09 BIOMASS FUELS↗
Generalized moving least squares vs. radial basis function finite difference methods for approximating surface derivatives
Approximating differential operators defined on two-dimensional surfaces is an important problem that arises in many areas of science and engineering. Over the past ten years, localized meshfree methods based on generalized moving least squares (GMLS) and radial basis function finite differences (RBF-FD) have been shown to be effective for this task as they can give high orders of accuracy at low computational cost, and they can be applied to surfaces defined only by point clouds. However, there have yet to be any studies that perform a direct comparison of these methods for approximating surface differential operators (SDOs). The first purpose of this work is to fill that gap. For this comparison, we focus on an RBF-FD method based on polyharmonic spline kernels and polynomials (PHS+Poly) since they are most closely related to the GMLS method. Additionally, we use a relatively new technique for approximating SDOs with RBF-FD called the tangent plane method since it is simpler than previous techniques and natural to use with PHS+Poly RBF-FD. Further, the second purpose of this work is to relate the tangent plane formulation of SDOs to the local coordinate formulation used in GMLS and to show that they are equivalent when the tangent space to the surface is known exactly. The final purpose is to use ideas from the GMLS SDO formulation to derive a new RBF-FD method for approximating the tangent space for a point cloud surface when it is unknown. For the numerical comparisons of the methods, we examine their convergence rates for approximating the surface gradient, divergence, and Laplacian as the point clouds are refined for various parameter choices. We also compare their efficiency in terms of accuracy per computational cost, both when including and excluding setup costs.
97 MATHEMATICS AND COMPUTING↗
Classical field approximation of ultralight dark matter: Quantum break times, corrections, and decoherence
The classical field approximation is widely used to better understand the predictions of ultralight dark matter. Here, in this work, we use the truncated Wigner approximation method to test the classical field approximation of ultralight dark matter. This method approximates a quantum state as an ensemble of independently evolving realizations drawn from its Wigner function. The method is highly parallelizable and allows the direct simulation of quantum corrections and decoherence times in systems many times larger than have been previously studied in reference to ultralight dark matter. Our study involves simulation of systems in 1, 2, and 3 spatial dimensions. We simulate three systems, the condensation of a Gaussian random field in three spatial dimensions, a stable collapsed object in three spatial dimensions, and the merging of two stable objects in two spatial dimensions. We study the quantum corrections to the classical field theory in each case. We find that quantum corrections grow exponentially during nonlinear growth with the timescale being approximately equal to the system dynamical time. In stable systems the corrections grow quadratically. We also find that the primary effect of quantum corrections is to reduce the amplitude of fluctuations on the de Broglie scale in the spatial density. Finally, we find that the timescale associated with decoherence due to gravitational coupling to baryonic matter is at least as fast as the quantum corrections due to gravitational interactions. These results are consistent with the predictions of the classical field theory being accurate.
79 ASTRONOMY AND ASTROPHYSICS↗
Scalable Programming Workflows for Validation of Quantum Computers
Hybrid quantum-classical workflows have become standard methods for executing variational algorithms and other quantum simulation techniques, which are key applications for noisy intermediate scale quantum (NISQ) computers. Validating these simulations is an important task which helps gauge the progress of quantum computer development, and classical simulation can serve as a tool to this end. Both exact and more scalable approximate methods with quantifiable error bounds can be used in validation tasks where the applicable metrics include the distance from a calculable ground truth, the quality of an error model fit to data, etc. Here we present a library extension that includes methods for validation of quantum simulations based on scalable hybrid workflows executable on high performance computers. We provide examples that use approximate methods based on tensor networks and stabilizer simulators to bound the error of quantum simulations on NISQ hardware.
Nguyen, Thien↗
Numerical solution of 2D-vector tomography problem using the method of approximate inverse
We propose a numerical solution of reconstruction problem of a two-dimensional vector field in a unit disk from the known values of the longitudinal and transverse ray transforms. The algorithm is based on the method of approximate inverse. Numerical simulations confirm that the proposed method yields good results of reconstruction of vector fields.
97 MATHEMATICS AND COMPUTING↗
Theoretical investigation of resonant frequencies of unstrapped magnetron with arbitrary side resonators
In this paper, a sector steps approximation method is proposed to investigate the resonant frequencies of magnetrons with arbitrary side resonators. The arbitrary side resonator is substituted with a series of sector steps, in which the spatial harmonics of electromagnetic field are also considered. By using the method of admittance matching between adjacent steps, as well as field continuity conditions between side resonators and interaction regions, the dispersion equation of magnetron with arbitrary side resonators is derived. Resonant frequencies of magnetrons with five common kinds of side resonators are calculated with sector steps approximation method and computer simulation softwares, in which the results have a good agreement. The relative error is less than 2%, which verifies the validity of sector steps approximation method.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗