The Similarity Structure Function Lagrangian CFD and the Finite Scale Theory
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97 MATHEMATICS AND COMPUTING↗
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Electromagnetic and gravitational interactions from Lagrangian mechanics
Highlights: • Background Maxwell and Einstein fields are universal features of Lagrangian systems. • The Lagrangian function is promoted to a dynamic field. • The Einstein–Maxwell theory is derived from Lagrangian mechanics. Background fields of electromagnetic and gravitational type emerge in the low kinetic energy limit of any regular Lagrangian system and, in particular, in the corresponding limit of any spacetime theory in which the free motion of test particles is described by an unspecified regular Lagrangian. Electromagnetic and gravitational type interactions are therefore a universal feature of low kinetic energy Lagrangian systems. These background interactions can be consistently turned into dynamic Einstein–Maxwell fields by promoting the Lagrangian function to a dynamic scalar field on the tangent bundle of the configuration space. Accordingly, Einstein–Maxwell theory can be deduced from the assumption that the motion of elementary test particles in spacetime is described by Lagrangian mechanics. For higher kinetic energy-type values, identified with the square of the invariant mass of the particle, the Lagrangian induces higher rank interactions that seem however too weak to have been detected in spacetime physics, but which might prove relevant at the Planck scale.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Arbitrary-order Bernstein basis functions for Lagrangian Hydrodynamics [Slides]
Abstract not provided.
97 MATHEMATICS AND COMPUTING↗
Online Optimization as a Feedback Controller: Stability and Tracking
This paper develops and analyzes feedback-based online optimization methods to regulate the output of a linear time-invariant (LTI) dynamical system to the optimal solution of a time-varying convex optimization problem. The design of the algorithm is based on continuous-time primal-dual dynamics, properly modified to incorporate feedback from the LTI dynamical system, applied to a proximal augmented Lagrangian function. The resultant closed-loop algorithm tracks the solution of the time-varying optimization problem without requiring knowledge of (time-varying) disturbances in the dynamical system. The analysis leverages integral quadratic constraints to provide linear matrix inequality (LMI) conditions that guarantee global exponential stability and bounded tracking error. Analytical results show that, under a sufficient time-scale separation between the dynamics of the LTI dynamical system and the algorithm, the LMI conditions can be always satisfied. The paper further proposes a modified algorithm that can track an approximate solution trajectory of the constrained optimization problem under less restrictive assumptions. As an illustrative example, the proposed algorithms are showcased for power transmission systems, to compress the time scales between secondary and tertiary control, and allow to simultaneously power re-balancing and tracking of DC optimal power flow points.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Distribution Locational Marginal Pricing (DLMP) for Congestion Management and Voltage Support
In this paper, a day-ahead market-clearing model for smart distribution systems is proposed. Various types of distributed energy resources (DERs), such as distributed energy storage, distributed generators, microgrids, and load aggregators, can bid into the day-ahead distribution-level electricity market. Considering system Volt/VAR control, network reconfiguration, and interactions with the wholesale market, an optimization model is built to clear the day-ahead market, through which the distribution locational marginal pricing (DLMPs) for both active power and reactive power are determined. Through derivations of the Lagrangian function and sensitivity factors, DLMPs are decomposed to five components (i.e., marginal costs for active power, reactive power, congestion, voltage support, and loss), which provide price signals to motivate DERs to contribute to congestion management and voltage support. Finally, case studies demonstrate the effectiveness of the proposed method.
congestion management↗
Generalized Graph Laplacian Based Anomaly Detection for Spatiotemporal MicroPMU Data
This letter develops a novel anomaly detection method using the generalized graph Laplacian (GGL) matrix to visualize the spatiotemporal relationship of distribution-level phasor measurement unit (uPMU) data. The uPMU data in a specific time horizon is segregated into multiple segments. An optimization problem formulated as a Lagrangian function is utilized to estimate the GGL matrix. During the iterative process, an optimal update is constituted as a quadratic program (QP) problem. To perform the uPMU-based spatiotemporal analysis, normalized diagonal elements of GGL matrix are proposed as a quantitative metric. The effectiveness of the developed method is demonstrated through real-world uPMU measurements gathered from test feeders in Riverside, CA.
97 MATHEMATICS AND COMPUTING↗
Online Primal-Dual Methods With Measurement Feedback for Time-Varying Convex Optimization
This paper addresses the design and analysis of feedback-based online algorithms to control systems or networked systems based on performance objectives and engineering constraints that may evolve over time. The emerging timevarying convex optimization formalism is leveraged to model optimal operational trajectories of the systems, as well as explicit local and network-level operational constraints. Departing from existing batch and feed-forward optimization approaches, the design of the algorithms capitalizes on an online implementation of primal-dual projected-gradient methods; the gradient steps are, however, suitably modified to accommodate feedback from the system in the form of measurements - hence, the term 'online optimization with feedback.' By virtue of this approach, the resultant algorithms can cope with model mismatches in the algebraic representation of the system states and outputs, they avoid pervasive measurements of exogenous inputs, and they naturally lend themselves to a distributed implementation. Under suitable assumptions, analytical convergence claims are established in terms of dynamic regret. Furthermore, when the synthesis of the feedback-based online algorithms is based on a regularized Lagrangian function, Q-linear convergence to solutions of the time-varying optimization problem is shown.
97 MATHEMATICS AND COMPUTING↗
Boson–fermion duality in a gravitational background
We study the 2+1 dimensional boson–fermion duality in the presence of background curvature and electromagnetic fields. The main players are, on the one hand, a massive complex |ϕ|{sup 4} scalar field coupled to a U(1) Maxwell–Chern–Simons gauge field at level 1, representing a relativistic composite boson with one unit of attached flux, and on the other hand, a massive Dirac fermion. We show that, in a curved background and at the level of the partition function, the relativistic composite boson, in the infinite coupling limit, is dual to a short-range interacting Dirac fermion. The coupling to the gravitational spin connection arises naturally from the spin factors of the Wilson loop in the Chern–Simons theory. A non-minimal coupling to the scalar curvature is included on the bosonic side in order to obtain agreement between partition functions. Although an explicit Lagrangian expression for the fermionic interactions is not obtained, their short-range nature constrains them to be irrelevant, which protects the duality in its strong interpretation as an exact mapping at the IR fixed point between a Wilson–Fisher–Chern–Simons complex scalar and a free Dirac fermion. We also show that, even away from the IR, keeping the |ϕ|{sup 4} term is of key importance as it provides the short-range bosonic interactions necessary to prevent intersections of worldlines in the path integral, thus forbidding unknotting of knots and ensuring preservation of the worldline topologies.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Non-local Lagrangians from renormalons and analyzable functions
We embed in a generalized Borel procedure the notion of renormalization and renormalons. While there are several efforts in literature to have a semi-classical understanding of the renormalons, here we argue that this is not the fundamental issue and show how to deal with the problem. We find that the effective Lagrangians describing the effects of renormalons are non-local in space but local in time. The quark–antiquark potential in QCD with an infinite number of fermions is also analyzed. The connection between the analyzable functions, the Callan–Symanzyk equation and the renormalons, provides an insight of a non-perturbative renormalization from the standard perturbative renormalization approach.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Non-minimally coupled scalar field in Kantowski–Sachs model and symmetry analysis
The paper deals with a non-minimally coupled scalar field in the background of homogeneous but anisotropic Kantowski–Sachs space–time model. The form of the coupling function of the scalar field with gravity and the potential function of the scalar field are not assumed phenomenologically, rather they are evaluated by imposing Noether symmetry to the Lagrangian of the present physical system. The physical system gets considerable mathematical simplification by a suitable transformation of the augmented variables (a,b,ϕ)→(u,v,w) and by the use of the conserved quantities due to the geometrical symmetry. Finally, cosmological solutions are evaluated and analyzed from the point of view of the present evolution of the Universe.
79 ASTRONOMY AND ASTROPHYSICS↗
An Immersed Finite Element Lagrangian-Eulerian Code-Coupling Framework
This report presents an assessment of immersed Eulerian-Lagrangian code-coupling techniques suitable for use in a broad range of mechanics applications. The coupling algorithm is based on an immersed finite element method that considers the Lagrangian and Eulerian overlap regions in the overall variational formulation. In this report the basic formulation details are presented followed by various aspects of the code-coupling algorithm using OpenIFEM as the Lagrangian/coupling framework. A series of representative test cases that illustrate the code-coupling algorithm are discussed. The current work provides an in-depth investigation into the immersed finite element method for the purposes of providing a rigorous coupling technique that is minimally invasive in the respective Eulerian and Lagrangian codes. A number of extensions to the base immersed finite element method have been examined. These extension include nodal and quadrature-based indicator functions, a Lagrangian volume-fraction calculation in regions of overlap, and the use of penalty constraints between the Lagrangian and Eulerian domains. A unique MPI-based coupling strategy that retains the independent MPI structure of each code has been demonstrated.
97 MATHEMATICS AND COMPUTING↗
A class of customized proximal point algorithms for linearly constrained convex optimization
In this paper, we propose a class of customized proximal point algorithms for linearly constrained convex optimization problems. The algorithms are implementable, provided that the proximal operator of the objective function is easy to evaluate. We show that, with special setting of the algorithmic scalar, our algorithms contain the customized proximal point algorithm (He et al., Optim Appl 56:559–572, 2013), the linearized augmented Lagrangian method (Yang and Yuan, Math Comput 82:301–329, 2013), the Bregman Operator Splitting algorithm (Zhang et al., SIAM J Imaging Sci 3:253–276, 2010) as special cases. The global convergence and worst-case convergence rate measured by the iteration complexity are established for the proposed algorithms. Numerical results demonstrate that the algorithms work well for a wide range of the scalar.
97 MATHEMATICS AND COMPUTING↗
Ergodic Lagrangian dynamics in a superhero universe
We present a fictional scenario that, while undeniably whimsical, provides the foundation for a unique exercise in extended problem solving, physics analysis, and quantitative model development. Starting with the foundational premise of the Wild Cards shared-world superhero universe, we demonstrate how a variety of concepts appropriate to the advanced undergraduate level—ergodicity, functional analysis, Lagrangian mechanics, and the ever-important simplifying approximation—can be combined into a rich, coherent mathematical model. The goal of this case study is to develop a useful pedagogical exercise in exploring an open-ended research question that presents, at first glance, no clear path forward. Being both eclectic and lengthy, this exercise offers a unique way for students to apply their core physics and mathematics education. It is perhaps best used within a senior honors seminar or within a brief (e.g., January term) elective class.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Some aspects of the five-dimensional Lovelock black hole spacetime: Strong homotopy retract, perihelion precession and quasistationary levels
Highlights: • Some topological aspects are explored. • The perihelion precession is calculated. • The general Heun functions are applied to obtain analytical solutions. • The quasibound states and the radial wave eigenfunctions are obtained. In this work we explore some mathematical physics aspects of the spherically symmetric Lovelock black hole in high dimensions. Intended for this aim, we thoroughly consider the metric corresponding to the five-dimensional Lovelock black hole spacetime. We construct the strong retractions by the geodesic equations on the background under consideration. As a result, from the topological point of view, we construct the theory of strong homotopy retract, which will allow us, in principle, to better understand some of its suitable applications on astrophysics and cosmology, in particular, in the analysis of the spacetime singularities. We find the solutions of the equation of motion for both radial and angular coordinates, and then we describe the outer (“exterior”) and lower (“interior”) apparent horizons. Indeed, the outer apparent horizon is the last surface from which the light waves could still escape from the black hole. Thus, it is meaningful to analyze some physical phenomena related to quantum particles propagating outside the exterior apparent horizon, in particular, we discuss the quasistationary levels of scalar fields and their radial wave functions, which are given in terms of the general Heun functions. We also calculate the perihelion precession in this background.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Effects of Nozzle Radial Position, Separation Angle, and Gas Flow Partitioning on the Mixing, Eye Area, and Wall Shear Stress in Ladles Fitted with Dual Plugs
Mixing time, slag eye area, and wall shear stress in a ladle fitted with dual plugs have been studied as a function of operating variables, namely, gas flow rate, radial nozzle position, separation angle between nozzles and flow rate partitioning. While the mixing time and slag eye area have been experimentally investigated in a scaled water model (with and without a top slag layer), the shear stress on the vessel wall has been studied computationally via a RANS-based turbulent, three-dimensional coupled Eulerian–Lagrangian (VOF-DPM), multiphase flow model. Experimental and computational results have indicated that the mixing, eye area, and wall shear stress depend on the gas flow rate, i.e., while mixing efficiency increases with the increasing gas flow rate, the slag eye area, and wall shear stress, in contrast, become more pronounced with the increasing gas flow, leading to an undesirable operating regime. The radial nozzle position, separation angle between the nozzles and flow rate partitioning at any given flow rate also influence the ladle process performance, influencing the mixing, eye area, and wall shear stress, albeit to a varied degree. Within the range of operating conditions studied, an expected inverse correspondence between mixing time and shear behavior was observed. Experimental and computational results in conjunction have indicated that the best arrangement of porous plugs or gas injection nozzles for superior ladle process performance is dependent on the gas flow rate and is specific to the desired objective (i.e., decreasing the mixing time, or slag eye area and wall shear stress). Hence, a unique gas injection practice cannot and should not be suggested as the optimum for ladle metallurgy in steelmaking. Nevertheless, if the mixing time is the parameter of primary interest, a nozzle configuration with equal flow partitioning (1:1) between the nozzles and identical nozzle radial positions (0.7R/0.7R, 45 deg) should suffice for both low and high gas flow rates. In contrast, a nonidentical nozzle radial position (0.7R/0.5R, 90 deg) and an unequal gas flow rate per nozzle (1:3) appear preferable if both ladle eye and shear stresses, rather than mixing, are the issues of concern.
36 MATERIALS SCIENCE↗
Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamics scheme
Lagrangian methods to solve the inviscid Euler equations produce numerical oscillations near shock waves. A common approach to reducing these oscillations is to add artificial viscosity (AV) to the discrete equations. The AV term acts as a dissipative mechanism that attenuates oscillations by smearing the shock across a finite number of computational cells. However, AV introduces several control parameters that are not determined by the underlying physical model, and hence, in practice are tuned to the characteristics of a given problem. We seek to improve the standard quadratic-linear AV form by replacing it with a learned neural function that reduces oscillations relative to exact solutions of the Euler equations, resulting in a hybrid numerical-neural hydrodynamic solver. Because AV is an artificial construct that exists solely to improve the numerical properties of a hydrodynamic code, there is no offline ‘viscosity data’ against which a neural network can be trained before inserting into a numerical simulation, thus requiring online training. We achieve this via differentiable programming, i.e. end-to-end backpropagation or adjoint solution through both the neural and differential equation code, using automatic differentiation of the hybrid code in the Julia programming language to calculate the necessary loss function gradients. A novel offline pre-training step accelerates training by initializing the neural network to the default numerical AV scheme, which can be learned rapidly by space-filling sampling over the AV input space. We find that online training over early time steps of simulation is sufficient to learn a neural AV function that reduces numerical oscillations in long-term hydrodynamic shock simulations. These results offer an early proof-of-principle that online differentiable training of hybrid numerical schemes with novel neural network components can improve certain performance aspects existing in purely numerical schemes.
97 MATHEMATICS AND COMPUTING↗
Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management
Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Analytic error analysis of cross section interpolation methods in nodal diffusion codes - I : Theory
This paper discusses two cross section interpolation methods commonly found in popular nodal codes; the partial derivatives and multiple tables models. The motivation for choosing a model, and thus a case matrix structure, is a trade off between accuracy and computational cost. Due to decades of experience, there are default structures that are sufficient for current light water reactor analysis. However, this is not necessarily the case for advanced reactor designs. Therefore, it is advantageous to understand the sources of error in cross section interpolation models so that the quality of a case matrix may be improved. A mathematical framework for these models is presented in this work that provides a more rigorous connection between the nuclear engineering field's cross section interpolation methods and the broader mathematical field of function approximation. The two cross section models examined in this paper were found to utilize Lagrange interpolation and are a subset of Lagrange tensor products. Classical results of Lagrange polynomial error analysis were then applied to the partial derivative and multiple tables models to derive expressions for the total point-wise error. The analytical results classify the total error into two parts: the model form error and interpolation error. Finally, based on our observations, a better foundation for improving the quality of a case matrix is proposed. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗