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At least 811 records · Page 45

Nonlinear Model Predictive Control Based on Real-Time Iteration Scheme for Wave Energy Converters Using WEC-Sim: Preprint

One of several challenges that wave energy technologies face is their inability to generate electricity cost-competitively with other grid-scale energy generation sources. Several studies have identified two approaches to lower the levelised cost of electricity: reduce the cost over the device's lifetime or increase its overall electrical energy production. Several advanced control strategies have been developed to address the latter. However, only a few take into account the overall efficiency of the power take-off (PTO) system, and none of them solve the optimisation problem that arises at each sampling time on real-time. In this paper, a detailed Nonlinear model predictive control (NMPC) approach based on the real-time iteration (RTI) scheme is presented, and the controller performance is evaluated using a time-domain hydrodynamics model (WEC-Sim). The proposed control law incorporates the PTO system's efficiency in a control law to maximise the energy extracted. The study also revealed that RTI-NMPC clearly outperforms a simple resistive controller.

model predictive control↗

Three-dimensional broadband nonlinear phased array imaging

System include an ultrasonic transducer configured to couple to a nondestructive testing (NDT) sample and configured to produce and direct an ultrasonic probe wave at a selected frequency into a subsurface region of the NDT sample, a 3D laser scanning vibrometer configured to direct a detection beam in a scan area on a surface of the NDT sample and to receive a return beam from the scan area, and to detect, based on the return beam, a 3D motion of the surface across a wideband frequency range, and a processor, and a memory configured with instructions that, when executed by the processor, cause the processor to produce sub-surface image data of the NDT sample at multiple harmonics of the selected frequency in the wideband frequency range based on the detected 3D surface motion, wherein the sub-surface image data describes a nonlinear defect response produced in the NDT sample by interaction of the ultrasonic probe wave with the subsurface region.

Remillieux, Marcel↗

Multimodal nonlinear optical imaging via evanescent wave excitation

A system for multimodal nonlinear optical imaging is provided. Each mode uses a high NA objective to cause total internal reflection excitation at a sample-substrate interface. The system has a femtosecond oscillator to generate pulses used for two beams. The objective receives at least one beam, redirects the received at least one beam through a dielectric substrate to cause the TIR and produces corresponding evanescent waves in a portion of the sample adjacent to the sample-substrate interface, and collects a backward-propagating beam of pulses of responsive light. The portion of the sample illuminated by the evanescent waves emits responsive light. Different modes or combinations of the distinct modalities may be selected to access complementary chemical and structural information for various chemical species near the sample-substrate interface. Each mode may have mode-specific control such as selective beam blocking, power ratios and filtering.

Doughty, Benjamin L.↗

Porting the Nonlinear Optimization Library HiOp to Accelerator-Based Hardware Architectures

While interior point method has been the centerpiece of nonlinear programming tools used in science and engineering, its reliance on linear solvers that can tackle sparse symmetric indefinite and highly ill-conditioned problems made it difficult to implement it effectively on hardware accelerators. HiOp optimization package attempts to provide an implementation of the interior point method suitable for hardware accelerators by compressing the original sparse problem to produce an underlying linear problem that is dense and of manageable size. Implementations of dense linear solvers are more mature and utilize hardware accelerators better than their sparse counterparts. There is a number of important domain problems, such as optimal power flow analysis for power grids, where the sparse problem can be effectively compressed and deploying dense linear solver within the interior point method can improve performance. Here we describe a portable implementation of HiOp optimization engine, which uses a linear solver from Magma library and runs entirely on hardware accelerators. To compress the problem, HiOp uses customized mixed dense-sparse linear algebra. All HiOp kernels are implemented using Umpire and RAJA portability libraries. We describe details of the implementation and discuss trade-offs between performance, portability and development cost.

97 MATHEMATICS AND COMPUTING↗

Gyromagnetic nonlinear transmission line for radio frequency signal generation and pulse compression

Disclosed are non-linear transmission lines using ferromagnetic materials to generate ferromagnetic resonance oscillations. In one aspect, a non-linear transmission line apparatus is disclosed. The apparatus includes an outer conductor having a first side and a second internally facing side, and an inner conductor positioned internal to the non-linear transmission line apparatus. The apparatus further includes a ferromagnetic material surrounding the inner conductor, wherein the ferromagnetic material comprises nanoparticles of an ε-polymorph of iron oxide expressed as ε-Fe2O3. The apparatus also includes a first dielectric material positioned between the outer conductor and the inner conductor, the dielectric material in contact with both the ferromagnetic material and with the second internally facing side of the outer conductor, wherein the outer conductor, the inner conductor, the dielectric material and the ferromagnetic material form the nonlinear transmission line.

Schneider, Joseph Devin↗

SNoGloDe: A Structured Nonlinear Global Decomposition Solver

Large-scale optimization problems often require decomposition strategies and customized algorithms to achieve optimal solutions within a reasonable time. Building on the work of Cao and Zavala (2019) for solving nonlinear two-stage stochastic programs to global optimality, we implement and extend their approach. We generalize to optimization problems reformulated with a block-angular constraint structure (e.g., temporal decomposition). Our framework, written in Python using Pyomo, is highly customizable and enables parallel execution of the decomposition. SNoGloDe allows tailored branching strategies, lower bounding problems, and candidate generators to leverage problem-specific knowledge. To demonstrate effectiveness, we compare SNoGloDe’s performance with Gurobi on a temporally decomposed produced water case study.

algorithms↗

Redshifting the Cosmological Constant in Unimodular Gravity via Nonlinear Quantum Mechanics

The cosmological constant problem represents a profound conflict between quantum field theory and general relativity. Unimodular gravity offers a compelling starting point by de-gravitating the vacuum energy of the Standard Model, but this framework traditionally trades the problem of vacuum energy for a fine-tuning of initial conditions, which manifest as a ``shadow" cosmological constant. In this paper, we resolve this initial conditions problem by proposing a novel modification to gravity based on nonlinear quantum mechanics. We introduce specific state-dependent terms to the Hamiltonian, constructed from expectation values of the metric such as the average Ricci scalar. These terms alter the dynamical equations of gravity such that the shadow energy density associated with unconstrained initial conditions redshifts away with cosmic expansion, rendering it negligible at late times. The resulting cosmology is naturally dominated by matter and radiation without fine-tuning. We demonstrate that this significant infrared modification of gravity is consistent with local and cosmological tests of gravity. We comment on the possibility of testing this solution in cosmological measurements of Newton's constant.

Kaplan, David E. [Johns Hopkins U.; Tokyo U., IPMU↗

A Scalable Space-Time Domain Decomposition Approach for Solving Large Scale Nonlinear Regularized Inverse Ill Posed Problems in 4D Variational Data Assimilation

We address the development of innovative algorithms designed to solve the strong-constraint Four Dimensional Variational Data Assimilation (4DVar DA) problems in large scale applications. We present a space-time decomposition approach which employs the whole domain decomposition, i.e. both along the spacial and temporal direction in the overlapping case, and the partitioning of both the solution and the operator. Starting from the global functional defined on the entire domain, we get to a sort of regularized local functionals on the set of sub domains providing the order reduction of both the predictive and the Data Assimilation models. The algorithm convergence is developed. Performance in terms of reduction of time complexity and algorithmic scalability is discussed on the Shallow Water Equations on the sphere. The number of state variables in the model, the number of observations in an assimilation cycle, as well as numerical parameters as the discretization step in time and in space domain are defined on the basis of discretization grid used by data available at repository Ocean Synthesis/Reanalysis Directory of Hamburg University.

97 MATHEMATICS AND COMPUTING↗

Green’s Function Perspective on the Nonlinear Density Response of Quantum Many-Body Systems

We derive equations of motion for higher order density response functions using the theory of thermodynamic Green’s functions. We also derive expressions for the higher order generalized dielectric functions and polarization functions. Moreover, we relate higher order response functions and higher order collision integrals within the Martin–Schwinger hierarchy. We expect our results to be highly relevant to the study of a variety of quantum many-body systems such as matter under extreme temperatures, densities, and pressures.

Density Functional Theory↗

A quantum Monte Carlo study of systems with effective core potentials and node nonlinearities

In this report we study beryllium dihydride (BeH2) and acetylene (C2H2) molecules using real-space diffusion Monte Carlo (DMC) method. The molecules serve as perhaps the simplest prototypes that illustrate the difficulties with biases in the fixed-node DMC calculations that might appear with the use of effective core potentials (ECPs) or other nonlocal operators. This is especially relevant for the recently introduced correlation consistent ECPs (ccECPs) for 2s2p elements. Corresponding ccECPs exhibit deeper potential functions due to higher fidelity to all-electron counterparts, which could lead to larger local energy fluctuations. We point out that the difficulties stem from issues that are straightforward to address by upgrades of basis sets, use of T-moves for nonlocal terms, inclusion of a few configurations into the trial function and similar. The resulting accuracy corresponds to the ccECP target (chemical accuracy) and it is in consistent agreement with independent correlated calculations. Further possibilities for upgrading the reliability of the DMC algorithm and considerations for better adapted and more robust Jastrow factors are discussed as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis, structure, linear and nonlinear optical properties of noncentrosymmetric quaternary diamond-like semiconductors, Cu 2 ZnGeSe 4 (CZGSe) and the novel Cu 4 ZnGe 2 Se 7

In this work, two quaternary diamond-like semiconductors (DLSs) in the Cu-Zn-Ge-Se system, the known Cu 2 ZnGeSe 4 (also referred to as CZGSe) and the new Cu 4 ZnGe 2 Se 7 , are compared in terms of their crystal structures, electronic structures and physicochemical properties. Both compounds were prepared by high-temperature, solid-state synthesis at 800 degrees C. Single crystal X-ray diffraction was used to determine the structure of Cu 4 ZnGe 2 Se 7 . The structures of both Cu 2 ZnGeSe 4 and Cu 4 ZnGe 2 Se 7 can be considered as derivatives of cubic diamond. Cu 4 ZnGe 2 Se 7 , with a reduced symmetry due to the cation ordering pattern, adopts the Cu 4 NiSi 2 S 7 structure type, with space group C2. The corner-sharing tetrahedra in Cu 4 ZnGe 2 Se 7 are slightly distorted because the charge for some of the S 2 - anions is not compensated by the first-nearest-neighbor cations. Rietveld refinements using synchrotron X-ray powder diffraction data were used to assess the phase purity of the samples and confirm the bulk structural behavior. Diffuse reflectance UV/Vis/NIR spectroscopy shows that Cu 2 ZnGeSe 4 and Cu 4 ZnGe 2 Se 7 have direct optical bandgaps of 1.38 and 0.91 eV, respectively. Electronic structure calculations implementing density functional theory confirm the direct bandgap for Cu 4 ZnGe 2 Se 7 , with a calculated value of 0.62 eV. Both compounds are air stable, thermally stable up to relatively high temperatures, undergo phase transitions and have wide windows of optical clarity. The Kurtz-Perry powder technique was used to determine the second harmonic generation (SHG) responses using a commercial AgGaSe 2 standard. While Cu 4 ZnGe 2 Se 7 displays a weak SHG response, Cu 2 ZnGeSe 4 exhibits a response that is greater than several benchmark materials, with a large SHG coefficient, χ (2) , of 43 ± 6 pm/V at λ = 2900 nm.

36 MATERIALS SCIENCE↗