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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Digital memcomputing: From logic to dynamics to topology

Digital memcomputing machines (DMMs) are a class of computational machines designed to solve combinatorial optimization problems. A practical realization of DMMs can be accomplished via electrical circuits of highly non-linear, point-dissipative dynamical systems engineered so that periodic orbits and chaos can be avoided. A given logic problem is first mapped into this type of dynamical system whose point attractors represent the solutions of the original problem. A DMM then finds the solution via a succession of elementary instantons whose role is to eliminate solitonic configurations of logical inconsistency (“logical defects”) from the circuit. By employing a supersymmetric theory of dynamics, a DMM can be described by a cohomological field theory that allows for computation of certain topological matrix elements on instantons that have the mathematical meaning of intersection numbers on instantons. We discuss the “dynamical” meaning of these matrix elements, and argue that the number of elementary instantons needed to reach the solution cannot exceed the number of state variables of DMMs, which in turn can only grow at most polynomially with the size of the problem. These results shed further light on the relation between logic, dynamics and topology in digital memcomputing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

Computation of maximum gust loads in nonlinear aircraft using a new method based on the matched filter approach and numerical optimization

Time-correlated gust loads are time histories of two or more load quantities due to the same disturbance time history. Time correlation provides knowledge of the value (magnitude and sign) of one load when another is maximum. At least two analysis methods have been identified that are capable of computing maximized time-correlated gust loads for linear aircraft. Both methods solve for the unit-energy gust profile (gust velocity as a function of time) that produces the maximum load at a given location on a linear airplane. Time-correlated gust loads are obtained by re-applying this gust profile to the airplane and computing multiple simultaneous load responses. Such time histories are physically realizable and may be applied to aircraft structures. Within the past several years there has been much interest in obtaining a practical analysis method which is capable of solving the analogous problem for nonlinear aircraft. Such an analysis method has been the focus of an international committee of gust loads specialists formed by the U.S. Federal Aviation Administration and was the topic of a panel discussion at the Gust and Buffet Loads session at the 1989 SDM Conference in Mobile, Alabama. The kinds of nonlinearities common on modern transport aircraft are indicated. The Statical Discrete Gust method is capable of being, but so far has not been, applied to nonlinear aircraft. To make the method practical for nonlinear applications, a search procedure is essential. Another method is based on Matched Filter Theory and, in its current form, is applicable to linear systems only. The purpose here is to present the status of an attempt to extend the matched filter approach to nonlinear systems. The extension uses Matched Filter Theory as a starting point and then employs a constrained optimization algorithm to attack the nonlinear problem.

Pototzky, Anthony S.↗
DOE OSTI2014

Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization

Summary An adaptive approach to using reduced‐order models (ROMs) as surrogates in partial differential equations (PDE)‐constrained optimization is introduced that breaks the traditional offline‐online framework of model order reduction. A sequence of optimization problems constrained by a given ROM is defined with the goal of converging to the solution of a given PDE‐constrained optimization problem. For each reduced optimization problem, the constraining ROM is trained from sampling the high‐dimensional model (HDM) at the solution of some of the previous problems in the sequence. The reduced optimization problems are equipped with a nonlinear trust‐region based on a residual error indicator to keep the optimization trajectory in a region of the parameter space where the ROM is accurate. A technique for incorporating sensitivities into a reduced‐order basis is also presented, along with a methodology for computing sensitivities of the ROM that minimizes the distance to the corresponding HDM sensitivity, in a suitable norm. The proposed reduced optimization framework is applied to subsonic aerodynamic shape optimization and shown to reduce the number of queries to the HDM by a factor of 4‐5, compared with the optimization problem solved using only the HDM, with errors in the optimal solution far less than 0.1%. Copyright © 2014 John Wiley & Sons, Ltd.

Zahr, Matthew J.↗
DOE OSTI2020

An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems

The goal of this paper is to solve a class of stochastic optimal control problems numerically, in which the state process is governed by an Itô type stochastic differential equation with control process entering both in the drift and the diffusion, and is observed partially. The optimal control of feedback form is determined based on the available observational data. In this work, we call this type of control problems the data driven feedback control. The computational framework that we introduce to solve such type of problems aims to find the best estimate for the optimal control as a conditional expectation given the observational information. To make our method feasible in providing timely feedback to the controlled system from data, we develop an efficient stochastic optimization algorithm to implement our computational framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Sequence of polyhedral relaxations for nonlinear univariate functions

Here, given a nonlinear, univariate, bounded, and differentiable function f(x), this article develops a sequence of Mixed Integer Linear Programming (MILP) and Linear Programming (LP) relaxations that converge to the graph of f(x) and its convex hull, respectively. Theoretical convergence of the sequence of relaxations to the graph of the function and its convex hull is established. For nonlinear non-convex optimization problems, the relaxations presented in this article can be used to construct tight MILP and LP relaxations. These MILP and the LP relaxations can also be used with MILP-based and spatial branch-and-bound based global optimization algorithms, respectively.

42 ENGINEERING↗
DOE OSTI2014

Exploring the effects of data quality, data worth, and redundancy of CO2 gas pressure and saturation data on reservoir characterization through PEST Inversion

This study examined the impacts of reservoir properties on CO2 migration after subsurface injection and evaluated the possibility of characterizing reservoir properties using CO2 monitoring data such as saturation distribution. The injection reservoir was assumed to be located 1400-1500 m below the ground surface such that CO2 remained in the supercritical state. The reservoir was assumed to contain layers with alternating conductive and resistive properties, which is analogous to actual geological formations such as the Mount Simon Sandstone unit. The CO2 injection simulation used a cylindrical grid setting in which the injection well was situated at the center of the domain, which extended up to 8000 m from the injection well. The CO2 migration was simulated using the PNNL-developed simulator STOMP-CO2e (the water-salt-CO2 module). We adopted a nonlinear parameter estimation and optimization modeling software package, PEST, for automated reservoir parameter estimation. We explored the effects of data quality, data worth, and data redundancy on the detectability of reservoir parameters using CO2 saturation monitoring data, by comparing PEST inversion results using data with different levels of noises, various numbers of monitoring wells and locations, and different data collection spacing and temporal sampling intervals. This study yielded insight into the use of CO2 saturation monitoring data for reservoir characterization and how to design the monitoring system to optimize data worth and reduce data redundancy.

Carbon sequestration↗
DOE OSTI2014

A simulation environment for ITER PCS development

A simulation environment known as the Plasma Control System Simulation Platform (PCSSP), specifically designed to support development of the ITER Plasma Control System (PCS), is currently under construction by an international team encompassing a cross-section of expertise in simulation and exception handling for plasma control. The proposed design addresses the challenging requirements of supporting the PCS design. This work provides an overview of the PCSSP project and a discussion of some of the major features of its design. Plasma control for the ITER tokamak will be significantly more challenging than for existing fusion devices. An order of magnitude greater performance is needed for some types of control, which together with limited actuator authority, implies that optimized individual controllers and nonlinear saturation logic are required. At the same time, consequences of control failure are significantly more severe, which implies a conflicting requirement for robust control. It also implies a requirement for comprehensive and robust exception handling. Coordinated control of multiple competing objectives with significant interactions, together with many shared uses of actuators to control multiple variables, implies that highly integrated control logic and shared actuator management will be required. It remains a challenge for the integrated technologies to simultaneously address these multiple and often competing requirements to be demonstrated on existing fusion devices and adapted for ITER in time to support its operational schedule. We describe ways in which the PCSSP will help address these challenges to support design of both the ITER PCS itself and the algorithms that will be implemented therein. and at the same time greatly reduce the cost of that development. We summarize the current status of the PCSSP design task, including system requirements and preliminary design documents already delivered as well as features of the ongoing detailed architectural design. The methods being incorporated in the detailed design are based on prior experience with control simulation environments in fusion and on standard practices prevalent in development of control-intensive industrial product designs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Delivery drone route planning over a battery swapping network

Many enterprises invest on drone delivery research and development to drop off packages at consumers’ doorsteps in a matter of minutes. We study delivery drone route planning over a battery swapping network allowing farther reach by penetrating current battery capacity constraints. A mixed-integer nonlinear programming model is created to plan efficient drone routing over the swapping machines by minimizing the delivery lead time. We develop an exact solution method, evaluate its performance, and compare it with a straightforward nonlinear solver application. A case study highlights the applicability of the model. Data and source code to the solver are publicly shared.

drone battery swapping↗
DOE OSTI2020

Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles

The range anxiety has been a major factor that affects the market acceptance of electric vehicles. Even with the recent development of battery technologies, a lack of charging stations and range anxiety are still significant concerns, specifically for intercity trips. This calls for more investments in building charging stations and advancing battery technologies to increase the market share of electric vehicles and improve sustainability. This study suggests a configuration for plug-in electric vehicle charging infrastructure to support long-distance intercity trips of electric vehicles at the network level. A model is proposed to minimize the total system cost including infrastructure investment (building charging stations/spots) and travel time delays (charging time, waiting time in the queue, and detour time to access charging stations). This study fills existing gaps in the literature by capturing realistic patterns of travel demand and considering flow-dependent charging delays at charging stations. Furthermore, the proposed model, which is formulated as a mixed-integer program with nonlinear constraints, solves the optimization problem at the network level. At the network level, impacts of charging station locations on the traffic assignment problem with a mixed fleet of electric and conventional vehicles need to be considered. To this end, a traffic assignment module is integrated with a simulated annealing algorithm. The numerical experiments show a satisfactory application of the model for a full-scale case study (intercity network in Michigan). The solution quality and efficiency of the proposed solution algorithm are evaluated against those of an enumeration approach for a small case study. The results suggest that even for the current market share and charging stations’ setting, a significant investment is needed to support intercity trips without range anxiety issues and with acceptable delays. Additionally, through sensitivity analyses, the required infrastructure and battery investments to support intercity trips with acceptable delays are established for hypothetical increased market shares and battery size in the future.

42 ENGINEERING↗
DOE OSTI2022

A learned closure method applied to phase mixing in a turbulent gradient-driven gyrokinetic system in simple geometry

We present a new method for formulating closures that learn from kinetic simulation data. We apply this method to phase mixing in a simple gyrokinetic turbulent system – temperature-gradient-driven turbulence in an unsheared slab. The closure, called the learned multi-mode (LMM) closure, is constructed by, first, extracting an optimal basis from a nonlinear kinetic simulation using singular value decomposition. Subsequent nonlinear fluid simulations are projected onto this basis and the results are used to formulate the closure. We compare the closure with other closures schemes over a broad range of the relevant two-dimensional parameter space (collisionality and gradient drive). We find that the turbulent kinetic system produces phase-mixing rates much lower than the linear expectations, which the LMM closure is capable of capturing. We also compare radial heat fluxes. A Hammett–Perkins closure, generalized to include collisional effects, is quite successful throughout the parameter space, producing ${\sim }14\,\%$ root-mean-square (r.m.s.) error. The LMM closure is also very effective: when trained at three (two) points (in a 35 point parameter grid), the LMM closure produces $8\,\%$ ( $12\,\%$ ) r.m.s. errors. The LMM procedure can be readily generalized to other closure problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Enhanced High Resolution RBS System

Improvements in full spectrum resolution with the second NEC high resolution RBS system are summarized. Results for 50 A ring TiN/HfO films on Si yielding energy resolution on the order of 1 keV are also presented. Detector enhancements include improved pulse processing electronics, upgraded shielding for the MCP/RAE detector, and reduced noise generated from pumping. Energy resolution measurements on spectra front edge coupled with calculations using 0.4mStr solid angle show that beam energy spread at 400 KeV from the Pelletron registered accelerator is less than 100 eV. To improve user throughput, magnet control has been added to the automatic data collection. Depth profiles derived from experimental data are discussed. For the thin films profiled, depth resolutions were on the Angstrom level with the non-linear energy/channel conversions ranging from 100 to 200 eV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Terahertz generation by two cross focused laser beams in collisional plasmas

The role of two cross-focused spatial-Gaussian laser beams has been studied for the high power and efficient terahertz (THz) radiation generation in the collisional plasma. The nonlinear current at THz frequency arises on account of temperature dependent collision frequency of electrons with ions in the plasma and the presence of a static electric field (applied externally in the plasma) and density ripple. Optimisation of laser-plasma parameters gives the radiated THz power of the order of 0.23 MW.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Enhancement of temporal contrast of high-power laser pulses in an anisotropic medium with cubic nonlinearity

We consider the methods for enhancing the temporal contrast of super-high-power laser pulses, based on the conversion of radiation polarisation in a medium with cubic nonlinearity. For a medium with weak birefringence and isotropic nonlinearity, we propose a new scheme to enhance the temporal contrast. For a medium with anisotropic nonlinearity, the efficiency of the temporal contrast optimisation is shown to depend not only on the spatial orientation of the crystal and B-integral, but also on the type of the crystal lattice symmetry. (extreme light fields and their applications)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Extended analysis of CMB constraints on non-gaussianity in isocurvature perturbations

We study CMB constraints on non-Gaussianity from isocurvature perturbations of general types. Specifically, we study CDM/neutrino isocurvature perturbations which are uncorrelated or totally correlated with adiabatic ones. Using the data from the WMAP 7-year observation at V and W bands, we obtained optimal constraints on the nonlinearity parameters of adiabatic and isocurvature perturbations. Our result shows that primordial perturbations are consistent with Gaussian ones at around 2σ level for above mentioned isocurvature modes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Fault geometry and slip distribution of the 2008 M w 7.9 Wenchuan, China earthquake, inferred from GPS and InSAR measurements

We revisit the problem of coseismic rupture of the 2008 M w 7.9 Wenchuan earthquake. Precise determination of the fault structure and slip distribution provides critical information about the mechanical behaviour of the fault system and earthquake rupture. We use all the geodetic data available, craft a more realistic Earth structure and fault model compared to previous studies, and employ a nonlinear inversion scheme to optimally solve for the fault geometry and slip distribution. Compared to a homogeneous elastic half-space model and laterally uniform layered models, adopting separate layered elastic structure models on both sides of the Beichuan fault significantly improved data fitting. Our results reveal that: (1) The Beichuan fault is listric in shape, with near surface fault dip angles increasing from ~36° at the southwest end to ~83° at the northeast end of the rupture. (2) The fault rupture style changes from predominantly thrust at the southwest end to dextral at the northeast end of the fault rupture. (3) Fault slip peaks near the surface for most parts of the fault, with~8.4mthrust and ~5 m dextral slip near Hongkou and ~6 m thrust and ~8.4 m dextral slip near Beichuan, respectively. (4) The peak slips are located around fault geometric complexities, suggesting that earthquake style and rupture propagation were determined by fault zone geometric barriers. Such barriers exist primarily along restraining left stepping discontinuities of the dextralcompressional fault system. (5) The seismic moment released on the fault above 20 km depth is 8.2 × 10 21 N m, corresponding to an M w 7.9 event. The seismic moments released on the local slip concentrations are equivalent to events of M w 7.5 at Yingxiu-Hongkou, M w 7.3 at Beichuan-Pingtong, M w 7.2 near Qingping, M w 7.1 near Qingchuan, and M w 6.7 near Nanba, respectively. (6) The fault geometry and kinematics are consistent with a model in which crustal deformation at the eastern margin of the Tibetan plateau is decoupled by differential motion across a decollement in the mid crust, above which deformation is dominated by brittle reverse faulting and below which deformation occurs by viscous horizontal shortening and vertical thickening.

58 GEOSCIENCES↗
DOE OSTI2014

SU-D-17A-03: 5D Respiratory Motion Model Based Iterative Reconstruction Method for 4D Cone-Beam CT

Purpose: The purpose of this work is to develop a new iterative reconstruction method for 4D cone-beam CT (CBCT) based on a published time-independent 5D respiratory motion model. The proposed method will offer a single high-resolution image at a user-selected breathing phase and the 5D motion model parameters, which could be used to generate the breathing pattern during the CT acquisition. Methods: 5D respiratory motion model was proposed for accurately modeling the motion of lung and lung tumor tissues. 4D images are then parameterized by a reference image, measured breathing amplitude, breathing rate, two time-independent vector fields that describe the 5D model parameters, and a scalar field that describes the change in HU as a function of breathing amplitude. In contrast with the traditional method of reconstructing multiple temporal image phases to reduce respiratory artifact, 5D model based method simplify the problem into the reconstruction of a single reference image and the 5D motion model parameters. The reconstruction formulation of the reference image and scalar and vector fields is a nonlinear least-square optimization problem that consists of solving the reference image and fields alternately, in which the reference image is regularized with the total variation sparsity transform and the vector fields are solved through linearizations regularized by the H1 norm. 2D lung simulations were performed in this proof-of-concept study. Results: The breathing amplitude, its rate, and the corresponding scalar and vector fields were generated from a patient case. Compared with filtered backprojection method and sparsity regularized iterative method for the phase-by-phase reconstruction, the proposed 5D motion model based method yielded improved image quality. Conclusion: Based on 5D respiratory motion model, we have developed a new iterative reconstruction method for 4D CBCT that has the potential for improving image quality while providing needed on-table motion information.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Subgap states in disordered superconductors

We revise the problem of the density of states in disordered superconductors. Randomness of local sample characteristics translates to the quenched spatial inhomogeneity of the spectral gap, smearing the BCS coherence peak. We show that various microscopic models of potential and magnetic disorder can be reduced to a universal phenomenological random order parameter model, whereas the details of the microscopic description are encoded in the correlation function of the order parameter fluctuations. The resulting form of the density of states is generally described by two parameters: the width {Gamma} measuring the broadening of the BCS peak and the energy scale {Gamma}{sub tail} that controls the exponential decay of the density of subgap states. We refine the existing instanton approaches for determination of {Gamma}{sub tail} and show that they appear as limiting cases of a unified theory of optimal fluctuations in a nonlinear system. The application to various types of disorder is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Binary Optimal Control of Single-Flux-Quantum Pulse Sequences

We introduce a binary, relaxed gradient, trust-region method for optimizing pulse sequences for single flux quanta (SFQ) control of a quantum computer. The pulse sequences are optimized with the goal of realizing unitary gate transformations. Each pulse has a fixed amplitude and duration. Here we model this process as an binary optimal control problem, constrained by Schrödinger’s equation, where the binary variables indicate whether each pulse is on or off. We introduce a first-order trust-region method, which takes advantage of a relaxed gradient to determine an optimal pulse sequence that minimizes the gate infidelity, while also suppressing leakage to higher energy levels. The proposed algorithm has a computational complexity of O(p log(p)), where p is the number of pulses in the sequence. We present numerical results for the H and X gates, where the optimized pulse sequences give gate fidelity’s better than 99.9%, in ≈ 25 trust-region iterations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗