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At least 127 records · Page 7

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Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification(Presentation)

Two phase-optimized multisine peak factor minimization algorithms are presented and evaluated. The first algorithm minimizes peak factor by iteratively clipping the peaks of generated multisine signals. The second algorithm optimizes peak factor indirectly through minimization of an approximation of the infinity norm of the multisine. Algorithm performance was evaluated as a function of different signal properties, including the number of harmonics, harmonic spacing, and number of snow harmonics (extra harmonics included for further reduction of the peak factor). The two algorithms are compared against results obtained by minimizing peak factor directly using a simplex algorithm, which has been a common approach when designing phase-optimized multisines for system identification flight tests. Sample results show that the clipping and infinity norm algorithms produced multisine signals with comparable peak factors that were lower than that of the simplex algorithm. However, the clipping algorithm runs an order of magnitude faster than the other two algorithms, which also makes it practical to repeat the algorithm multiple times to achieve even lower peak factors.

flight test↗

DOE OSTI2017

Increasingly minimal bias routing

A system and algorithm configured to generate diversity at the traffic source so that packets are uniformly distributed over all of the available paths, but to increase the likelihood of taking a minimal path with each hop the packet takes. This is achieved by configuring routing biases so as to prefer non-minimal paths at the injection point, but increasingly prefer minimal paths as the packet proceeds, referred to herein as Increasing Minimal Bias (IMB).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Increasingly minimal bias routing

Bataineh, Abdulla↗

DOE OSTI2020

Increasingly minimal bias routing

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Quantifying impact reduction due to avoidance, minimization and restoration for a natural gas pipeline in the Peruvian Andes

We present monitoring methods and quantitative biodiversity data to document components of the mitigation hierarchy. We estimated avoidance, minimization, restoration and impact reduction in quality hectares for the 25 m wide right of way of a 408 km natural gas buried pipeline that crosses 14 Ecological Landscape Units (ELUs) in the tropical Andes of Peru. We found that applying the mitigation hierarchy as part of a comprehensive biodiversity action plan substantially reduced impacts on biodiversity in all habitats studied. Avoidance and right of way minimization contributed to significant impact reduction. We quantified impact reduction during construction and operation on the right of way of the pipeline over a five-year period and found that restoration was the greatest contributor to reducing impacts. We documented that most ELUs have a positive restoration trajectory. We also documented how monitoring over large scale spatial scales, in combination with site-specific monitoring, generated data for management to determine restoration priorities and impact mitigation. A biodiversity action plan that incorporated the mitigation hierarchy and a science-based biodiversity monitoring and assessment program contributed to biodiversity management of the project and played an important role in minimizing and managing impacts. - Highlights: •Quantitative data for mitigation hierarchy components are presented. •Application of the mitigation hierarchy reduced impacts on biodiversity. •A biodiversity monitoring program provided data to reduce impacts.

03 NATURAL GAS↗

DOE OSTI2024

A novel technique for minimizing energy functional using neural networks

An energy functional describes the equilibrium state of a system. In this work, we present a novel technique, Functional Optimization using Neural Networks (FONN), for minimizing the system’s energy. FONN utilizes neural networks to process information at discrete grid points, considering their interactions with neighboring grid points, to update the state of the system. The training process involves formulating a loss function based on the system’s energy, and with the help of multiple fine-tuning steps, the method employs a progressive energy reduction technique that decreases the energy in multiple steps. FONN’s effectiveness is demonstrated across various problems, including the minimization of the heat and Lyapunov energy. Furthermore, the paper explores the minimization of the elastic bending energy with an area constraint.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Minimizing Energy Consumption from Connected Signalized Intersections by Reinforcement Learning

Explicit energy minimization objectives are often discouraged in signal optimization algorithms due to its negative impact on mobility performance. One potential direction to solve this problem is to provide a balanced objective function to achieve desired mobility with minimized energy consumption. This research developed a reinforcement learning (RL) based control with reward functions considering energy and mobility in a joint manner-a penalty function is introduced for number of stops. Further, we proposed a clustering-based technique to make the state-space finite which is critical for a tractable implementation of the RL algorithm. We implemented the algorithm in a calibrated NG-SIM network within a traffic micro-simulator-PTV VISSIM. With sole focus on energy, we report 47% reduction in energy consumption when compared with existing signal control schemes, however causing a 65.6% increase in system travel time. In contrast, the control strategy focusing on energy minimization with penalty for stops yields 6.7% reduction in energy consumption with 27% increase in system travel time. The developed RL algorithm with a flexible penalty function in the reward will achieve desired energy goals for a network of signalized intersections without compromising on the mobility performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

MO-FG-204-01: Improved Noise Suppression for Dual-Energy CT Through Entropy Minimization

Purpose: In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects contain a limited number of materials, we propose to suppress noise for DECT based on image entropy minimization. An adaptive weighting scheme is employed during noise suppression to improve decomposition accuracy with limited effect on spatial resolution and image texture preservation. Methods: From decomposed images, we first generate a 2D plot of scattered data points, using basis material densities as coordinates. Data points representing the same material generate a highly asymmetric cluster. We orient an axis by minimizing the entropy in a 1D histogram of these points projected onto the axis. To suppress noise, we replace pixel values of decomposed images with center-of-mass values in the direction perpendicular to the optimal axis. To limit errors due to cluster overlap, we weight each data point’s contribution based on its high and low energy CT values and location within the image. The proposed method’s performance is assessed on physical phantom studies. Electron density is used as the quality metric for decomposition accuracy. Our results are compared to those without noise suppression and with a recently developed iterative method. Results: The proposed method reduces noise standard deviations of the decomposed images by at least one order of magnitude. On the Catphan phantom, this method greatly preserves the spatial resolution and texture of the CT images and limits induced error in measured electron density to below 1.2%. In the head phantom study, the proposed method performs the best in retaining fine, intricate structures. Conclusion: The entropy minimization based algorithm with adaptive weighting substantially reduces DECT noise while preserving image spatial resolution and texture. Future investigations will include extensive investigations on material decomposition accuracy that go beyond the current electron density calculations. This work was supported in part by the National Institutes of Health (NIH) under Grant Number R21 EB012700.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2012

Minimal Coordinate Formulation of Contact Dynamics in Operational Space

In recent years, complementarity techniques have been developed for modeling non-smooth contact and collision dynamics problems for multi-link robotic systems. Normally, in this approach, a linear complementarity problem (LCP) is set up using 6n non-minimal coordinates for a system with n links together with all the unilateral constraints and inter-link bilateral constraints on the system. In this paper, we use operational space dynamics to develop a complementarity formulation for contact and collision dynamics that uses minimal coordinates. The use of such non-redundant coordinates results in much smaller size LCP problems and the automatic enforcement of the inter-link bilateral constraints. Furthermore, we exploit operational space low-order computational algorithms to overcome some of the bottlenecks in using minimal coordinates.

contact dynamics↗

NASA NTRS2014

Application of Sequential Quadratic Programming to Minimize Smart Active Flap Rotor Hub Loads

In an analytical study, SMART active flap rotor hub loads have been minimized using nonlinear programming constrained optimization methodology. The recently developed NLPQLP system (Schittkowski, 2010) that employs Sequential Quadratic Programming (SQP) as its core algorithm was embedded into a driver code (NLP10x10) specifically designed to minimize active flap rotor hub loads (Leyland, 2014). Three types of practical constraints on the flap deflections have been considered. To validate the current application, two other optimization methods have been used: i) the standard, linear unconstrained method, and ii) the nonlinear Generalized Reduced Gradient (GRG) method with constraints. The new software code NLP10x10 has been systematically checked out. It has been verified that NLP10x10 is functioning as desired. The following are briefly covered in this paper: relevant optimization theory; implementation of the capability of minimizing a metric of all, or a subset, of the hub loads as well as the capability of using all, or a subset, of the flap harmonics; and finally, solutions for the SMART rotor. The eventual goal is to implement NLP10x10 in a real-time wind tunnel environment.

HUB LOADS↗

NASA NTRS2016

Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

Aeroservoelasticity↗

DOE OSTI2019

Low-Level Waste Minimization and Management Planning at the Western Waste Management Facility, Ontario Power Generation - 19235

The purpose of this study was to examine the strategies intended to mitigate the temporary storage restrictions for Low-Level radioactive waste at the Western Waste Management Facility to enable continued accommodation of waste generation rates, and to recover storage capacity from 2018-2023 to optimize long-term sustainability for radioactive waste management. The management options considered were based on existing waste processing technologies and programs available at the Western Waste Management Facility, in combination with third party volume-reduction services. Completed analysis measured the consumption of Low-Level Waste storage space as influenced by the projected volumes from nuclear generating stations, and the various processing scenarios developed; such as reducing the volume of surplus processable waste on-site, and the reduction of specific waste streams previously considered to be non-processable. Results from the quantitative analysis indicated which strategies will be most effective for minimizing waste volumes for long-term storage and for recovering low-level storage space at the Western Waste Management Facility. The strategic path forward is presented in short- to long-term management objectives. Results from this study will contribute to the waste stream planning and management of major reactor refurbishment projects and to the technological advancements and innovation of radioactive waste processing and minimization. With further understanding of the refurbishment-specific waste types and volumes, it is expected that Nuclear Waste Management and the nuclear generating stations will achieve increasingly improved minimization results with the progression of each refurbished reactor. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Model-dependence of minimal-twist OPEs in d > 2 holographic CFTs

Following recent work on heavy-light correlators in higher-dimensional conformal field theories (CFTs) with a large central charge C T , we clarify the properties of stress tensor composite primary operators of minimal twist, [ T m ], using arguments in both CFT and gravity. We provide an efficient proof that the three-point coupling $\left\langle {\mathcal{O}}_L{\mathcal{O}}_L\left[{T}^m\right]\right\rangle$, where ${\mathcal{O}}_L$ is any light primary operator, is independent of the purely gravitational action. Next, we consider corrections to this coupling due to additional interactions in AdS effective field theory and the corresponding dual CFT. When the CFT contains a non-zero three-point coupling $\left\langle TT{\mathcal{O}}_L\right\rangle$, the three-point coupling $\left\langle {\mathcal{O}}_L{\mathcal{O}}_L\left[{T}^2\right]\right\rangle$ is modified at large C T if $\left\langle TT{\mathcal{O}}_L\right\rangle \sim \sqrt{C_T}$. This scaling is obeyed by the dilaton, by Kaluza-Klein modes of prototypical supergravity compactifications, and by scalars in stress tensor multiplets of supersymmetric CFTs. Quartic derivative interactions involving the graviton and the light probe field dual to ${\mathcal{O}}_L $ can also modify the minimal-twist couplings; these local interactions may be generated by integrating out a spin- ℓ ≥ 2 bulk field at tree level, or any spin ℓ at loop level. These results show how the minimal-twist OPE coefficients can depend on the higher-spin gap scale, even perturbatively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Convex Programs for Minimal-Area Problems

The minimal-area problem that defines string diagrams in closed string field theory asks for the metric of least area on a Riemann surface with the condition that all non-contractible closed curves have length at least 2π. This is an extremal length problem in conformal geometry as well as a problem in systolic geometry. Here, we consider the analogous minimal-area problem for homology classes of curves and, with the aid of calibrations and the max flow-min cut theorem, formulate it as a local convex program. We derive an equivalent dual program involving maximization of a concave functional. These two programs give new insights into the form of the minimal-area metric and are amenable to numerical solution. We explain how the homology problem can be modified to provide the solution to the original homotopy problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Minimal-Area Metrics on the Swiss Cross and Punctured Torus

The closed string theory minimal-area problem asks for the conformal metric of least area on a Riemann surface with the condition that all non-contractible closed curves have length greater than or equal to an arbitrary constant that can be set to one. Through every point in such a metric there is a geodesic that saturates the length condition, and the saturating geodesics in a given homotopy class form a band. The extremal metric is unknown when bands of geodesics cross, as it happens for surfaces of non-zero genus. Here, we use recently proposed convex programs to numerically find the minimal-area metric on the square torus with a square boundary, for various sizes of the boundary. For large enough boundary the problem is equivalent to the “Swiss cross” challenge posed by Strebel. We find that the metric is positively curved in the two-band region and flat in the single-band regions. For small boundary the metric develops a third band of geodesics wrapping around it, and has both regions of positive and of negative curvature. This surface can be completed to provide the minimal-area metric on a once-punctured torus, representing a closed-string tadpole diagram.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Energy levels of one-dimensional systems satisfying the minimal length uncertainty relation

The standard approach to calculating the energy levels for quantum systems satisfying the minimal length uncertainty relation is to solve an eigenvalue problem involving a fourth- or higher-order differential equation in quasiposition space. It is shown that the problem can be reformulated so that the energy levels of these systems can be obtained by solving only a second-order quasiposition eigenvalue equation. Through this formulation the energy levels are calculated for the following potentials: particle in a box, harmonic oscillator, Pöschl–Teller well, Gaussian well, and double-Gaussian well. For the particle in a box, the second-order quasiposition eigenvalue equation is a second-order differential equation with constant coefficients. For the harmonic oscillator, Pöschl–Teller well, Gaussian well, and double-Gaussian well, a method that involves using Wronskians has been used to solve the second-order quasiposition eigenvalue equation. It is observed for all of these quantum systems that the introduction of a nonzero minimal length uncertainty induces a positive shift in the energy levels. It is shown that the calculation of energy levels in systems satisfying the minimal length uncertainty relation is not limited to a small number of problems like particle in a box and the harmonic oscillator but can be extended to a wider class of problems involving potentials such as the Pöschl–Teller and Gaussian wells.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Collective motion in prolate γ-rigid nuclei within minimal length concept via a quantum perturbation method

Based on the minimal length concept, inspired by Heisenberg algebra, a closed analytical formula is derived for the energy spectrum of the prolate γ-rigid Bohr–Mottelson Hamiltonian of nuclei, within a quantum perturbation method (QPM), by considering a scaled Davidson potential in β shape variable. In the resulting solution, called X(3)-D-ML, the ground state and the first β-band are all studied as a function of the free parameters. The fact of introducing the minimal length concept with a QPM makes the model very flexible and a powerful approach to describe nuclear collective excitations of a variety of vibrational-like nuclei. The introduction of scaling parameters in the Davidson potential enables us to get a physical minimum of this latter in comparison with previous works. The analysis of the corrected wave function, as well as the probability density distribution, shows that the minimal length parameter has a physical upper bound limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

The R35 residue of the influenza A virus NS1 protein has minimal effects on nuclear localization but alters virus replication through disrupting protein dimerization

The influenza A virus NS1 protein has a nuclear localization sequence (NLS) in the amino terminal region. This NLS overlaps sequences that are important for RNA binding as well as protein dimerization. To assess the significance of the NS1 NLS on influenza virus replication, the NLS amino acids were individually mutated to alanines and recombinant viruses encoding these mutations were rescued. Viruses containing NS1 proteins with mutations at R37, R38 and K41 displayed minimal changes in replication or NS1 protein nuclear localization. Recombinant viruses encoding NS1 R35A were not recovered but viruses containing second site mutations at position D39 in addition to the R35A mutation were isolated. The mutations at position 39 were shown to partially restore NS1 protein dimerization but had minimal effects on nuclear localization. These data indicate that the amino acids in the NS1 NLS region play a more important role in protein dimerization compared to nuclear localization. - Highlights: • Mutations were introduced into influenza NS1 NLS1. • NS1 R37A, R38A, K41A viruses had minimal changes in replication and NS1 localization. • Viruses from NS1 R35A rescue all contained additional mutations at D39. • NS1 R35A D39X mutations recover dimerization lost in NS1 R35A mutations. • These results reaffirm the importance of dimerization for NS1 protein function.

60 APPLIED LIFE SCIENCES↗