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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Flight Test Results of a GPS-Based Pitot-Static Calibration Method Using Output-Error Optimization for a Light Twin-Engine Airplane

As part of the NASA Aviation Safety Program (AvSP), a novel pitot-static calibration method was developed to allow rapid in-flight calibration for subscale aircraft while flying within confined test areas. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. This method has been demonstrated in subscale flight tests and has shown small 2- error bounds with significant reduction in test time compared to other methods. The current research was motivated by the desire to further evaluate and develop this method for full-scale aircraft. A goal of this research was to develop an accurate calibration method that enables reductions in test equipment and flight time, thus reducing costs. The approach involved analysis of data acquisition requirements, development of efficient flight patterns, and analysis of pressure error models based on system identification methods. Flight tests were conducted at The University of Tennessee Space Institute (UTSI) utilizing an instrumented Piper Navajo research aircraft. In addition, the UTSI engineering flight simulator was used to investigate test maneuver requirements and handling qualities issues associated with this technique. This paper provides a summary of piloted simulation and flight test results that illustrates the performance and capabilities of the NASA calibration method. Discussion of maneuver requirements and data analysis methods is included as well as recommendations for piloting technique.

Martos, Borja↗
DOE OSTI2016

Poster - 19: Investigation of Electron Reference Dosimetry Based on Optimal Chamber Shift

An addendum/revision to AAPM TG-51 electron reference dosimetry is highly expected to meet the clinical requirement with the increasing usage of new ion chambers not covered in TG-51. A recent study, Med. Phys. 41, 111701, proposed a new fitting equation for the beam quality conversion factor k’{sub Q} to a wide spectrum of chambers. In the study, an optimal Effective Point of Measurement (EPOM) from Monte Carlo calculations was recommended and the fitting parameters to k’{sub Q} was based on it. We investigated the absolute dose obtained based on the optimal EPOM method and the original TG-51 method with k’{sub R50} determined differently. The results showed that using the Markus curve is a better choice than the well-guarded chamber fitting for an IBA PPC-05 parallel plate chamber if we need to strictly follow the AAPM TG-51 protocol. We also examined the usage of the new fitting equation with measurement performed at the physical EPOM, instead of the optimal EPOM. The former is more readily determined and more practical in clinics. Our study indicated that the k’{sub Q} fitting based on the optimal EPOM can be used to measurement at the physical EPOM with no significant clinical impact. The inclusion of Farmer chamber gradient correction P{sub gr} in k’{sub Q}, as in the mentioned study, asks for the precise positioning of chamber center at dref. It is not recommended in clinics to avoid over-correction for low electron energies, especially for an institute having matching Linacs implemented.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

An optimization‐based phase‐field method for continuous‐discontinuous crack propagation

Summary A new continuous‐discontinuous strategy for the computational modeling of crack propagation within the context of phase‐field models of fracture is presented. The method is designed to introduce and update a sharp crack surface within an evolving damage band and to enhance the kinematics of the finite element approximation accordingly. The proposed approach relies on three key elements. First, we propose the use of a crack length functional to provide a trigger for initiating a continuous to discontinuous transition. Next, the crack path identification is addressed by introducing the concept of an auxiliary damage field that varies with an extension of the sharp crack surface. The sharp crack surface is extended through an optimization algorithm, in which the difference between the auxiliary field and the actual damage field stemming from the phase‐field framework is minimized. Finally, a strong discontinuity is inserted in the wake of the diffuse crack tip with the extended finite element method, completing the continuous to discontinuous transition. Several benchmark problems in two‐dimensional quasi‐static fracture mechanics are presented to demonstrate the accuracy and robustness of the method.

Geelen, Rudy J. M.↗
DOE OSTI2018

Classical Optimal Control for Energy Minimization Based On Diffeomorphic Modulation under Observable-Response-Preserving Homotopy

In this work, we introduce the so-called “Classical Optimal Control Optimization” (COCO) method for global energy minimization based on the implementation of the diffeomorphic modulation under observable-response-preserving homotopy (DMORPH) gradient algorithm. A probe particle with time-dependent mass $m(t;β)$ and dipole $μ(r,t;β)$ is evolved classically on the potential energy surface $V(r)$ coupled to an electric field $E(t;β)$, as described by the time-dependent density of states represented on a grid, or otherwise as a linear combination of Gaussians generated by the k-means clustering algorithm. Control parameters $β$ defining $m(t;β), μ(r,t;β),$ and $E(t;β)$ are optimized by following the gradients of the energy with respect to $β,$ adapting them to steer the particle toward the global minimum energy configuration. We find that the resulting COCO algorithm is capable of resolving near-degenerate states separated by large energy barriers and successfully locates the global minima of golf potentials on flat and rugged surfaces, previously explored for testing quantum annealing methodologies and the quantum optimal control optimization (QuOCO) method. Preliminary results show successful energy minimization of multidimensional Lennard-Jones clusters. Beyond the analysis of energy minimization in the specific model systems investigated, we anticipate COCO should be valuable for solving minimization problems in general, including optimization of parameters in applications to machine learning and molecular structure determination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Method and system for providing flexible reserve power for power grid

An optimization-based method and system is disclosed to enable heterogeneous loads and distributed energy resources (DERs) to participate in grid ancillary services, such as spinning and non-spinning reserves, and ramping reserves. The method includes receiving inputs for decision parameters for optimizing an objective for obtaining flexible reserve power, solving the objective for obtaining flexible reserve power, determining a reserve power schedule for a prediction horizon for providing flexible reserve power based on the objective, generating a service bid based on the reserve power schedule for the power grid; and when the service bid is accepted, providing flexible reserve power to the power grid based on the service bid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Efficiency Calibration of 4{pi} NaI(Tl) Gamma-ray Detectors for Plane Sources - Paper 130

4{pi} NaI(Tl) detectors are useful for low level gamma activity measurements due to the near 4{pi} solid angle that can be obtained with them. An analytical theoretical approach is presented here to calculate the absolute efficiencies for this type of detectors. The approach depends on the accurate calculation of two important factors; the path length, d, the photon traverses within the active volume of a gamma detector, and the geometrical solid angle,{Omega}, subtended by the source to the detector at the point of entrance. These two factors are theoretically derived through a straightforward analytical approach. In this work, this model is extended to an isotropic radiating point source, and a thin circular disk source. The results of the present absolute efficiency values were compared with the experimental and M.C. method works reported in the literature. The present theoretical and the experimental efficiency values are in good agreement. The present approach offers a good method to calibrate 4{pi} NaI(Tl) detectors over a large energy range without the need for standard sources, as is the case for experimental methods, nor optimization of detector parameters as for Monte Carlo simulations. Discrepancies with experimental results are reduced to lower than 4%. (author)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1987

A study of methods to predict and measure the transmission of sound through the walls of light aircraft. Numerical method for analyzing the optimal performance of active noise controllers

An optimal active noise controller is formulated and analyzed for three different active noise control problems. The first problem formulated is the active control of enclosed or partially enclosed harmonic sound fields where the noise source strengths and enclosure boundary description are known. The enclosure boundary is described by either pressure, velocity, or impedance boundary conditions. The second problem formulated is the active control of the free field power radiated from a distributed noise source with a known time harmonic surface velocity. The third problem formulated is the active control of enclosed or partially enclosed harmonic sound field where the noise source strengths of enclosure boundary description may not be known. All three formulations are derived using an indirect boundary element technique. Formulation and verification of an indirect boundary element method is presented. The active noise controller formulations for enclosures are capable of analyzing systems with generalized enclosure shapes, point noise sources, and/or locally reacting impedance boundary conditions. For each formulation, representative results of optimal active noise controller case studies are presented, and some general conclusions are drawn.

Mollo, Christopher G.↗
NASA NTRS1987

The application of quadratic optimal cooperative control synthesis to a CH-47 helicopter

A control-system design method, quadratic optimal cooperative control synthesis (CCS), is applied to the design of a stability and control augmentation system (SCAS). The CCS design method is different from other design methods in that it does not require detailed a priori design criteria, but instead relies on an explicit optimal pilot-model to create desired performance. The design method, which was developed previously for fixed-wing aircraft, is simplified and modified for application to a Boeing CH-47 helicopter. Two SCAS designs are developed using the CCS design methodology. The resulting CCS designs are then compared with designs obtained using classical/frequency-domain methods and linear quadratic regulator (LQR) theory in a piloted fixed-base simulation. Results indicate that the CCS method, with slight modifications, can be used to produce controller designs which compare favorably with the frequency-domain approach.

Townsend, Barbara K.↗
DOE OSTI2025

Fermilab Automation of Coil Winding System

The automated coil winder project creates a repeatable, scalable method for producing superconducting magnet coils with increased accuracy and efficiency. The design uses an ortho cyclic winding method to achieve high fill factors by combining computer numerical control (CNC), microcontroller-based controls, and sophisticated optimization techniques. The method optimizes coil turns, core geometry, and current consumption by utilizing analytical models based on magnetic moment, Ohm’s law, and power constraints. For particle accelerator applications, prototype testing using a 3D-printed coil winder has shown enhanced winding repeatability, thermal management, and manufacturability.

Dzida, Rafal [Northern Illinois U.]↗
NASA NTRS2016

Method and Apparatus for Performance Optimization Through Physical Perturbation of Task Elements

The invention is an apparatus and method of biofeedback training for attaining a physiological state optimally consistent with the successful performance of a task, wherein the probability of successfully completing the task is made is inversely proportional to a physiological difference value, computed as the absolute value of the difference between at least one physiological signal optimally consistent with the successful performance of the task and at least one corresponding measured physiological signal of a trainee performing the task. The probability of successfully completing the task is made inversely proportional to the physiological difference value by making one or more measurable physical attributes of the environment in which the task is performed, and upon which completion of the task depends, vary in inverse proportion to the physiological difference value.

Prinzel, Lawrence J., III↗
DOE OSTI2023

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

Theoretical Foundation of Copernicus: A Unified System for Trajectory Design and Optimization

The fundamental methods are described for the general spacecraft trajectory design and optimization software system called Copernicus. The methods rely on a unified framework that is used to model, design, and optimize spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The trajectory model, with its associated equations of motion and maneuver models, are discussed.

Ocampo, Cesar↗
DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗
DOE OSTI2014

SU-E-T-367: Optimization of DLG Using TG-119 Test Cases and a Weighted Mean Approach

Purpose: Optimization of the dosimetric leaf gap (DLG) is an important step in commissioning the Eclipse treatment planning system for sliding window intensity-modulated radiation therapy (SW-IMRT) and RapidArc. Often the values needed for optimal dose delivery differ markedly from those measured at commissioning. We present a method to optimize this value using the AAPM TG-119 test cases. Methods: For SW-IMRT and RapidArc, TG-119 based test plans were created using a water-equivalent phantom. Dose distributions measured on film and ion chamber (IC) readings taken in low-gradient regions within the targets were analyzed separately. Since DLG is a single value per energy, SW-IMRT and RapidArc must be considered simultaneously. Plans were recalculated using a linear sweep from 0.02cm (the minimum DLG) to 0.3 cm. The calculated point doses were compared to the measured doses for each plan, and based on these comparisons an optimal DLG value was computed for each plan. TG-119 cases are designed to push the system in various ways, thus, a weighted mean of the DLG was computed where the relative importance of each type of plan was given a score from 0.0 to 1.0. Finally, SW-IMRT and RapidArc are assigned an overall weight based on clinical utilization. Our routine patient-QA (PQA) process was performed as independent validation. Results: For a Varian TrueBeam, the optimized DLG varied with σ = 0.044cm for SW-IMRT and σ = 0.035cm for RapidArc. The difference between the weighted mean SW-IMRT and RapidArc value was 0.038cm. We predicted utilization of 25% SW-IMRT and 75% RapidArc. The resulting DLG was ~1mm different than that found by commissioning and produced an average error of <1% for SW-IMRT and RapidArc PQA test cases separately. Conclusion: The weighted mean method presented is a useful tool for determining an optimal DLG value for commissioning Eclipse.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Robust Trajectory Optimization Techniques Using a Sweeping Gradient Method and Linear Covariance Analysis

We present robust trajectory optimization techniques using a sweeping gradient method for ordinary differential equations with events (SGM) and linear covariance analysis (LinCov). SGM is a method for computing the gradient of trajectory analyses defined by performance indices over initial value problems with events with respect to static parameters. LinCov is an analytic technique for predicting stochastic behavior of dynamical systems. By combining SGM and LinCov, it is possible use efficient, off-the-shelf, gradient-based optimizers to solve robust optimal trajectory design problems. We describe the individual methods and some details on how they can be combined. Then we apply the combined techniques to a variety of orbital trajectory design problems to demonstrate its use, including minimum fuel transfer and mid-course correction burn scheduling.

Benjamin W L Margolis↗
DOE OSTI2014

System and method of cylinder deactivation for optimal engine torque-speed map operation

This disclosure provides a system and method for determining cylinder deactivation in a vehicle engine to optimize fuel consumption while providing the desired or demanded power. In one aspect, data indicative of terrain variation is utilized in determining a vehicle target operating state. An optimal active cylinder distribution and corresponding fueling is determined from a recommendation from a supervisory agent monitoring the operating state of the vehicle of a subset of the total number of cylinders, and a determination as to which number of cylinders provides the optimal fuel consumption. Once the optimal cylinder number is determined, a transmission gear shift recommendation is provided in view of the determined active cylinder distribution and target operating state.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

SU-E-T-258: Parallel Optimization of Beam Configurations for CyberKnife Treatments

Purpose: The CyberKnife delivers a large number of beams originating at different non-planar positions and with different orientation. We study how much the quality of treatment plans depends on the beams considered during plan optimization. Particularly, we evaluate a new approach to search for optimal treatment plans in parallel by running optimization steps concurrently. Methods: So far, no deterministic, complete and efficient method to select the optimal beam configuration for robotic SRS/SBRT is known. Considering a large candidate beam set increases the likelihood to achieve a good plan, but the optimization problem becomes large and impractical to solve. We have implemented an approach that parallelizes the search by solving multiple linear programming problems concurrently while iteratively resampling zero weighted beams. Each optimization problem contains the same set of constraints but different variables representing candidate beams. The search is synchronized by sharing the resulting basis variables among the parallel optimizations. We demonstrate the utility of the approach based on an actual spinal case with the objective to improve the coverage. Results: The objective function is falling and reaches a value of 5000 after 49, 31, 25 and 15 iterations for 1, 2, 4, and 8 parallel processes. This corresponds to approximately 97% coverage in 77%, 59%, and 36% of the mean number of iterations with one process for 2, 4, and 8 parallel processes, respectively. Overall, coverage increases from approximately 91.5% to approximately 98.5%. Conclusion: While on our current computer with uniform memory access the reduced number of iterations does not translate into a similar speedup, the approach illustrates how to effectively parallelize the search for the optimal beam configuration. The experimental results also indicate that for complex geometries the beam selection is critical for further plan optimization.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

TAS: 89 0227: TAS Recovery Act - Optimization and Control of Electric Power Systems: ARRA

The name SuperOPF is used to refer several projects, problem formulations and soft-ware tools intended to extend, improve and re-define some of the standard methods of optimizing electric power systems. Our work included applying primal-dual interior point methods to standard AC optimal power flow problems of large size, as well as extensions of this problem to include co-optimization of multiple scenarios. The original SuperOPF problem formulation was based on co-optimizing a base scenario along with multiple post-contingency scenarios, where all AC power flow models and constraints are enforced for each, to find optimal energy contracts, endogenously determined locational reserves and appropriate nodal energy prices for a single period optimal power flow problem with uncertainty. This led to example non-linear programming problems on the order of 1 million constraints and half a million variables. The second generation SuperOPF formulation extends this by adding multiple periods and multiple base scenarios per period. It also incorporates additional variables and constraints to model load following reserves, ramping costs, and storage resources. A third generation of the multi-period SuperOPF, adds both integer variables and a receding horizon framework in which the problem type is more challenging (mixed integer), the size is even larger, and it must be solved more frequently, pushing the limits of currently available algorithms and solvers. The consideration of transient stability constraints in optimal power flow (OPF) problems has become increasingly important in modern power systems. Transient stability constrained OPF (TSCOPF) is a nonlinear optimization problem subject to a set of algebraic and differential equations. Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an optimization problem, (ii) the lack of a true analytical expression for transient stability in OPF. To handle the dynamics in TSCOPF, the set of differential equations can be approximated or converted into equivalent algebraic equations before they are included in an OPF formulation. In Chapter 4, a rigorous evaluation of using a predefined and fixed threshold for rotor angles as a mean to determine transient stability of the system is developed. TSCOPF can be modeled as a large-scale nonlinear programming problem including the constraints of differential-algebraic equations (DAE). Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an optimization problem, (ii) the lack of a true analytical expression for transient stability constraint in OPF. Unfortunately, even the current best TSCOPF solvers still suffer from the curse of dimensionality and unacceptable computational time, especially for large-scale power systems with multiple contingencies. In chapter 5, thse issues will be addressed and a new method to incorporate the transient stability constraints will be presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗