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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Optimized anion exchange column isolation of zirconium-89 (89Zr) from yttrium cyclotron target: Method development and implementation on an automated fluidic platform

Zirconium-89 (89Zr), produced by the (p,n) reaction from naturally monoisotopic yttrium (natY), is a promising positron emitting isotope for immunoPET imaging. Its long half-life of 78.4 h is sufficient for evaluating slow physiological processes. A prototype automated fluidic system, coupled to on-line and in-line detectors, has been constructed to facilitate development of new 89Zr purification methodologies. The highly reproducible reagent delivery platform and near-real time monitoring of column effluents allows for efficient method optimization. The separation of Zr from dissolved Y metal targets was evaluated using several anion exchange resins. Each resin was evaluated against its ability to quantitatively capture Zr from a load solution that is high in dissolved Y. The most appropriate anion exchange resin for this application was identified, and the separation method was optimized. The method is capable of a high Y decontamination factor (>105) and has been shown to separate Fe, an abundant contaminant in Y foils, from the 89Zr elution fraction. Finally, the performance of the method was evaluated using cyclotron bombarded Y foil targets. The separation method was shown to achieve >95% recovery of the 89Zr present in the foils. The 89Zr eluent, however, was in a chemical matrix not immediately conducive to labeling onto proteins. The main intent of this study was to develop a tandem column 89Zr purification process, wherein the anion exchange column method described here is the first separation in a dual-column purification process.

Zirconium-89, ImmunoPET, medical isotope, automati↗
NASA NTRS1994

Comparison of transform coding methods with an optimal predictor for the data compression of digital elevation models

Statistical encoding techniques enable the reduction of the number of bits required to encode a set of symbols, and are derived from their probabilities. Huffman encoding is an example of statistical encoding that has been used for error-free data compression. The degree of compression given by Huffman encoding in this application can be improved by the use of prediction methods. These replace the set of elevations by a set of corrections that have a more advantageous probability distribution. In particular, the method of Lagrange Multipliers for minimization of the mean square error has been applied to local geometrical predictors. Using this technique, an 8-point predictor achieved about a 7 percent improvement over an existing simple triangular predictor.

Lewis, Michael↗
DOE OSTI2015

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T{sub d} less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value = 0.08). Conclusions: Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

A technique for integrating engine cycle and aircraft configuration optimization

A method for conceptual aircraft design that incorporates the optimization of major engine design variables for a variety of cycle types was developed. The methodology should improve the lengthy screening process currently involved in selecting an appropriate engine cycle for a given application or mission. The new capability will allow environmental concerns such as airport noise and emissions to be addressed early in the design process. The ability to rapidly perform optimization and parametric variations using both engine cycle and aircraft design variables, and to see the impact on the aircraft, should provide insight and guidance for more detailed studies. A brief description of the aircraft performance and mission analysis program and the engine cycle analysis program that were used is given. A new method of predicting propulsion system weight and dimensions using thermodynamic cycle data, preliminary design, and semi-empirical techniques is introduced. Propulsion system performance and weights data generated by the program are compared with industry data and data generated using well established codes. The ability of the optimization techniques to locate an optimum is demonstrated and some of the problems that had to be solved to accomplish this are illustrated. Results from the application of the program to the analysis of three supersonic transport concepts installed with mixed flow turbofans are presented. The results from the application to a Mach 2.4, 5000 n.mi. transport indicate that the optimum bypass ratio is near 0.45 with less than 1 percent variation in minimum gross weight for bypass ratios ranging from 0.3 to 0.6. In the final application of the program, a low sonic boom fix a takeoff gross weight concept that would fly at Mach 2.0 overwater and at Mach 1.6 overland is compared with a baseline concept of the same takeoff gross weight that would fly Mach 2.4 overwater and subsonically overland. The results indicate that for the design mission, the low boom concept has a 5 percent total range penalty relative to the baseline. Additional cycles were optimized for various design overland distances and the effect of flying off-design overland distances is illustrated.

Geiselhart, Karl A.↗
DOE OSTI2017

Trip optimization system and method for a train

A system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives, the system including a locator element to determine a location of the train, a track characterization element to provide information about a track, a sensor for measuring an operating condition of the locomotive consist, a processor operable to receive information from the locator element, the track characterizing element, and the sensor, and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train.

42 ENGINEERING↗
NASA NTRS1972

Optimal and suboptimal methods of satellite surveillance for traffic control of transoceanic flights.

Description of a system which uses two synchronous equatorial satellites. Aircraft location is determined by measuring the range of the aircraft to each satellite as well as aircraft altitude, and transmitting this information periodically to a ground station. There, the aircraft's geographic position at the time of transmission is computed. This information is then combined with past position measurements in a suboptimal filter to determine aircraft position and velocity (the velocity being used to estimate aircraft position between transmissions). The suboptimal filter is a simplification of the optimal Kalman filter. Except for altitude information, the system is independent of the aircraft navigation system.

Winter, H.↗
DOE OSTI2022

A method for determining optimal electric range by considering electric vehicle lightweighting on perceived ownership cost

The limited driving range due to high costs and low energy densities of batteries constraints the battery electric vehicle (BEV) market growth. Lightweighting in theory can reduce energy consumption rate and extend the driving range. The knowledge gap is to quantitatively link the cost-effectiveness of light-weight technologies with range extension and consumer acceptance of BEVs. In this study, a physics-based energy consumption model of BEVs is constructed and associated with a statistics-based model on the basis of travel surveys. A perceived cost of ownership (PCO) is then developed by adding intangible costs to traditional total cost of ownership models. We estimate, at the disaggregate vehicle model and driver level and the aggregate market level, 1) the extended range due to lightweighting for a given battery size; and 2) the optimal electric range based on lightweighting decisions. The cost-effectiveness of lightweighting for BEV range extension is found to vary with income-dependent daily range limitation value, driving patterns and lightweighting technology costs. In general, adopting lightweighting in BEVs is more cost-effective for consumers with higher daily limitation value, as well as for those with higher driving intensity or suitable daily driving patterns. When the lightweighting involves a higher vehicle production cost, less lightweighting could reduce the overall PCO for BEV owners. 4 of the selected top ten BEV models are found to benefit from additional 2.09%–4.45% lightweighting. Finally, the method built in this study can guide automakers in planning R&D investments in battery and lightweighting technologies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints

The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective function and deterministic constraints. Our main contribution is combining the augmented Lagrangian framework with adaptive sampling, resulting in an efficient optimization methodology validated with practical examples. To achieve the presented efficiency, here we consider inexact solutions for the augmented Lagrangian subproblems, and through an adaptive sampling mechanism, we control the variance in the gradient estimates. Furthermore, we analyze the theoretical performance of the proposed scheme by showing equivalence to a gradient descent algorithm on a Moreau envelope function, and we prove sublinear convergence for convex objectives and linear convergence for strongly convex objectives with affine equality constraints. The worst-case sample complexity of the resulting algorithm, for an arbitrary choice of penalty parameter in the augmented Lagrangian function, is $\mathscr{O}$(ϵ -3-δ ) , where ϵ > 0 is the expected error of the solution and δ > 0 is a user-defined parameter. If the penalty parameter is chosen to be $\mathscr{O}$(ϵ -1 ), we demonstrate that the result can be improved to $\mathscr{O}$(ϵ -2 ) , which is competitive with the other methods employed in the literature. Moreover, if the objective function is strongly convex with affine equality constraints, we obtain $\mathscr{O}$(ϵ -1 log(1/ϵ)) complexity. Finally, we empirically verify the performance of our adaptive sampling augmented Lagrangian framework in machine learning optimization and engineering design problems, including topology optimization of a heat sink with environmental uncertainty.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Level Set Topology Optimization of Load Carrying Heat Dissipation Devices

In this paper, we introduce a level set method topology optimization method of structures subjected to coupled mechanical and thermal loads. Different examples considering compliance minimization and stress minimization under temperature and volume constraints, and mass minimization under stress and temperature constraints, are presented. The p-norm of the stress field and temperature field is used to approximate the maximum stress and temperature, respectively. The developed method is applied in the design of an L-bracket and a battery package. The results show that designs obtained by ignoring the thermal or structural constraints can result in high values of temperature or stress, respectively.

Kambampati, Sandilya↗
NASA NTRS1975

A steepest descents method for reentry optimization

A steepest descents optimization program is applied to the problem of a lifting vehicle entering the earth's atmosphere. The program employs penalty functions representing terminal conditions and inflight inequality constraints. During each iteration, it reduces a single performance measure which is the sum of the performance index and the penalty functions. Therefore, only one set of adjoint equations must be integrated per iteration. Values of weight factors, multiplying the penalty functions, are automatically adjusted before each iteration in order that the penalty functions will approach acceptable values. This method is shown to be a form of the classical Lagrange multiplier methods.

Andrus, J. F.↗
NASA NTRS1983

Separation of time scales in aircraft trajectory optimization

Two methods for analyzing the time-scale properties of aircraft trajectory optimization problems are presented. Time-scale properties must be identified before solutions can be obtained by using singular perturbation methods. Both methods only require a knowledge of the state equations, the aircraft characteristics, and the bounds on the state and control variables. Although these methods give only rough estimates of time-scale separation, they do not require that an 'exact' optimal trajectory be known, as do the more rigorous methods, and they are an improvement on the ad hoc methods currently in use. The two methods are applied to an example problem for a high performance aircraft.

Ardema, M. D.↗
NASA NTRS1995

Implementation of a multiblock sensitivity analysis method in numerical aerodynamic shape optimization

A multiblock sensitivity analysis method is applied in a numerical aerodynamic shape optimization technique. The Sensitivity Analysis Domain Decomposition (SADD) scheme which is implemented in this study was developed to reduce the computer memory requirements resulting from the aerodynamic sensitivity analysis equations. Discrete sensitivity analysis offers the ability to compute quasi-analytical derivatives in a more efficient manner than traditional finite-difference methods, which tend to be computationally expensive and prone to inaccuracies. The direct optimization procedure couples CFD analysis based on the two-dimensional thin-layer Navier-Stokes equations with a gradient-based numerical optimization technique. The linking mechanism is the sensitivity equation derived from the CFD discretized flow equations, recast in adjoint form, and solved using direct matrix inversion techniques. This investigation is performed to demonstrate an aerodynamic shape optimization technique on a multiblock domain and its applicability to complex geometries. The objectives are accomplished by shape optimizing two aerodynamic configurations. First, the shape optimization of a transonic airfoil is performed to investigate the behavior of the method in highly nonlinear flows and the effect of different grid blocking strategies on the procedure. Secondly, shape optimization of a two-element configuration in subsonic flow is completed. Cases are presented for this configuration to demonstrate the effect of simultaneously reshaping interfering elements. The aerodynamic shape optimization is shown to produce supercritical type airfoils in the transonic flow from an initially symmetric airfoil. Multiblocking effects the path of optimization while providing similar results at the conclusion. Simultaneous reshaping of elements is shown to be more effective than individual element reshaping due to the inclusion of mutual interference effects.

Lacasse, James M.↗
DOE OSTI2021

Using projection operators with maximum overlap methods to simplify challenging self-consistent field optimization

Maximum overlap methods are effective tools for optimizing challenging ground- and excited-state wave functions using self-consistent field models such as Hartree-Fock and Kohn-Sham density functional theory. Nevertheless, such models have shown significant sensitivity to the user-defined initial guess of the target wave function. Here in this work, a projection operator framework is defined and used to provide a metric for non-aufbau orbital selection in maximum-overlap-methods. The resulting algorithms, termed the Projection-based Maximum Overlap Method (PMOM) and Projection-based Initial Maximum Overlap Method (PIMOM), are shown to perform exceptionally well when using simple user-defined target solutions based on occupied/virtual molecular orbital permutations. This work also presents a new metric that provides a simple and conceptually convenient measure of agreement between the desired target and the current or final SCF results during a calculation employing a maximum-overlap method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Instrument design optimization with computational methods

Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q wea k experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.

43 PARTICLE ACCELERATORS↗
NASA NTRS2015

An Analytical Solution for Yaw Maneuver Optimization on the International Space Station and Other Orbiting Space Vehicles

This paper presents a new method for optimizing yaw maneuvers, which are the most common large maneuvers on the International Space Station (ISS). The goal of the maneuver optimization is to find a maneuver trajectory with minimal torques acting on the vehicle during the maneuver. Therefore, the thruster firings necessary to perform the maneuver are minimized. Reduction of thruster firings saves propellant and decreases structural loads and contamination of the vehicle critical elements, thus saving the service life of the thrusters and the vehicle itself. Equations describing the pitch and roll motion needed to counteract the major torques during a yaw maneuver are obtained. Also, a yaw rate profile is suggested. In the obtained optimized case, the torques are significantly reduced. The proposed approximate analytical solution does not require extensive computer resources and, therefore, can be implemented using software onboard the ISS. As a result, the maneuver execution will be automatic. This is one of the major benefits of the simplified solution presented in this paper with respect to existing computational approaches. The suggested maneuver optimization method can be used not only for the ISS, but for other space vehicles as well.

Dobrinskaya, Tatiana↗
DOE OSTI2014

Hierarchy of model Kohn–Sham potentials for orbital-dependent functionals: A practical alternative to the optimized effective potential method

We describe a method for constructing a hierarchy of model potentials approximating the functional derivative of a given orbital-dependent exchange-correlation functional with respect to electron density. Each model is derived by assuming a particular relationship between the self-consistent solutions of Kohn–Sham (KS) and generalized Kohn–Sham (GKS) equations for the same functional. In the KS scheme, the functional is differentiated with respect to density, in the GKS scheme—with respect to orbitals. The lowest-level approximation is the orbital-averaged effective potential (OAEP) built with the GKS orbitals. The second-level approximation, termed the orbital-consistent effective potential (OCEP), is based on the assumption that the KS and GKS orbitals are the same. It has the form of the OAEP plus a correction term. The highest-level approximation is the density-consistent effective potential (DCEP), derived under the assumption that the KS and GKS electron densities are equal. The analytic expression for a DCEP is the OCEP formula augmented with kinetic-energy-density-dependent terms. In the case of exact-exchange functional, the OAEP is the Slater potential, the OCEP is roughly equivalent to the localized Hartree–Fock approximation and related models, and the DCEP is practically indistinguishable from the true optimized effective potential for exact exchange. All three levels of the proposed hierarchy require solutions of the GKS equations as input and have the same affordable computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

On optimizing Jacobi–Davidson method for calculating eigenvalues in low dimensional structures using eight band k · p model

The paper presents two ways of improving the Jacobi–Davidson method for calculating the eigenvalues and eigenvectors described by eight-band k · p model for quantum dots and other low dimensional structures. First, the method is extended by the application of time reversal symmetry operator. This extension allows efficient calculations of the twofold degeneracy present in the multiband k · p model and other interior eigenvalues. Second, the preconditioner for the indefinite matrix which comes from the discretization of the eight band k · p Hamiltonian is presented. The construction of this preconditioner is based on physical considerations about energy band structure in the k · p model. On the basis of two real examples, it is shown that the preconditioner can significantly shorten the time needed to calculate the interior eigenvalues, despite the fact that the memory usage of the preconditioner and Hamiltionian is comparable. Finally, some technical details for implementing the eight band k · p Hamiltonian and the eigensolver are provided.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

TU-E-213-03: Tools for Ensuring Quality and Safety

Purpose: To develop the first 4D robust optimization (RO) method accounting for respiratory motion and evaluate its potential to improve plan robustness and optimality compared to 3D RO and PTV-based optimization. Methods: A set of 4D CT images are used to track respiratory motion and deformation of tumors and organs. For each of 10 respiration phases, dose distributions for nine different uncertainty scenarios including the nominal one, those incorporating ±5mm setup uncertainties long x, y and z directions and ±3.5% range uncertainties are calculated. All 90 dose distributions are simultaneously optimized to achieve full dose coverage of 10 CTVs and sparing of normal structures. ITV-based 3D RO and PTV-based optimization based on the average CT are also carried for the same patient using same dose volume constrains. After optimization, 4D robustness evaluation was performed for all resulting plans. The CTV coverage and the sparing of normal tissue in 10 phases are evaluated and compared among the three methods. The widths of DVH bands represent the robustness of dose distributions in the structures. Results: For one patient studied so far, the worst case CTV coverage by the prescription dose among all 90 scenarios is: 99% for 4D RO; 88.9% for 3D RO, and 85.2% for PTV based optimization. 4D RO also results in best robustness with the narrowest DVH’ bandwidths for the CTV. 4D and 3D RO have similar organ sparing while PTV based optimization results in worst organ sparing. Conclusion: 4D robust optimization which accounts for anatomy motion and deformation in the optimization process, significantly improves plan robustness and achieves higher quality treatment plans for lung cancer patients. The method is being evaluated for multiple patients with different tumor and motion characteristics.

60 APPLIED LIFE SCIENCES↗