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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 1,315 records · Page 73

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NASA NTRS1984

High frequency plasma generator for ion thrusters

The results of a program to experimentally develop two new types of plasma generators for 30 cm electrostatic argon ion thrusters are presented. The two plasma generating methods selected for this study were by radio frequency induction (RFI), operating at an input power frequency of 1 MHz, and by electron cyclotron heating (ECH) at an operating frequency of 5.0 GHz. Both of these generators utilize multiline cusp permanent magnet configurations for plasma confinement and beam profile optimization. The program goals were to develop a plasma generator possessing the characteristics of high electrical efficiency (low eV/ion) and simplicity of operation while maintaining the reliability and durability of the conventional hollow cathode plasma sources. The RFI plasma generator has achieved minimum discharge losses of 120 eV/ion while the ECH generator has obtained 145 eV/ion, assuming a 90% ion optical transparency of the electrostatic acceleration system. Details of experimental tests with a variety of magnet configurations are presented.

Goede, H.↗

NASA NTRS1981

Performance of a magnetic multipole line-cusp argon ion thruster

The performance of a 17-cm diameter line-cusp ion thruster, using argon and xenon propellants, is investigated. Basic optimization of the thruster was accomplished without ion extraction and tests were conducted with small vacuum facilities and power supplies. The evaluation of the sensitivity of the performance to changes in discharge electrode configurations and the magnetic circuit is discussed. Final optimization results show that an argon propellant utilization efficiency of 0.9, at 260 W of discharge power per beam ampere, was obtained with a thruster having 20 rows of magnets and 10 tubular anodes. The average ion beam current densities were as high as 13 mA/sq cm. The results are considered to be the highest yet achieved with argon propellant.

Sovey, J. S.↗

DOE OSTI2026

IOTA experiment for proton pulse compression at extreme space-charge

The longitudinal compression of intense proton bunches with strong space-charge force is an essential component of a proton driver for a muon collider. We propose a proton bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to explore optimal radio frequency (RF) cavity and lattice configurations. IOTA is a compact fixed-energy storage ring dedicated to beam physics R&D that can circulate a 2.5-MeV proton beam with extreme space-charge. Using ImpactX and its 3D space-charge solver, simulations indicate that bunch length can be rapidly reduced by a factor of at least two, without appreciable degradation in transverse beam quality, even under strong space-charge conditions. However, longitudinal defocusing presents a large effect in short-pulsed proton beams, and the optimization of bunch compression under such conditions is discussed.

Simons, Benjamin [Northern Illinois U.; Fermilab]↗

NASA NTRS1972

Optimum spaceborne computer system design by simulation

A deterministic digital simulation model is described which models the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. Use of the model as a tool in configuring a minimum computer system for a typical mission is demonstrated. The configuration which is developed as a result of studies with the simulator is optimal with respect to the efficient use of computer system resources, i.e., the configuration derived is a minimal one. Other considerations such as increased reliability through the use of standby spares would be taken into account in the definition of a practical system for a given mission.

Williams, T.↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

NASA NTRSDate not supplied

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

air traffic management↗

DOE OSTI2021

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework and fictional input data, and a genetic optimization is included which determines optimal flash plant parameters. The inputs and outputs associated with the forecast and genetic optimization are included. The input and output files consist of data, configuration files, and plots. A link to the Physics-Guided Neural Networks (phygnn) GitHub repository is also included, which augments a traditional neural network loss function with a generic loss term that can be used to guide the neural network to learn physical or theoretical constraints. phygnn is used by the GOOML framework to help integrate its machine learning models into the relevant physics and engineering applications. Note that the data included in this submission are intended to provide a demonstration of GOOML's capabilities. Additional files that have not been released to the public are needed for users to run these models and reproduce these results. Units can be found in the readme data resource.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

Turning statistical physics models into materials design engines

Despite the success statistical physics has enjoyed at predicting the properties of materials for given parameters, the inverse problem, identifying which material parameters produce given, desired properties, is only beginning to be addressed. Recently, several methods have emerged across disciplines that draw upon optimization and simulation to create computer programs that tailor material responses to specified behaviors. However, so far the methods developed either involve black-box techniques, in which the optimizer operates without explicit knowledge of the material's configuration space, or require carefully tuned algorithms with applicability limited to a narrow subclass of materials. Here we introduce a formalism that can generate optimizers automatically by extending statistical mechanics into the realm of design. The strength of this approach lies in its capability to transform statistical models that describe materials into optimizers to tailor them. Here, by comparing against standard black-box optimization methods, we demonstrate how optimizers generated by this formalism can be faster and more effective, while remaining straightforward to implement. The scope of our approach includes possibilities for solving a variety of complex optimization and design problems concerning materials both in and out of equilibrium.

36 MATERIALS SCIENCE↗

NASA NTRS1988

Multi-airfoil Navier-Stokes simulations of turbine rotor-stator interaction

An accurate numerical analysis of the flows associated with rotor-stator configurations in turbomachinery can be extremely helpful in optimizing the performance of turbomachinery. In this study the unsteady, thin-layer, Navier-Stokes equations in two spatial dimensions are solved on a system of patched and overlaid grids for a rotor-stator configuration from an axial turbine. The governing equations are solved using a finite-difference, upwind algorithm that is set in an iterative, implicit framework. Results in the form of pressure contours, time-averaged pressures, unsteady pressure amplitudes and phase are presented. The numerical results are compared with experimental data and the agreement is found to be good. The results are also compared with those of an earlier study which used only one rotor and one stator. The current study uses multiple rotors and stators and a pitch ratio that is much closer to the experimental ratio. Consequently the results of this study are found to be closer to the experimental data.

Rai, Man Mohan↗

DOE OSTI2019

Gibbs Energy Minimization Model for Solvent Extraction with Application to Rare-Earths Recovery

The emergence of technologies in which rare-earth elements provide critical functionality has increased the demand for these materials, with important implications for supply security. Recycling provides an option for mitigating supply risk and for creating economic value from the resale of recovered materials. While solvent extraction is a proven technology for rare-earth recovery and separation, its application often requires extensive trial-and-error experimentation to estimate parameter values and determine experimental design configurations. We describe a modeling strategy based on Gibbs energy minimization that incorporates parameter estimation for required thermodynamic properties as well as process design for solvent extraction and illustrate its applicability to rare earths separation. Visualization analysis during parameter estimation revealed a linear relationship between the standard enthalpies of the extractant and respective organo-metal complexes, analogous to the additivity principle for predicting molar volumes of organic compounds. Establishing this relationship reduced the size of the parameter estimation problem and yielded good agreement between model predictions and reported equilibrium extraction data, validating the property estimates for the organic phase species. Design exploration and optimization results map the space of feasible solvent extraction column configurations and identify the set of optimal design parameter values that meet recovery and purity targets.

Critical materials↗

DOE OSTI2016

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrc package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Economic Analysis of Integrated Solar Power, Hydrogen Production, and Electricity Markets

Hydrogen is a versatile energy carrier that is used in a wide variety of chemical and industrial processes. Producing hydrogen using electrolysis can enable integration of multiple sectors including electricity, heating, and industrial sectors; however, the cost of producing hydrogen from electrolysis remains a challenge for encouraging greater adoption. To help improve the economics for both solar PV and hydrogen production using electrolyzers, we explore the benefit of combining PV and electrolysis systems. Using the Revenue Operation and Device Optimization Model (RODeO) model, the optimal breakeven hydrogen production cost for six unique market participation configurations is calculated at six candidate locations in California where PV is already installed. Costs include production, storage, and compression in preparation for gaseous delivery trucks. Revenue streams included in the optimization are the sale of hydrogen, Low Carbon Fuel Standard (LCFS) credits, renewable electricity sold to the grid, and Renewable Energy Credits (REC). The costs included are the electricity costs, capital and fixed operation and maintenance cost (FOM) for the electrolyzer, PV, and storage and compression systems as well as taxes and financing costs. In addition, cost reductions are achieved through retail and wholesale electricity use optimization, by which electricity is purchased at the lowest price and sold, if possible, at the highest price. For all locations analyzed, the breakeven hydrogen production cost results show that, in order of decreasing cost, the system configurations are islanded (highest), separated, NEM, retail, hybrid retail/wholesale, and wholesale (lowest). This report also explores other aspects of hydrogen systems including optimal renewable sizing and resulting energy mixture to the electrolyzer, value of renewable premiums, competition with incumbent technologies, cost sensitivity to a variety of parameters.

decarbonized economy↗

NASA NTRS1987

Optimal reconfiguration strategy for a degradable multimodule computing system

The present quantitative approach to the problem of reconfiguring a degradable multimode system assigns some modules to computation and arranges others for reliability. By using expected total reward as the optimal criterion, there emerges an active reconfiguration strategy based not only on the occurrence of failure but the progression of the given mission. This reconfiguration strategy requires specification of the times at which the system should undergo reconfiguration, and the configurations to which the system should change. The optimal reconfiguration problem is converted to integer nonlinear knapsack and fractional programming problems.

Lee, Yann-Hang↗

NASA NTRS1990

Optimum structural design of robotic manipulators with fiber reinforced composite materials

High-speed robotic arms with advanced structural characteristics can be fabricated from optimally tailored fiber reinforced composites. An integrated design methodology is presented for the optimal structural synthesis of composite robotic manipulators. Optimum configurations of ply angles and ply thicknesses are predicted for maximum structural end-effector stiffness and maximum end-effector load carrying capacity, without altering the geometric dimensions of the links. Multiple posture finite element-based static performance criteria are implemented. A new finite element has been developed for the modeling of tubular composite links. Unique features are the inclusion of shear effects and coupling between stretching and flexure. Numerical solutions are obtained via an efficient optimization algorithm. Applications to an existing SCARA-class manipulator illustrate the effectiveness of the method and demonstrate the dramatic influence of the multi-postural design criteria on the optimal design. For a filament wound structure using a high strength carbon fiber in a thermoplastic matrix, the resultant optimum ply configurations have increased the specific stiffness and specific load capacity by factors of 1.5 and 16, respectively, in comparison to identically sized aluminum links.

Saravanos, D. A.↗

DOE OSTI2023

IER - 551: Experiment for Unresolved Resonance of Plutonium Actinides (EUROPA): CED-1 for True Intermediate Pu Benchmark

IER-551 or the Experiment for Unresolved Resonance Of Plutonium Actinides (EUROPA), is an experiment campaign to design and execute a series of true intermediate energy plutonium critical configurations. EUROPA is a collaboration between Los Alamos National Laboratory (LANL), Oak Ridge National Laboratory (ORNL), and the French Institut de Radioprotection et de Sûreté Nucléaire (IRSN) to validate current and future evaluations of 239,240 Pu isotopes. Preliminary designs were optimized using Particle Swarm Optimization to save on computation time and the configuration with highest percentage of intermediate neutrons causing fission found was BeO-Cd. This combination has over 70% of fissions occurring from intermediate energy neutrons. Secondary considerations regarding end benchmark uncertainties and quality of nuclear data resulted in a beryllium metal only experiment proposed as the final system. This final preliminary design achieves 68% intermediate fissions, sensitivities of fission and capture cross sections of 239 Pu of 0.3021 and -0.1610 respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Optimization of Marine Thrusters

Improving the maneuverability of ships by increasing the tractional force of the thrusters is considered. To minimize the losses associated with swirling liquid flow and the variable attack angles in reversing, the traditional configuration must be modified, and the inclination of the thruster blades must be optimized. To increase the efficiency, the rotors should have different speeds and blade inclinations.

42 ENGINEERING↗

DOE OSTI2021

Transient Efficiency Flexibility and Reliability Optimization of Coal-Fired Power Plants: Model-Predictive Control Library Development (Report)

This document pertains to the reporting requirements of DOE contract FE-0031767. The document covers the development of a model predictive control (MPC) library for implementing MPC for a general dynamic system. The library is implemented in a standardized manner in Matlab/Simulink, where core functions on model prediction, linearization and formulation and solution of a quadratic programming (QP) optimization problem is done in the core library - independent of the specific application. The user can provide the application-specific dynamic model in continuous and discrete time, to rapidly implement and test the MPC performance in a desktop simulation. The MPC optimization objective and constraints are also easily configured via an Excel file to allow iterative refinement as needed. Finally, the MPC library enables a rapid deployment to a target environment through auto C-code generation and containerization. The MPC library works seamlessly with the model based estimation (MBE) library to obtain the overall output feedback control solution. In this program, the reduced order model (ROM) of a coal-fired power plant (CFPP) is used to implement and test the MPC solution.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS2007

Parametric Study of Biconic Re-Entry Vehicles

An optimization based on hypersonic aerodynamic performance and volumetric efficiency was accomplished for a range of biconic configurations. Both axisymmetric and quasi-axisymmetric geometries (bent and flattened) were analyzed. The aerodynamic optimization wag based on hypersonic simple Incidence angle analysis tools. The range of configurations included those suitable for r lunar return trajectory with a lifting aerocapture at Earth and an overall volume that could support a nominal crew. The results yielded five configurations that had acceptable aerodynamic performance and met overall geometry and size limitations

Steele, Bryan↗