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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Implementation of fuel management multi-cycle optimization capabilities in RAVEN optimization framework

Optimization in nuclear fuel-management assists the core reload engineer with finding optimal out-of-core and in-core strategies. RAVEN is INL’s open source software that is equipped with fuel-management optimization capabilities including single-cycle, single- and multi-objective optimization of pressurized water reactors (PWRs) loading patterns (LP) of a fresh core using genetic algorithm (GA) and non-dominated sorting genetic algorithm (NSGA-II). In practice, however, medium and long term planning of fuel-management needs a multi-cycle approach, where the history and availability of fuel assemblies is considered in the optimization process. In this paper, we present a description of an initial expansion of RAVEN fuel-management optimization capabilities for a multi-cycle optimization framework. N-th cycle optimization capabilities that account for the unique history of recycled fuel assembly in the core were added. The multi-cycle optimization approach taken is formulated as a cycle-wise optimization problem where out-of-core decisions are used to onset each cycle optimization. Out-of-core decisions are managed externally to the in-core optimization by a fuel inventory management module. A proof-of-concept optimization problem is also presented.

42 - ENGINEERING↗
DOE OSTI2022

J-PLUS: Support vector machine applied to STAR-GALAXY-QSO classification

Context. In modern astronomy, machine learning has proved to be efficient and effective in mining big data from the newest telescopes. Aims. In this study, we construct a supervised machine-learning algorithm to classify the objects in the Javalambre Photometric Local Universe Survey first data release (J-PLUS DR1). Methods. The sample set is featured with 12-waveband photometry and labeled with spectrum-based catalogs, including Sloan Digital Sky Survey spectroscopic data, the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and VERONCAT – the Veron Catalog of Quasars & AGN. The performance of the classifier is presented with the applications of blind test validations based on RAdial Velocity Extension, the Kepler Input Catalog, the Two Micron All Sky Survey Redshift Survey, and the UV-bright Quasar Survey. A new algorithm was applied to constrain the potential extrapolation that could decrease the performance of the machine-learning classifier. Results. The accuracies of the classifier are 96.5% in the blind test and 97.0% in training cross-validation. The F1-scores for each class are presented to show the balance between the precision and the recall of the classifier. We also discuss different methods to constrain the potential extrapolation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Energy-Transit Nexus Tools for Bus Fleet Electrification (NEXTBUS)

NEXTBUS is an open-source software project that integrates NLR's bus energy modeling and simulation tools with multi-objective optimization for fleet operations. NLR is collaborating with a transit technology startup, ReVolt, to commercialize these capabilities by deploying NEXTBUS in ReVolt's software platform. The goal is to manage the added complexities of running a heterogeneous fleet, encompassing battery electric and diesel buses, across a large, multi-depot transit network.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2019

Overview of the Optomechanical Design of the LUVOIR Instruments

The Large Ultraviolet/Optical/Infrared Surveyor (LUVOIR) is a space telescope being submitted for review to the 2020 Decadal Survey in Astronomy and Astrophysics. Its science objectives include both direct imaging and spectral characterization of habitable exoplanets around sun-like stars, the study of planet, star, and galaxy formation, the transfer of matter between different galaxies, and the remote sensing of objects within the Solar System. Two architectures have been designed: a 15 m diameter on-axis telescope (LUVOIR-A) and an 8 m off-axis telescope (LUVOIR-B). This paper discusses the opto-mechanical design of the three LUVOIR instruments: the High Definition Imager (HDI), the LUVOIR UV Multi-object Spectrograph (LUMOS), and the Extreme Coronagraph for Living Planetary Systems (ECLIPS). For both the LUVOIR-A and LUVOIR-B variants of each instrument, optical design specifications are presented including first-order constraints, packaging requirements, and optical performance metrics. These factors are used to illustrate the final design of each instrument and LUVOIR as a whole. In addition to the optical designs, mechanical models are presented for each instrument showing the optical mounts, mechanisms, support structure, etc.

Decadal Study↗
DOE OSTI2022

J-PLUS: Support vector regression to measure stellar parameters

Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameter's regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account, the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Finding the Pareto front for high-entropy-alloy catalysts

Finding catalysts that have both high activity and high stability presents a long-standing challenge. Since optimizing activity and stability are conflicting objectives, the best one can do is find the Pareto front that yields optimal tradeoffs between these features. On the Pareto front, there is a trade-off where a portion of catalytic activity must be sacrificed to gain further stability and vice versa . Here, we provide a method to optimize the front by designing a multi-objective genetic algorithm that combines machine learning, graph neural network calculations, and density functional calculations. The application considered is the oxygen evolution reaction catalyzed by high-entropy alloys. We find that the Pareto front generally contains alloys with diverse elements, but that enhancing stability inevitably inflicts a toll on activity. We compare the general conclusions of our work to a survey of 545 experiments.

Zhang, Chengyi [Univ. of Auckland (New Zealand)]↗
DOE OSTI2020

Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities

This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed control architecture distributes the computational effort and is easier to be scaled up than traditional centralized control. The decentralized control architecture consists of two layers: The community operator layer (COL) allocates the limited amount of renewable energy resource according to the power flexibility of each building. The building agent layer (BAL) addresses the optimal load scheduling problem for each building with the allowable load determined by the COL. Both layers are formulated as a model predictive control (MPC) based optimization. Simulation scenarios are designed to compare different combinations of building weighting methods and objective functions to provide guidance for real-world deployment by community and microgrid operators. The results indicate that the impact of power flexibility is more prominent than the weighting factor to the resource allocation process. Allocation based purely on occupancy status could lead to an increase of PV curtailment. Further, it is necessary for the building agent to have multi-objective optimization to minimize unserved load ratio and maximize comfort simultaneously.

model predictive control↗
DOE OSTI2024

Physics-based reward driven image analysis in microscopy

The rise of electron microscopy has expanded our ability to acquire nanometer and atomically resolved images of complex materials. The resulting vast datasets are typically analyzed by human operators, an intrinsically challenging process due to the multiple possible analysis steps and the corresponding need to build and optimize complex analysis workflows. We present a methodology based on the concept of a Reward Function coupled with Bayesian Optimization, to optimize image analysis workflows dynamically. The Reward Function is engineered to closely align with the experimental objectives and broader context and is quantifiable upon completion of the analysis. Here, cross-section, high-angle annular dark field (HAADF) images of ion-irradiated (Y, Dy)Ba 2 Cu 3 O 7–δ thin-films were used as a model system. The reward functions were formed based on the expected materials density and atomic spacings and used to drive multi-objective optimization of the classical Laplacian-of-Gaussian (LoG) method. These results can be benchmarked against the DCNN segmentation. This optimized LoG* compares favorably against DCNN in the presence of the additional noise. We further extend the reward function approach towards the identification of partially-disordered regions, creating a physics-driven reward function and action space of high-dimensional clustering. We pose that with correct definition, the reward function approach allows real-time optimization of complex analysis workflows at much higher speeds and lower computational costs than classical DCNN-based inference, ensuring the attainment of results that are both precise and aligned with the human-defined objectives.

47 OTHER INSTRUMENTATION↗
NASA NTRS1984

Advanced wide-field broad-passband refracting field correctors for large telescopes

Design objectives, constraints, and optical data are presented for specific corrector designs under consideration for several large telescope projects. These include a preliminary 30-arcmin prime focus (f/2.0) refracting field corrector system for the University of California Ten-Meter Telescope (UC TMT); a compact 40-arcmin internal Cassegrain (f/1.75 hyperbola to f/5.0) broad-passband (3300 A to 1.0 micron) corrector suitable for imaging and multi-object spectroscopy at the UC TMT; three 60-arcmin Cassegrain correctors for 300-inch f/1.8 and f/2.0 parabolic primary mirrors suitable for a Fifteen-Meter NNTT/MMT; and a 300-inch 40-arcmin external Cassegrain (f/1.0 parabola to f/4.0) broad-passband (3300 A to 1.0 micron) corrector with ADC.

Epps, H. W.↗
NASA NTRS2003

The Star Formation History of Orion and its Environs

During the period of performance, we have obtained the following observations and carried out the analysis of the Orion associations itemized below. Optical Photometry: The Quest camera that had been damaged by lightning on Sept. 2001 was reconfigured to use 10 chips and only 3 filters instead of the original 4 but retaining its spatial coverage of 2.3deg wide in declination. During the Winter and Fall 2002 observing campaigns, we obtained multifilter photometry using the Quest camera on the 1mt Schmidt of the Venezuelan National Observatory, to continue the survey of the Orion clouds. In the Winter 2002 season, we obtained photometry for 10 scans at DEC=+5, 7 scans at DEC=-5. Several additional scans at DEC=-3 were obtained during the Fall 2002 observing campaign. Slit spectroscopy of bright candidates: During 2002 spectra for some 235 candidate PMS stars were obtained with the FAST spectrograph at the SAO 1.5m telescope in Mt. Hopkins. These objects, all brighter than V=16, are located in two strips centered at DEC=+l and -5, and spanning from RA=5h-6h. The spectra are being analyzed. Multifiber spectroscopy: Spectroscopy for our fainter (V less than or equal to 16) candidates has not kept pace with our spectroscopy of brighter candidates, because of the delay in the commissioning of the Hectospec and Hectoechelle multi-object spectrographs at the new 6.5m MMT. We obtained some data with the Hydra spectrograph on the WIYN telescope: Feb 1-4, 2002. Time granted to the project: "A Large Scale Survey of the Low-Mass Young Population in the Orion OB1 Association" (P.I.: C. Briceno). Three half-nights (we used the first half of the night, the second half of the night was used with the Mini-Mosaic imager by another team). Only the first half night was clear. We observed 3 fields centered in a 2.3 deg wide strip centered at DEC=-1 and spanning RA=Sh to 6h. A total of 250 spectra were obtained for the same number of candidate PMS stars. Nov. 13-15, 2002. Time granted to the project "Cluster survey of protoplanetary disk evolution", (P.I.: A. Sicilia-Aguilar). Clear weather throughout. We obtained spectra for some 200 candidate PMS stars in 3 fields located in a 2.3 deg wide strip centered at DEC=+l and spanning from RA=5h20m to 5h35m. Data for both observing runs is partially reduced and is being analyzed. U photometry: During Nov.29-Dec.4, 2002 we were granted time with the 4-shooter CCD Mosaic Camera at the SAO 1.2m telescope, to obtain U-band photometry of a subset of the newly identified T Tauri stars in the strip centered at DEC=-1. This sample is composed of strong H(alpha) emitting PMS stars (Classical T Tauri stars) located mostly in the Orion OB lb association, around the Orion Belt area. Our data will be combined with our calibration of the U-band excess (Gullbring et al. 1998) to derive mass accretion rates. Because of bad weather we observed only 20 stars during 1.5 clear nights. Near IR photometry: During Dec. 14-19, 2002 we used the IR Camera on the SAO 1.2m telescope, to obtain L-band photometry of a set of 17 the newly identified Orion OB 1a and 1b stars, in order to look for IR excess emission coming from the hotter inner parts of circumstellar disks. Again, mediocre weather prevented a larger set to be observed. These stars were also observed with the OSCIR mid-IR camera on Gemini North during later 2001. Our goal is to construct SEDs from the visual out to the mid-IR (by combining our optical/IR data with 2MASS JHK magnitudes) in order to explore disk dissipation at the critical ages of 5-10 Myr spanned by these stars.

Calvet, Nuria↗
NASA NTRS2017

A Requirements-Driven Optimization Method for Acoustic Liners Using Analytic Derivatives

More than ever, there is flexibility and freedom in acoustic liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. In a previous paper on this subject, a method deriving the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground was described. A simple code-wrapping approach was used to evaluate a community noise objective function for an external optimizer. Gradients were evaluated using a finite difference formula. The subject of this paper is an application of analytic derivatives that supply precise gradients to an optimization process. Analytic derivatives improve the efficiency and accuracy of gradient-based optimization methods and allow consideration of more design variables. In addition, the benefit of variable impedance liners is explored using a multi-objective optimization.

Aircraft Noise↗
DOE OSTI2026

Optimization and stabilization of Fermilab Booster using hybrid Bayesian/RL framework

PIPII project will raise Fermilab Booster intensity and ramp rate. Beam losses will limit average power and are hard to simulate. Presently, Booster uses operator-guided empirical tuning. This task is challenging due to high dimensionality, multiple objectives, critical safety constraints, and drifts. We developed a synergistic suite of Bayesian optimization (BO) and reinforcement learning (RL) tools to optimize and stabilize beam losses. First, active learning was used to build a rough model. Data was collected parasitically using two novel safety constraint types – nonlinear input space restrictions (based on optics model), and uncertainty constraints (to stop bad steps/beam aborts). We then applied online multi-objective BO with scalarized objectives and fitting to improve/rebalance losses, increasing safety margins by 25%. Using BO model as a safety veto, we tried several on/off-policy RL agents for long term stabilization; SAC had best performance. We found that adding contextual (state) information further improved performance, eventually integrating key knobs like linac phase and temperature into the parameter space. Long term testing is ongoing to enable operational use.

Kuklev, Nikita [Fermilab]↗
NASA NTRS2013

A Tool for the Automated Design and Evaluation of Habitat Interior Layouts

The objective of space habitat design is to minimize mass and system size while providing adequate space for all necessary equipment and a functional layout that supports crew health and productivity. Unfortunately, development and evaluation of interior layouts is often ignored during conceptual design because of the subjectivity and long times required using current evaluation methods (e.g., human-in-the-loop mockup tests and in-depth CAD evaluations). Early, more objective assessment could prevent expensive design changes that may increase vehicle mass and compromise functionality. This paper describes a new interior design evaluation method to enable early, structured consideration of habitat interior layouts. This interior layout evaluation method features a comprehensive list of quantifiable habitat layout evaluation criteria, automatic methods to measure these criteria from a geometry model, and application of systems engineering tools and numerical methods to construct a multi-objective value function measuring the overall habitat layout performance. In addition to a detailed description of this method, a C++/OpenGL software tool which has been developed to implement this method is also discussed. This tool leverages geometry modeling coupled with collision detection techniques to identify favorable layouts subject to multiple constraints and objectives (e.g., minimize mass, maximize contiguous habitable volume, maximize task performance, and minimize crew safety risks). Finally, a few habitat layout evaluation examples are described to demonstrate the effectiveness of this method and tool to influence habitat design.

Simon, Matthew A.↗
NASA NTRS2005

Surrogate-based Analysis and Optimization

A major challenge to the successful full-scale development of modem aerospace systems is to address competing objectives such as improved performance, reduced costs, and enhanced safety. Accurate, high-fidelity models are typically time consuming and computationally expensive. Furthermore, informed decisions should be made with an understanding of the impact (global sensitivity) of the design variables on the different objectives. In this context, the so-called surrogate-based approach for analysis and optimization can play a very valuable role. The surrogates are constructed using data drawn from high-fidelity models, and provide fast approximations of the objectives and constraints at new design points, thereby making sensitivity and optimization studies feasible. This paper provides a comprehensive discussion of the fundamental issues that arise in surrogate-based analysis and optimization (SBAO), highlighting concepts, methods, techniques, as well as practical implications. The issues addressed include the selection of the loss function and regularization criteria for constructing the surrogates, design of experiments, surrogate selection and construction, sensitivity analysis, convergence, and optimization. The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.

Queipo, Nestor V.↗
NASA NTRS2012

Studies of Supernovae, SNR, and Dust with the James Webb Space Telescope

The james Webb Space Telescope (JWST) will provide breakthrough capabilities for the study of supernovae and supernova remnants, as well as many other science objectives. JWST is a large aperture, cryogenic, infrared-optimized general purpose space observatory under construction by NASA, ESA, and CSA for launch in 2018. The JWST instrumentation will provide imaging, coronagraphy, and spectroscopy between 6000A to 29 microns. This spectral region contains many atomic, molecular, and particulate diagnostics that are especially relevant for the study of dust formation. The spectroscopic capabilities include velocity resolution down to approx. 100 km/sec, a near-IR multi-object spectrograph with a approx. 3x3 arcmin field of view array of approx. 250,000 addressable shutters, and near-IR and mid-IR approx. 3x3 arcsec integral field units. The JWST telescope will have a 6.5m-diameter segmented primary mirror and will be diffraction-limited at 2 microns (PSF FWHM - 0.07 arcsec). The imaging and spectroscopic sensitivities will be about 100x lower than previous capabilities in the near- and mid-IR. The JWST observatory will be placed in a L2 orbit by an Ariane 5 launch vehicle provided by ESA. The JWST telescope and instruments will be passively cooled to approx. 40K by a sunshield that will be unfolded after launch. The sunshield geometry limits the JWST pointing on the sky to be between 85 deg and 135 deg from the Sun. The observatory is designed for a 5-year prime science mission, with consumables for 10 years of science operations, and a Target of Opportunity response time of 48 hours.

Sonneborn, George↗
NASA NTRS2002

STS-109 Crew Interviews: Michael J. Massimino

STS-109 Mission Specialist Michael J. Massimino is seen during a prelaunch interview. He answers questions about his inspiration to become an astronaut, his career path, and his most memorable experiences. He gives details on the mission's goals and objectives, which focus on the refurbishing of the Hubble Space Telescope, and his role in the mission. He explains the plans for the rendezvous of the Columbia Orbiter with the Hubble Space Telescope. He provides details and timelines for each of the planned Extravehicular Activities (EVAs), which include replacing the solar arrays, changing the Power Control Unit, installing the Advanced Camera for Surveys (ACS), and installing a new Cryocooler for the Near Infrared Camera and Multi-Object Spectrometer (NICMOS). He also describes the break-out plan in place for these spacewalks. The interview ends with Massimino explaining the details of a late addition to the mission's tasks, which is to replace a reaction wheel on the Hubble Space Telescope.

Source record↗
NASA NTRS2006

Reentry-Vehicle Shape Optimization Using a Cartesian Adjoint Method and CAD Geometry

A DJOINT solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (e.g., geometric parameters that control the shape). Classic aerodynamic applications of gradient-based optimization include the design of cruise configurations for transonic and supersonic flow, as well as the design of high-lift systems. are perhaps the most promising approach for addressing the issues of flow solution automation for aerodynamic design problems. In these methods, the discretization of the wetted surface is decoupled from that of the volume mesh. This not only enables fast and robust mesh generation for geometry of arbitrary complexity, but also facilitates access to geometry modeling and manipulation using parametric computer-aided design (CAD). In previous work on Cartesian adjoint solvers, Melvin et al. developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the two-dimensional Euler equations using a ghost-cell method to enforce the wall boundary conditions. In Refs. 18 and 19, we presented an accurate and efficient algorithm for the solution of the adjoint Euler equations discretized on Cartesian meshes with embedded, cut-cell boundaries. Novel aspects of the algorithm were the computation of surface shape sensitivities for triangulations based on parametric-CAD models and the linearization of the coupling between the surface triangulation and the cut-cells. The accuracy of the gradient computation was verified using several three-dimensional test cases, which included design variables such as the free stream parameters and the planform shape of an isolated wing. The objective of the present work is to extend our adjoint formulation to problems involving general shape changes. Factors under consideration include the computation of mesh sensitivities that provide a reliable approximation of the objective function gradient, as well as the computation of surface shape sensitivities based on a direct-CAD interface. We present detailed gradient verification studies and then focus on a shape optimization problem for an Apollo-like reentry vehicle. The goal of the optimization is to enhance the lift-to-drag ratio of the capsule by modifying the shape of its heat-shield in conjunction with a center-of-gravity (c.g.) offset. This multipoint and multi-objective optimization problem is used to demonstrate the overall effectiveness of the Cartesian adjoint method for addressing the issues of complex aerodynamic design.

Nemec, Marian↗
NASA NTRS1990

A homotopy approach for combined control-structure optimization - Constructive analysis and numerical examples

This paper outlines the development of methods for the combined control-structure optimization of physical systems encountered in the technology of large space structures. The objectives of the approach taken in this paper is not to produce the 'best' optimized design, but rather to efficiently produce a family of design options so as to assist in early trade studies, typically before hard design constraints are imposed. The philosophy is that these are candidate designs to be passed on for further considerations, and their function is more to guide the development of the system design rather than to represent the ultimate product. A homotopy approach involving multi-objective functions is developed for this purpose. Analytical and numerical examples are also presented.

Scheid, R. E.↗