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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Optimizing Federal Fleet Vehicle Acquisitions: An Eleven-Agency FY 2012 Analysis

This report focuses on the National Renewable Energy Laboratory's (NREL) fiscal year (FY) 2012 effort that used the NREL Optimal Vehicle Acquisition (NOVA) analysis to identify optimal vehicle acquisition recommendations for eleven diverse federal agencies. Results of the study show that by following a vehicle acquisition plan that maximizes the reduction in greenhouse gas (GHG) emissions, significant progress is also made toward the mandated complementary goals of acquiring alternative fuel vehicles, petroleum use reduction, and alternative fuel use increase.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

25 ENERGY STORAGE↗
DOE OSTI2022

Implementation of an Orificing Optimization Algorithm in the DASSH Subchannel Analysis Code

The Ducted Assembly Steady-State Heat transfer code (DASSH) performs full-core subchannel thermal hydraulics calculations in liquid metal fast reactors. One of the applications of subchannel codes is to optimize coolant flow orificing. As a design activity, the primary task is to determine the best way to divide assemblies into groups and distribute coolant flow rates among them. This report documents an algorithm implemented in DASSH to automatically optimize coolant orificing. Over the course of multiple iterations, DASSH determines the orifice grouping and flow distribution that minimizes peak coolant, clad, or fuel temperatures across all timesteps for a user-specified number of assembly groups. The total coolant flow rate in the reactor is constrained to achieve the specified core-average outlet temperature. The flow rate to each orifice group may also be constrained by the allowable pressure drop. The distribution of coolant flow among groups is accelerated using a predictor-corrector algorithm based on interpolated results from single-assembly parametric calculations. The assembly orificing grouping is initially predicted based on assembly power but can be refined if results demonstrate that an assembly would fit better in another group. The algorithm is demonstrated with two case studies. The first is a simple model for a reactor core consisting of just fuel assemblies; the pin power distributions are specified to create a situation where the initial assembly grouping prediction is suboptimal. This example is used to describe the initial grouping, demonstrate convergence over multiple iterations, and highlight the impact of regrouping. Then, the algorithm is applied to minimize peak clad and fuel temperatures in an example sodium-cooled fast reactor, the Versatile Test Reactor. The multicycle optimization confirms prior calculations for the reference core design. The example highlights how optimizing for different peak temperatures affects the results and demonstrates the use of the pressure drop constraint to limit the maximum flow rate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

ROSE Compiler Framework

The purpose of the ROSE Complier Framework Is to automate source code porting, source and binary code analysis, and source code translations such as platform optimization, binary code analysis, Identification of source code and binary code vulnerablllttes.

Quinlan, Dan↗
NASA NTRS1989

Applications of integrated design/analysis systems in aerospace structural design

Integrated structural analysis and design systems and structural optimization procedures are being used in a production environment. Successful use of these systems requires experienced personnel. Interactive computer graphics can and will play a significant role in the analysis, optimization, design and manufacturing areas. Practical structural optimization procedures are tools that must be made available to the team. Much work still needs to be done to tie finite-element modeling to actual design details which are being tracked on systems such as CADAM or CATIA. More work needs to be done to automate the detailed design and analysis process. More emphasis should be placed on the real design problems.

Mason, Philip↗
NASA NTRS2012

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

Classification↗
DOE OSTI2023

Sensitivity Analysis, Reduced-order Modeling, and Optimization of a Gas-Cooled Pebble Bed Reactor using Equilibrium-Core and DLOFC Performance

This work presents and applies a workflow for performing design optimization on gas-cooled pebble-bed reactors. Based on previous research, a representative equilibrium core of a pebble-bed reactor and a depressurized loss-of-forced-cooling model are created. These applications are built using the Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically utilizing Griffin, Pronghorn, and Bison. After defining design-related parameters and quantities of interest regarding reactor safety and efficiency, this multiphysics model is sampled using the MOOSE stochastic tools module. The result is a comprehensive dataset of configurations, enabling sensitivity analysis and the generation of reduced-order models. Subsequently, the dataset and reduced-order models are employed in an optimization study aimed at maximizing fuel utilization while adhering to safety and operational constraints. The optimization process leads to an improvement of fuel utilization by approximately 10\%, compared to engineering-judgment-based nominal conditions.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Optimization of a Centrifugal Impeller Design Through CFD Analysis

This paper discusses the procedure, approach and Rocketdyne CFD results for the optimization of the NASA consortium impeller design. Two different approaches have been investigated. The first one is to use a tandem blade arrangement, the main impeller blade is split into two separate rows with the second blade row offset circumferentially with respect to the first row. The second approach is to control the high losses related to secondary flows within the impeller passage. Many key parameters have been identified and each consortium team member involved will optimize a specific parameter using 3-D CFD analysis. Rocketdyne has provided a series of CFD grids for the consortium team members. SECA will complete the tandem blade study, SRA will study the effect of the splitter blade solidity change, NASA LeRC will evaluate the effect of circumferential position of the splitter blade, VPI will work on the hub to shroud blade loading distribution, NASA Ames will examine the impeller discharge leakage flow impacts and Rocketdyne will continue to work on the meridional contour and the blade leading to trailing edge work distribution. This paper will also present Rocketdyne results from the tandem blade study and from the blade loading distribution study. It is the ultimate goal of this consortium team to integrate the available CFD analysis to design an advanced technology impeller that is suitable for use in the NASA Space Transportation Main Engine (STME) fuel turbopump.

Chen, W. C.↗
DOE OSTI2017

A CONSISTENT RETRIEVAL ANALYSIS OF 10 HOT JUPITERS OBSERVED IN TRANSMISSION

We present a consistent optimal estimation retrieval analysis of 10 hot Jupiter exoplanets, each with transmission spectral data spanning the visible to near-infrared wavelength range. Using the NEMESIS radiative transfer and retrieval tool, we calculate a range of possible atmospheric states for WASP-6b, WASP-12b, WASP-17b, WASP-19b, WASP-31b, WASP-39b, HD 189733b, HD 209458b, HAT-P-1b, and HAT-P-12b. We find that the spectra of all 10 planets are consistent with the presence of some atmospheric aerosol; WASP-6b, WASP-12b, WASP-17b, WASP-19b, HD 189733b, and HAT-P-12b are all fit best by Rayleigh scattering aerosols, whereas WASP-31b, WASP-39b and HD 209458b are better represented by a gray cloud model. HAT-P-1b has solutions that fall into both categories. WASP-6b, HAT-P-12b, HD 189733b, and WASP-12b must have aerosol extending to low atmospheric pressures (below 0.1 mbar). In general, planets with equilibrium temperatures between 1300 and 1700 K are best represented by deeper, gray cloud layers, whereas cooler or hotter planets are better fit using high Rayleigh scattering aerosol. We find little evidence for the presence of molecular absorbers other than H{sub 2}O. Retrieval methods can provide a consistent picture across a range of hot Jupiter atmospheres with existing data, and will be a powerful tool for the interpretation of James Webb Space Telescope observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Modeling perennial bioenergy crops in the E3SM land model (ELMv2)

Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few earth system models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Model (E3SM) Land Model (ELMv2) to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality , although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.

09 BIOMASS FUELS↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS2007

Analytical Approach for Estimating Preliminary Mass of ARES I Crew Launch Vehicle Upper Stage Structural Components

In January 2004, President Bush gave the National Aeronautics and Space Administration (NASA) a vision for Space Exploration by setting our sight on a bold new path to go back to the Moon, then to Mars and beyond. In response to this vision, NASA started the Constellation Program, which is a new exploration launch vehicle program. The primary mission for the Constellation Program is to carry out a series of human expeditions ranging from Low Earth Orbit to the surface of Mars and beyond for the purposes of conducting human exploration of space, as specified by the Vision for Space Exploration (VSE). The intent is that the information and technology developed by this program will provide the foundation for broader exploration activities as our operational experience grows. The ARES I Crew Launch Vehicle (CLV) has been designated as the launch vehicle that will be developed as a "first step" to facilitate the aforementioned human expeditions. The CLV Project is broken into four major elements: First Stage, Upper Stage Engine, Upper Stage (US), and the Crew Exploration Vehicle (CEV). NASA's Marshall Space Flight Center (MSFC) is responsible for the design of the CLV and has the prime responsibility to design the upper stage of the vehicle. The US is the second propulsive stage of the CLV and provides CEV insertion into low Earth orbit (LEO) after separation from the First Stage of the Crew Launch Vehicle. The fully integrated Upper Stage is a mix of modified existing heritage hardware (J-2X Engine) and new development (primary structure, subsystems, and avionics). The Upper Stage assembly is a structurally stabilized cylindrical structure, which is powered by a single J-2X engine which is developed as a separate Element of the CLV. The primary structure includes the load bearing liquid hydrogen (LH2) and liquid oxygen (LOX) propellant tanks, a Forward Skirt, the Intertank structure, the Aft Skirt and the Thrust Structure. A Systems Tunnel, which carries fluid and electrical power functions to other Elements of the CLV, is included as secondary structure. The MSFC has an overall responsibility for the integrated US element as well as structural design an thermal control of the fuel tanks, intertank, interstage, avionics, main propulsion system, Reaction Control System (RCS) for both the Upper Stage and the First Stage. MSFC's Spacecraft and Vehicle Department, Structural and Analysis Design Division is developing a set of predicted mass of these elements. This paper details the methodology, criterion and tools used for the preliminary mass predictions of the upper stage structural assembly components. In general, weight of the cylindrical barrel sections are estimated using the commercial code Hypersizer, whereas, weight of the domes are developed using classical solutions. HyperSizer is software that performs automated structural analysis and sizing optimization based on aerospace methods for strength, stability, and stiffness. Analysis methods range from closed form, traditional hand calculations repeated every day in industry to more advanced panel buckling algorithms. Margin-of-safety reporting for every potential failure provides the engineer with a powerful insight into the structural problem. Optimization capabilities include finding minimum weight panel or beam concepts, material selections, cross sectional dimensions, thicknesses, and lay-ups from a library of 40 different stiffened and sandwich designs and a database of composite, metallic, honeycomb, and foam materials. Multiple different concepts (orthogrid, isogrid, and skin stiffener) were run for multiple loading combinations of ascent design load with and with out tank pressure as well as proof pressure condition. Subsequently, selected optimized concept obtained from Hypersizer runs was translated into a computer aid design (CAD) model to account for the wall thickness tolerance, weld land etc for developing the most probable weight of the components. The flow diram summarizes the analysis steps used in developing these predicted mass.

Aggarwal, Pravin↗
NASA NTRS1986

Weight estimation of unconventional structures by structural optimization

Automated techniques are presented that are used in structural optimization technology, with emphasis on modifications of finite element models to obtain an optimal material distribution for minimum weight while satisfying the prescribed design requirements. It is anticipated that the future development of computer aided engineering (CAE) system will provide environments where structural analysis, a design optimization, and weight evaluation modules are integrated, sharing a common data base. Structural optimization capabilities obtained by integrating a finite element structural analysis program and a numerical optimization code are developed and applied to two illustrative examples: marine gear housing structural weight minimization and joined wing structures.

Miura, Hirokazu↗
DOE OSTI2013

A search for baryon-number-violating decays of the $\Lambda$ using CLAS at JLab

We present the status of a search for baryon-number-violating decays of the Lambda baryon using data from the CLAS detector for photoproducton off of the proton in liquid hydrogen. The dataset contains roughly 3.0×106 Lambda production events that are reconstructable from three charged final-state tracks (recoil K+ and decay products). We investigate nine potential decay modes in which the Lambda decays to a meson-lepton pair. We perform a blind analysis during the optimization of data selection criteria. We estimate that the analysis will be sensitive to branching fractions on the order of Gamma_BNV/Gamma_tot ~ 6×10^-5, roughly an order of magnitude smaller than those of the currently known rare ? decays.

McCracken, Michael↗
NASA NTRS1995

Analysis of the Hessian for aeroelastic optimization

The symbol of the Hessian for an aeroelastic optimization model problem is analyzed. The flow is modeled by the small-disturbance full potential equation and the structure is modeled by an isotropic (von Karman) plate equation. The cost function consists of both aerodynamic and structural terms. In the new analysis the symbol of the cost function Hessian near the minimum is computed. The result indicates that under some conditions, which are likely fulfilled in most applications, the system is decoupled for the non-smooth components. The result also shows that the structure part in the Hessian is well-conditioned while the aerodynamic part is ill-conditioned. Applications of the result to optimization strategies are discussed.

Arian, Eyal↗
NASA NTRS1982

An optimization technique for lumped-distributed two ports

A frequency domain direct efficient analysis and an optimization technique of a large class of lumped-distributed networks containing active elements are presented. Sensitivity and Hessian matrix calculations are performed using truncated Taylor series expansion of two-port parameters of subnetworks. An interactive computer program was developed to demonstrate the application of the method. Examples of network optimizations are included to illustrate the powerfulness of the technique.

Iobst, K. W.↗
NASA NTRS2003

Analysis and training - why different?

It is tempting to seek universal combat simulations, optimized for both analysis and training. Such a quest would be quixotic, however, because the two environments place conflicting requirements.

simulation modeling training analysis↗
NASA NTRS1992

Optimum design of a gearbox for low vibration

A computer program was developed for designing a low vibration gearbox. The code is based on a finite element shell analysis, a modal analysis, and a structural optimization method. In the finite element analysis, a triangular shell element with 18 degrees-of-freedom is used. In the optimization method, the overall vibration energy of the gearbox is used as the objective function and is minimized at the exciting frequency by varying the finite element thickness. Modal analysis is used to derive the sensitivity of the vibration energy with respect to the design variable. The sensitivity is representative of both eigenvalues and eigenvectors. The optimum value is computed by the gradient projection method and a unidimensional search procedure under the constraint condition of constant weight. The computer code is applied to a design problem derived from an experimental gearbox in use at the NASA Lewis Research Center. The top plate and two side plates of the gearbox are redesigned and the contribution of each surface to the total vibration is determined. Results show that optimization of the top plate alone is effective in reducing total gearbox vibration.

Inoue, Katsumi↗