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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tritium Breeding Ratio Evaluation of Solid Breeder Concepts for the FESS-FNSF

This paper presents a parametric study of the Fusion Energy System Studies-Fusion Nuclear Science Facility’s (FNSF’s) tritium breeding performance for several solid breeder concepts, neutron multiplying materials, and blanket materials, assuming volume fractions based on the most recent FNSF design as a realistically representative fusion facility. In this study, we initially surveyed the tritium breeding ratio (TBR) of several solid breeder concepts by employing a simplified but efficient one-dimensional (1-D) infinite cylinder reduced-order model (ROM). Parametric studies were performed with the ROMs for the full range of breeder-to-multiplier ratios to identify the optimum mixture compositions for each breeder type that would lead to a maximum TBR. These optimized breeder-multiplier combinations were then homogenized with FNSF blanket component materials to estimate their impacts on the TBR. Subsequently, as a validation step for the optimal designs, TBR calculations were performed using a more realistic modified 1-D ROM with inner and outer breeding regions, as well as with a fully detailed 22.5-deg three-dimensional (3-D) sector of the FNSF to assess the impact of geometry details on the TBR. The differences between the two 1-D models were negligible, while the ROMs were able to correctly predict trends and identify the maximum and minimum TBR cases, as well as show consistent biases relative to the results produced by the full 3-D, 22.5-deg sector for specific breeder/multiplier combinations. Solid breeder concepts such as Li 2 O, Li 4 SiO 4 , and Li 8 ZrO 6 outperformed all others in this study in terms of TBR performance when combined with all the neutron multiplier materials selected. Here, an underlying goal of this study was to develop and improve rapid and reliable ROMs to aid designers during parametric optimizations of highly complex and computationally expensive fusion models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Structural Optimization of a Direct-Drive Wind Turbine Generator Inspired by Additive Manufacturing

This study explores the structural freedom and design opportunities of additive manufacturing for a 5-MW direct-drive generator for a wind turbine and compares it to more traditional spoke-arm designs using NREL's GeneratorSE. The work focuses on light-weighting the stator within the generator, complementing previous rotor work. The light-weighting approach uses complex geometries and lattice structures made possible by additive manufacturing to realize increased strength with reduced mass. By reducing the mass at the top of the tower, wind turbines face lower loading along with decreased cost and improved structural stability. Furthermore, an altered bedplate support location facilitates lighter stator designs by better load transfer. Design optimization suggests additive manufacturing has the potential to transform generator designs to realize light-weighting. Since these machines are large, simulation and modeling are essential first steps before future experimental validation.

17 WIND ENERGY↗
DOE OSTI2023

Partial Least Squares, Experimental Design, and Near-Infrared Spectrophotometry for the Remote Quantification of Nitric Acid Concentration and Temperature

Near-infrared spectrophotometry and partial least squares regression (PLSR) were evaluated to create a pleasantly simple yet effective approach for measuring HNO3 concentration with varying temperature levels. A training set, which covered HNO3 concentrations (0.1–8 M) and temperature (10–40 °C), was selected using a D-optimal design to minimize the number of samples required in the calibration set for PLSR analysis. The top D-optimal-selected PLSR models had root mean squared error of prediction values of 1.4% for HNO 3 and 4.0% for temperature. The PLSR models built from spectra collected on static samples were validated against flow tests including HNO 3 concentration and temperature gradients to test abnormal conditions (e.g., bubbles) and the model performance between sample points in the factor space. Based on cross-validation and prediction modeling statistics, the designed near-infrared absorption approach can provide remote, quantitative analysis of HNO 3 concentration and temperature for production-oriented applications in facilities where laser safety challenges would inhibit the implementation of other optical techniques (e.g., Raman spectroscopy) and in which space, time, and/or resources are constrained. The experimental design approach effectively minimized the number of samples in the training set and maintained or improved PLSR model performance, which makes the described chemometric approach more amenable to nuclear field applications.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

The use of multi-objective optimization to improve the design process of nuclear power plant systems

Multi-objective optimization is proposed to address the problem of design optimality in the nuclear power plant design process. This is done via the creation/development of the Optimization and Preference Tool for the Improvement of Nuclear Systems (OPTIONS). This work details applications of multi-objective optimization methods (in Python 3) to two different nuclear system design problems: the flash-Rankine power conversion system (PCS) of the I 2 S-LWR and the Passive Endothermic Reaction Cooling System (PERCS) attached to a standard PWR primary system (in RELAP5). The PCS design problem is first solved for three configurations using a specific particle swarm optimization method, achieving a thermodynamic efficiency of 34.81%. A new method, the Mixed-Integer Non-dominated Sorting Genetic Algorithm (MI-NSGA), is created and then used, solving a PCS superstructure of 22 configurations and achieving an efficiency of 35.63%. Finally, the OPTIONS tool is used to optimize the PERCS, improving cost, core temperature control, and cooling longevity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Pareto Optimization of Analog Circuits Using Reinforcement Learning

Analog circuit optimization and design presents a unique set of challenges in the IC design process. Many applications require the designer to optimize for multiple competing objectives, which poses a crucial challenge. Motivated by these practical aspects, we propose a novel method to tackle multi-objective optimization for analog circuit design in continuous action spaces. In particular, we propose to (i) extrapolate current techniques in Multi-Objective Reinforcement Learning to continuous state and action spaces and (ii) provide for a dynamically tunable trained model to query user defined preferences in multi-objective optimization in the analog circuit design context.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Holistic Portfolio Optimization using Directed Mutations

Genetic algorithms provide attractive options for performing nonlinear multi-objective combinatorial design optimization, and they have proven very useful for optimizing individual systems. However, conventional genetic algorithms fall short when performing holistic portfolio optimizations in which the decision variables also include the integer counts of multiple system types over multiple time periods. When objective functions are formulated as analytic functions, we can formally differentiate with respect to system counts and use the resulting gradient information to generate favorable mutations in the count variables. We apply several variations on this basic idea to an idealized hanging chain example to obtain >> 1000x speedups over conventional genetic algorithms in both single - and multi-objective cases. We develop a more complex example of a notional military portfolio that includes combinatorial design variables and dependency constraints between the design choices. In this case, our initial results are mixed, but many variations are still open to further research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Near-infrared spectral tomography integrated with digital breast tomosynthesis: Effects of tissue scattering on optical data acquisition design

Purpose: Design optimization and phantom validation of an integrated digital breast tomosynthesis (DBT) and near-infrared spectral tomography (NIRST) system targeting improvement in sensitivity and specificity of breast cancer detection is presented. Factors affecting instrumentation design include minimization of cost, complexity, and examination time while maintaining high fidelity NIRST measurements with sufficient information to recover accurate optical property maps. Methods: Reconstructed DBT slices from eight patients with abnormal mammograms provided anatomical information for the NIRST simulations. A limited frequency domain (FD) and extensive continuous wave (CW) NIRST system was modeled. The FD components provided tissue scattering estimations used in the reconstruction of the CW data. Scattering estimates were perturbed to study the effects on hemoglobin recovery. Breast mimicking agar phantoms with inclusions were imaged using the combined DBT/NIRST system for comparison with simulation results. Results: Patient simulations derived from DBT images show successful reconstruction of both normal and malignant lesions in the breast. They also demonstrate the importance of accurately quantifying tissue scattering. Specifically, 20% errors in optical scattering resulted in 22.6% or 35.1% error in quantification of total hemoglobin concentrations, depending on whether scattering was over- or underestimated, respectively. Limited frequency-domain optical signal sampling provided two regions scattering estimates (for fat and fibroglandular tissues) that led to hemoglobin concentrations that reduced the error in the tumor region by 31% relative to when a single estimate of optical scattering was used throughout the breast volume of interest. Acquiring frequency-domain data with six wavelengths instead of three did not significantly improve the hemoglobin concentration estimates. Simulation results were confirmed through experiments in two-region breast mimicking gelatin phantoms. Conclusions: Accurate characterization of scattering is necessary for quantification of hemoglobin. Based on this study, a system design is described to optimally combine breast tomosynthesis with NIRST.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Density based topology optimization of turbulent flow heat transfer systems

The focus of this article is on topology optimization of heat sinks with turbulent forced convection. The goal is to demonstrate the extendibility, and the scalability of a previously developed fluid solver to coupled multi-physics and large 3D problems. The gradients of the objective and the constraints are obtained with the help of automatic differentiation applied on the discrete system without any simplifying assumptions. Thus, as demonstrated in earlier works of the authors, the sensitivities are exact to machine precision. The framework is applied to the optimization of 2D and 3D problems. Comparison between the simplified 2D setup and the full 3D optimized results is provided. A comparative study is also provided between designs optimized for laminar and turbulent flows. Overall, the comparisons highlight the importance and the benefits of full 3D optimization and including turbulence modeling in the optimization process, while also demonstrating extension of the methodology to include coupling of heat transfer with turbulent flows.

42 ENGINEERING↗
DOE OSTI2013

Full-Scale Testing of the Ambient Pressure, Acid-Dissolution Front-End Process for the Current 99 Mo Recovery Processes

The Global Threat Reduction Initiative (GTRI) Conversion Program is actively developing technologies for converting civilian facilities that use high enriched uranium (HEU) to low enriched uranium (LEU) fuels and targets. The conversion of conventional HEU targets to LEU for the production of 99 Mo production requires approximately five times the uranium in a target to maintain the 99 Mo yield on a per-target basis. Under GTRI, Argonne National Laboratory (Argonne) is developing two frontend options for current 99 Mo production processes to allow the use of LEU-foil targets. In both processes, the aim is to produce a frontend product that is compatible with current 99 Mo purification operations and will provide the same or a higher yield of 99 Mo for the same number of irradiated targets. The two frontend processes under development as part of this project are (1) the dissolution of irradiated LEU foil (up to 250 g in a single batch) and nickel fission recoil barrier in nitric acid at ambient pressure; and (2) the electrochemical dissolution of LEU foil in series of steps that produces an alkaline (basic) solution feed for 99 Mo purification. This report describes results from performance tests and design optimization of the ambient pressure, nitric-acid-dissolver system. The design, fabrication, and performance test planning for this system are described in more detail in previous reports (Jerden et al. 2011a,b, 2012). Full-scale demonstrations of both of the frontend processes using irradiated uranium foils are planned to be performed at Oak Ridge National Laboratory this fiscal year.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2013

Embedded Sensors and Controls to Improve Component Performance and Reliability - System Dynamics Modeling and Control System Design

This report documents the current status of the modeling, control design, and embedded control research for the magnetic bearing canned rotor pump being used as a demonstration platform for deeply integrating instrumentation and controls (I&C) into nuclear power plant components. This pump is a highly inter-connected thermo/electro/mechanical system that requires an active control system to operate. Magnetic bearings are inherently unstable system and without active, moment by moment control, the rotor would contact fixed surfaces in the pump causing physical damage. This report details the modeling of the pump rotordynamics, fluid forces, electromagnetic properties of the protective cans, active magnetic bearings, power electronics, and interactions between different dynamical models. The system stability of the unforced and controlled rotor are investigated analytically. Additionally, controllers are designed using proportional derivative (PD) control, proportional integral derivative (PID) control, voltage control, and linear quadratic regulator (LQR) control. Finally, a design optimization problem that joins the electrical, mechanical, magnetic, and control system design into one problem to balance the opposing needs of various design criteria using the embedded system approach is presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Combined Aero and Underhood Thermal Analysis for Heavy Duty Trucks

Aerodynamic analysis of the medium-duty delivery truck was performed to achieve vehicle design optimization. Three dimensional CFD simulations were carried out for several improved designs, with a detailed external component analysis of wheel covers, side skirts, roof fairings, and rounded trailer corners. The overall averaged aerodynamics drag reduction through the design modifications were shown up to 22.3% through aerodynamic considerations alone, which is equivalent to 11.16% fuel savings. The main identified fuel efficiencies were based on second generation devices, including wheel covers, side skirts, roof fairings, and rounded trailer corners. The important findings of this work were; (i) the optimum curvature radius of the rounded trailer edges found to be 125 mm, with an arc length of 196.3 mm, (ii) aerodynamic drag reduction increases with dropping clearance of side skirts between wheels and ground, and (iii) aerodynamic drag reduction increases with an extension of front bumper towards the ground.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Novel Transverse Flux Machine for Vehicle Traction Applications: Preprint

A novel transverse flux machine topology for electric vehicle traction applications using ferrite magnets is presented in this paper. The proposed transverse flux topology utilizes novel magnet arrangements in the rotor that are similar to the Halbach array to boost flux linkage; on the stator side, cores are alternately arranged around a pair of ring windings in each phase to make use of the entire rotor flux that eliminates end windings. Analytical design considerations and finite-element methods are used for an optimized design of a scooter in-wheel motor. Simulation results from finite element analysis (FEA) show that the motor achieved comparable torque density to conventional rare-earth permanent magnet (PM) machines. This machine is a viable candidate for direct-drive applications with low cost and high torque density.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A cross-sectional aeroelastic analysis and structural optimization tool for slender composite structures

A fully open-source available framework for the parametric cross-sectional analysis and design optimization of slender composite structures, such as helicopter or wind turbine blades, is presented. The framework—Structural Optimization and Aeroelastic Analysis (SONATA)—incorporates two structural solvers, the commercial tool VABS, and the novel open-source code ANBA4. SONATA also parameterizes the design inputs, postprocesses and visualizes the results, and generates the structural inputs to a variety of aeroelastic analysis tools. It is linked to the optimization library OpenMDAO. This work presents the methodology and explains the fundamental approaches of SONATA. Structural characteristics were successfully verified for both VABS and ANBA4 using box beam examples from literature, thereby verifying the parametric approach to generating the topology and mesh in a cross section as well as the solver integration. The framework was furthermore exercised by analyzing and evaluating a fully resolved highly flexible wind turbine blade. Computed structural characteristics correlated between VABS and ANBA4, including off-diagonal terms. Stresses, strains, and deformations were recovered from loads derived through coupling with aeroelastic analysis. The framework, therefore, proves effective in accurately analyzing and optimizing slender composite structures on a high-fidelity level that is close to a three-dimensional finite element model.

42 ENGINEERING↗
DOE OSTI2014

Modular Undersea Compressed Air Energy Storage (UCAES) System

This project has been devoted to the design, optimization, and cost analysis of a unique power plant with integral energy storage. The proposed facility combines a novel underwater compressed air energy storage (UCAES) system with a customized gas turbine generator, providing exceptional power management and overall efficiency. Unlike conventional CAES, opportunities for underwater storage are plentiful and proximal to the power grid. The UCAES system provides coastal and island communities a practical means for managing the volatility of large-scale wind and solar power resources. The result is higher renewable energy absorption and improved electrical reliability with reduced fossil fuel consumption. The UCAES power plant is composed of three major subsystems: The underwater air containment system (ACS), the air transport pipe (ATP), and the land-based power conversion system (PCS). The underwater ACS is made up of modular concrete shell units, structurally optimized for minimal material usage while employing conventional production methods and equipment. Each shell is designed to receive and control loose fill or gravel, serving as the ballast. The static nature of the final structures make them an asset to marine habitats and includes features intended to permit safe and cost-effective deployment. The ATP Connects the ACS modules to each other and to the on-land power conversion system and utilizes high density polyethylene (HDPE) pipe for low cost and long life. The PCS Houses the turbine-generator ‘expander modules’, with peak capacity of 12.3 MWe each, engineered from existing gas turbine equipment and includes electrically driven commercial 3-stage intercooled centrifugal compressors, each nominally drawing 6.6 MWe when matching the turbine flow requirements. The subsystems listed above are designed with the intent to serve as building-blocks to achieve a peak power output rating in the 40 to 120 MWe range, with 0.25 to 4 hours of energy storage capacity. The modular facility with integral energy storage provides some remarkable transient maneuvers and load-following features unachievable by competing technologies. The system can operate as a dispatchable power plant with a fuel-to-electric efficiency over 41%; substantially better that the average existing Hawaiian peak power generation assets. Optimal efficiency can be maintained while load-following due to modular PCS design and is operable with a range of liquid or gaseous fuels while meeting the most stringent California (CARB) emission standards. The system can operate as a peaking energy plant in discharge mode. Power ramp-up equivalent to 215% of continuous load rating within 1 second accomplished by simply turning off the electric compressor(s). Contrarily, the system can offer energy absorption during periods of grid surplus generation. The electric compressors may be sequenced on to absorb power within seconds. More moderate transitions are easily achieved with standard compressor control functions. The system offers unique features as compared to energy storage systems. ‘Round-trip efficiency’, as calculated by industry standard methods, is in the 90% range. The PCS equipment has a mean-time between overhauls of 80,000 hours, with maintenance costs of less than $0.005/kW-hr of electricity delivered. The underwater ACS structures and piping employ materials and designs specified to achieve a 75 year life. With the underwater containment modules qualified as a marine habitat, there would be no decommissioning costs. In conjunction with the engineering work invested in the design of the UCAES power plant, Brayton Energy has employed a team of manufacturing specialists, marine construction engineers, and power industry experts to create a comprehensive economic model that captures the many site-related variables and configuration options. The cost results and methodology have been validated by suppliers, engineers, and deployment specialists through a detailed case study on Hawaii. While creation of the parametric cost model was based on inputs specific to Hawaii, the proposed construction and deployment steps were chosen to be general enough to allow extrapolation across locations world-wide. Analysis of the proposed system shows it to be a viable option and addresses the principal challenges described by the Department of Energy by offering competitive costs, validated safety and reliability, consideration of the regulatory environment, and utilization of industry accepted practices and equipment. The UCAES system is recommended for immediate consideration in Hawaii. Estimation of time to complete planning, design, and construction of the facility is anticipated to take 3 to 5 years. Other coastal and island communities world-wide should realize similar benefits; as the results presented in this report are considered generally transferable to other locations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Optimal Membrane Cascade Design for Critical Mineral Recovery through Logic-based Superstructure Optimization

In this work, we extend the superstructure model proposed by Wamble et al. (2022) that considers feed input locations, recycling strategies, split fractions, stage numbers, and membrane area. We include the total number of stages as a decision variable, which might be particularly useful when there is cost as- sociated with adding additional stages. We propose a Generalized Disjunctive Programming (GDP) superstructure model that integrates all the design variables of the system. We also investigate the scalability of the model by varying the number of stages and the number of finite elements per stage to determine the impact on recovery and solution time.

Tran, Norman↗
DOE OSTI2023

Noise Optimization for MKIDs with Different Design Geometries and Material Selections

The separation and optimization of noise components is critical to microwave-kinetic inductance detector (MKID) development. We analyze the effect of several changes to the lumped-element inductor and interdigitated capacitor geometry on the noise performance of a series of MKIDs intended for millimeter-wavelength experiments. We extract the contributions from two-level system noise in the dielectric layer, the generation-recombination noise intrinsic to the superconducting thin-film, and system white noise from each detector noise power spectrum and characterize how these noise components depend on detector geometry, material, and measurement conditions such as driving power and temperature. We observe a reduction in the amplitude of two-level system noise with both an elevated sample temperature and an increased gap between the fingers within the interdigitated capacitors for both aluminum and niobium detectors. We also verify the expected reduction of the generation-recombination noise and associated quasiparticle lifetime with reduced inductor volume. This study also iterates over different materials, including aluminum, niobium, and aluminum manganese, and compares the results with an underlying physical model.

generation-recombination noise↗
DOE OSTI2022

[Retracted] Research on Application Experience Design of Ice and Snow Sports Equipment Based on Bee Colony Model

Sports equipment is the key to the smooth development of ice and snow sports. With the rapid development of social economy and the improvement of people’s living standards, the demand for ice and snow sports equipment is increasing day by day. This article presents an improved method based on the chaos theory and the bee colony algorithm to quantify the application experience design of ice and snow sports equipment and reduce the influence of uncertain factors on the design results. First, the chaos theory can establish the dataset of application experience design and analyze the discreteness of the set. According to the bee colony algorithm, the dataset is divided into several groups, and each group obtains the best application experience design by using the design optimization strategy. Finally, the results are mixed to obtain the final experience design results. Through MATLAB simulation analysis and verification, the improved bee colony model can improve the accuracy of application experience design of ice and snow sports equipment in an uncertain environment, shorten the overall design time, and meet the requirements of application experience design of different ice and snow sports equipment. Therefore, the model proposed in this paper is suitable for the application experience design of ice and snow sports equipment.

Li, Yuanjing (ORCID:000000018276647X)↗