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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design and Optimization of High-frequency Transformer for Isolated Single-Stage Three-Phase AC/DC Converter using Bidirectional Switches

This paper presents the design and optimization of the high-frequency transformer for an isolated single-stage threephase AC/DC converter enabled by the 4H-SiC BiDirectional Field Effect Transistor (BiDFET). Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to perform a multiobjective optimization to minimize loss, weight, and volume. A 20 kW, 50 kHz hardware prototype based on the selected optimal point is characterized by a power amplifier. The finite element analysis simulation results are also presented to validate the core magnetic flux density and winding electric field strength. The experimental prototype was tested at 800 Vdc/480 Vrms at 10 kW rated power.

BiDFET, High-frequency transformer, Multiobjective↗
DOE OSTI2026

Consequential improvement acquisition function for efficient multi-fidelity Bayesian optimization

Abstract Surrogate-based Bayesian optimization has been widely applied in design optimization to increase sampling efficiency. However, the cost for each evaluation of the objective function can still be very high when physical experiments or large-scale simulations are involved. Multi-fidelity Bayesian optimization is the new approach to further improve the sampling efficiency by reducing the number of expensive samples at the highest fidelity level and supplementing them with less expensive ones at low-fidelity levels. In this paper, a new consequential improvement (CI) acquisition function is proposed to allow for the simultaneous selection of the solution and the fidelity level in problems with a known hierarchy of fidelity levels. The new CI acquisition function incorporates the consequential effectiveness of objective improvement with the considerations of cost, accuracy, and validity differences between high- and low-fidelity samples in engineering practice. The new method of multi-fidelity Bayesian optimization based on the CI is demonstrated with several analytical and simulation-based design examples. In the simulation-based design optimization example, the results show that the CI acquisition function has a decisive advantage in the sampling efficiency over the other methods of multi-fidelity Bayesian optimization with simultaneous selection. The results indicate that the proposed method is particularly advantageous in solving high-dimensional problems and when large cost ratios between high- and low-fidelity evaluations exist and high-fidelity validation is mandatory. Furthermore, the method robustly avoids the prevalent issue of over sampling at low-fidelity levels.

Aydogdu, Ibrahim [Georgia Institute of Technology,↗
DOE OSTI2021

Design and Optimization of the Direct Recycling of Spent Li-Ion Battery Cathode Materials

Direct regeneration of spent Li-ion batteries based on the hydrothermal relithiation of cathode materials is a promising next-generation recycling technology. In order to demonstrate the feasibility of this approach at a large scale, we systematically design and optimize the process parameters to minimize both energy and raw material costs. Specifically, the effects of regenerative processing parameters on the composition, structure, and electrochemical performance of the regenerated cathode materials are investigated via systematic characterization and testing. From this analysis, it was found that the raw material costs can be substantially reduced by either replacing the typically employed 4 M LiOH solution by a cost-effective mixture of 0.1 M LiOH and 3.9 M KOH or recycling of the concentrated 4 M LiOH for continuous relithiation processes. Finally, life cycle analysis suggests that this strategy results in reduced energy consumption and greenhouse gas emissions, leading to an increased potential revenue, particularly when compared with hydro- and pyrometallurgical recycling methods.

25 ENERGY STORAGE↗
DOE OSTI2023

Bayesian optimal experimental design for constitutive model calibration

Computational simulation is increasingly relied upon for high/consequence engineering decisions, which necessitates a high confidence in the calibration of and predictions from complex material models. However, the calibration and validation of material models is often a discrete, multi-stage process that is decoupled from material characterization activities, which means the data collected does not always align with the data that is needed. To address this issue, an integrated workflow for delivering an enhanced characterization and calibration procedure—Interlaced Characterization and Calibration (ICC)—is introduced and demonstrated. Further, this framework leverages Bayesian optimal experimental design (BOED), which creates a line of communication between model calibration needs and data collection capabilities in order to optimize the information content gathered from the experiments for model calibration. Eventually, the ICC framework will be used in quasi real-time to actively control experiments of complex specimens for the calibration of a high-fidelity material model. This work presents the critical first piece of algorithm development and a demonstration in determining the optimal load path of a cruciform specimen with simulated data. Calibration results, obtained via Bayesian inference, from the integrated ICC approach are compared to calibrations performed by choosing the load path a priori based on human intuition, as is traditionally done. The calibration results are communicated through parameter uncertainties which are propagated to the model output space (i.e. stress–strain). In these exemplar problems, data generated within the ICC framework resulted in calibrated model parameters with reduced measures of uncertainty compared to the traditional approaches.

42 ENGINEERING↗
DOE OSTI2017

Additive manufacturing: Toward holistic design

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimization-based Design for Manufacturing

This report provides detailed documentation of the algorithms that where developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.

42 ENGINEERING↗
DOE OSTI2023

Thrust-optimized blade design for wind turbines

A wind rotor is disclosed that produces energy optimally for a given thrust overturning moment. By designing rotors with suboptimal aerodynamic efficiency, they can have optimal thrust performance, which will reduce the substructure cost and/or enable greater energy capture for a given substructure.

17 WIND ENERGY↗
DOE OSTI2018

Design and optimization of nanoparticle-pigmented solar selective absorber coatings for high-temperature concentrating solar thermal systems

In this paper, we present a systematic approach for the design and optimization of nanoparticle-pigmented solar selective absorbers for operation at 750 °C. Using the scattering and absorption cross-sections calculated by Lorenz-Mie scattering theory as input, we employ a four-flux radiative transfer method to investigate the solar selectivity mechanism and optimize the optical-to-thermal conversion efficiency (η therm ) as a function of the metallic nanoparticle material, the nanoparticle diameter, the volume fraction, and the coating thickness. Among the nanoparticle material candidates in this study, C54-TiSi 2 is the best option with an optimized η therm = 87.0% for a solar concentration ratio of C = 100 and η therm = 94.4% for C = 1000 at 750 °C. NiSi is also a promising candidate comparable to TiSi 2 in thermal efficiency, Experimentally, an un-optimized 200 nm-diameter TiSi 2 nanoparticle-silicone solar selective coating has already achieved η therm = 89.8% for C = 1000 at 750 °C. This performance is consistent with the theoretical model and close to the thermal efficiency of the commercial Pyromark 2500 coatings (90.1%). We also demonstrate that Ni/NiSi core-shell structures embedded in the SiO 1.5 matrix is thermally stable at 750 °C for 1000 h in air. Lastly, these results indicate that silicide cermet coatings are promising to achieve high optical performance and high temperature thermal stability simultaneously.

14 SOLAR ENERGY↗
DOE OSTI2022

Transformational Challenge Reactor – On the Application of Design for Additive Manufacturing (DfAM) Techniques to the Conception of Nuclear Core

Additive manufacturing (AM) technologies are radically changing the way objects are designed and manufactured. They allow building by deposition and solidification of material layer by layer, enabling the possibility to create simple and complex features alike, almost seamlessly. Generally, the design optimization process requires to define objectives, design variables and constraints. Additive manufacturing does not challenge this process per se but does allow designers to completely redefine the constraints space as the ones originating from fabrication can be considerably relaxed compared to more “traditional” manufacturing. Thus, design optimization becomes naturally far more responsive to the actual physics being solved and considerably less influenced by fabrication limitations, leading to dramatically different designs. To take advantage of these new opportunities, so-called Designing for Additive Manufacturing (DfAM) techniques are emerging. Development of design techniques specifically tailored for additive manufacturing is warranted because, considering AM, the design space is typically considerably larger than with traditional manufacturing. The ability to explore the design space efficiently is of paramount importance for designers. This study proposes to investigate and apply some of these DfAM techniques to the conception of nuclear core. The goal being to assess if these new methods can be applied to core design and if core design could benefits from additive manufacturing technologies. After a brief investigation on the pertinence of some DfAM techniques for core design, algorithms are proposed and a workflow is established to carry neutronics and steady-state thermal-hydraulics analyses. To diminish the work load, the workflow has been automated using python modules. These modules allow the rapid creation of input files, post-treatment of output files and visualization. To test the pertinence of the proposed workflow, three test cases have been investigated: a research and test reactor, a micro-reactor and a space propulsion reactor. These test cases offered a variety of objectives, constraints and operating conditions. It is observed that the proposed workflow is capable of converging quickly and efficiently to valid design solutions. It is then concluded that DfAM techniques can be applied to core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Design and optimization of a bi-axial vibration-driven electromagnetic generator

To scavenge energy from ambient vibrations with arbitrary in-plane motion directions and over a wide frequency range, a novel electromagnetic vibration energy harvester is designed and optimized. In the harvester, a circular cross-section elastic rod, not a traditional thin cantilever beam, is used to extract ambient vibration energy because of its capability to collect vibration from arbitrary in-plane motion directions. The magnetic interaction between magnets and the iron core contributes to a nonlinear oscillation of the rod with increased frequency bandwidth. The influences of the structure configurations on the electrical output and the working bandwidth of the harvester are investigated using Ansoft's Maxwell 3D to achieve optimal performance. The experimental results show that the harvester is sensitive to vibrations from arbitrary in-plane directions and it exhibits a bandwidth of 5.7 Hz and a maximum power of 13.4 mW at an acceleration of 0.6 g (with g=9.8 ms⁻²).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Review of Shape and Topology Optimization for Design of Air-to-Refrigerant Heat Exchangers

Air-to-refrigerant heat exchangers (HXs) have been the topic of exhaustive research as they are fundamental components of HVAC&R systems. It has been well-established that the large airside thermal resistance dominates the HX thermal resistance, and thus significant research efforts have focused on improving the air-side performance of these heat exchangers. As HXs continue to become more compact, thermal resistance reduction is typically realized through the utilization of extended secondary heat transfer surfaces such as fins. However, past research has shown that the thermal-hydraulic trade-offs provided by fins are often not attractive enough to warrant their use, especially for small diameter tubes. Yet, the inadequate primary surface area provided by compact HXs essentially mandate the necessity of fins to meet thermal resistance requirements. In recent years, advancements in computational tools such as Computational Fluid Dynamics (CFD) and optimization algorithms, coupled with the advent of additive manufacturing technologies, have allowed engineers to expand conventional HX design ideologies to include such concepts as shape and topology optimization. This lends itself directly to primary heat transfer surface optimization and even the potential removal of finned surfaces altogether. This paper presents a comprehensive literature review investigating air-to-refrigerant HX shape and topology optimization. The fundamentals of both shape and topology optimization, model development, and experimental validations are all separately discussed. Studies featuring manufactured prototypes and/or experimentally validated optimal designs are treated with additional emphasis. This paper concludes by identifying key research gaps and proposing future research directions for HX shape and topology optimization.

42 ENGINEERING↗
DOE OSTI2021

Aero-structural design and optimization of 50 MW wind turbine with over 250-m blades

The quest for reduced levelized cost of energy has driven significant growth in wind turbine size; however, larger rotors face significant technical and logistical challenges. The largest published rotor design is 25 MW, and here we consider an even larger 50 MW design with blade length over 250 m. This paper shows that a 50 MW design is indeed possible from a detailed engineering perspective and presents a series of aero-structural blade designs, and critical assessment of technology pathways and challenges for extreme-scale rotors. The 50 MW rotor design begins with Monte Carlo simulations focused on optimizing carbon spar cap and root design. A baseline design resulted in a 250-m blade with mass of 502 tonnes. Subsequently, an aero-structural design and optimization were performed to reduce the blade mass/cost with more than 25% mass reduction and 30% cost reduction by determining optimal blade chord and airfoil thickness for best aero-structural performance.

Yao, Shulong↗
DOE OSTI2023

Mutual-information based optimal experimental design for hyperpolarized $$^{13}$$C-pyruvate MRI

Abstract A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, $$k_{{\textrm PL}}$$ k P L , for measuring tumor metabolism. This manuscript presents an information-theory-based optimal experimental design approach that minimizes the uncertainty in the rate parameter, $$k_{{\textrm PL}}$$ k P L , recovered from HP-MRI measurements. Mutual information is employed to measure the information content of the HP measurements with respect to the first-order exchange kinetics of the pyruvate conversion to lactate. Flip angles of the pulse sequence acquisition are optimized with respect to the mutual information. A time-varying flip angle scheme leads to a higher parameter optimization that can further improve the quantitative value of mutual information over a constant flip angle scheme. However, the constant flip angle scheme, 35 and 28 degrees for pyruvate and lactate measurements, leads to an accuracy and precision comparable to the variable flip angle schemes obtained from our method. Combining the comparable performance and practical implementation, optimized pyruvate and lactate flip angles of 35 and 28 degrees, respectively, are recommended.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Coordinated Optimal Control of Constrained DERs

In this paper, a coordinated optimal control is designed to simultaneously satisfy multiple power system objectives at the distribution network level. With high penetration of renewables, traditional generation and control may not be enough to compensate for intermittent changes in net load. Dynamic coordination of battery storage devices and demand response at aggregated distributed energy resource (DER) sites becomes necessary to maintain power system operation, however, each dynamic power component operates at different time scales. Frequency stabilization can be achieved by designing optimal controls for traditional generation, storage devices and demand response. The proposed optimal controls naturally render frequency separation of these load balancing mechanisms. Given a 24-hour net load forecast, optimal tracking control inputs are designed subject to constraints of selected system elements to ensure optimal performance of the power system. Simulation results are presented and discussed.

Harvey, Roland↗
DOE OSTI2025

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.

active learning↗
DOE OSTI2021

Design and optimization of the RF input-coupler for a low-frequency, split-coaxial RFQ

The Isotope Decay-At-Rest experiment (IsoDAR) is a proposed underground experiment which is expected to be a definitive search for sterile neutrinos. In order to be decisive within 5 years, high rates of neutrinos must be produced, by impinging a 10 mA continuous wave proton beam at 60 MeV on a high power target. Due to space restrictions, a compact cyclotron was chosen as an accelerator to produce this driver beam. To overcome space charge limitations during injection, H 2 + ions are accelerated and later stripped into protons by means of a carbon foil. IsoDAR uses an especially designed low-frequency (32.8 MHz) split-coaxial Radio-Frequency Quadrupole (RFQ) to effectively bunch H 2 + ions before injecting them into this cyclotron. The RFQ will be embedded vertically in the cyclotron yoke, facilitating a very compact design. This puts stringent limits on RFQ size, type, and accessibility. Here, we present the design and optimization of the low-frequency (32.8 MHz) RF input-coupler for the IsoDAR RFQ. The design is challenging due to the necessarily small diameter of the RFQ (28 cm) and the split-coaxial type, as well as limited access to the RFQ. We have determined the optimal position and shape for the coupler, leading to a low power consumption of < 6 kW for an inter-vane voltage of 22 kV. Finally, the highest calculated fields are safely below the Kilpatrick limit for this structure.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

An open source fast fluid dynamics model for data center thermal management

Although computational fluid dynamics (CFD) has been widely adopted to improve data center thermal management, the high computational demand limits its applications, such as multivariate optimal design and operation. Fast fluid dynamics (FFD), which has been applied for fast airflow simulation, shows great potential. However, few research applied FFD for optimal design and operation of data center thermal management. This research improves the FFD model for data centers and conducts a comprehensive evaluation and demonstration. First, the FFD model is improved by solving the advection and diffusion equations together using an upwind scheme instead of a semi-Lagrangian advection solver in the conventional FFD model. Second, new features for data centers are added, such as a pressure correction method to simulate plenum airflow and dynamic boundary conditions for IT racks. The new FFD model is first validated with two indoor environment cases and the results show that the new FFD model has slightly better overall prediction accuracy and faster speed compared to the conventional FFD model. It is also observed that both FFD models achieve acceptable accuracy, except for a few localized disparities with experimental data, which might be due to simplified handling of turbulence viscosity near the boundaries. Furthermore, validation with a real data center shows that the FFD model achieves a similar level of accuracy as CFD when compared to the experimental measurements with some level of uncertainties. It is then demonstrated for data center optimal design and operation, which saves 53.4–58.8% of annual energy while still meeting the thermal requirements. In conclusion, with a much faster speed and comparable accuracy compared to CFD, the FFD model parallelized on a graphics processing unit is promising for practical model-based data center early design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗