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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Design and Analysis of High Heat Flux Plasma-Facing Components for NSTX Upgrade

The National Spherical Tokamak Experiment (NSTX) upgrade (NSTX-U) requirements lead to enhanced heat loads on plasma-facing components (PFCs) especially in the divertor regions, where normal heat flux density can reach up to 8 MW/m 2 . For these high heat flux (HHF) regions, the PFCs were redesigned, to use castellations which relieved the thermal stresses associated with high incident heat flux. Another design feature of HHF PFCs is the absence of front face mounting holes which create localized areas of high temperature and thermal stress concentrations. Optimized shaping of the front face of the HHF PFCs eliminates regions where the front face is perpendicular to the heat flux direction during normal helicity operation and spreads the heat load. A unique mechanism was designed to connect PFC tiles to the NSTX-U center stack casing using locking features accessible from the low heat flux regions. Isotropic graphite was selected as the HHF PFC tile material. Initial tile design parameters were accessed using analytical expressions for pulsed heat flux loading. A working prototype of the locking mechanism was created during the initial stages of the design to prove the concept performance. This article presents an overview of the divertor HHF PFC design and the results of the thermal and structural analyses performed using ANSYS software. The results of the analyses cover normal operating conditions and disruptions which impose electromagnetic (EM) loads from eddy and halo currents. The 3-D, transient, nonlinear analyses took into account the temperature-dependent properties of the materials, friction interfaces between the parts, and variable electric properties of the parts and interfaces. The results confirm that the HHF PFC tiles remain within the allowable limits for the loads defined by the NSTX-U Recovery Project. In addition, tolerance stack up analyses were performed to ensure tile performance in the worst possible assembly configuration. Finally, the design process was completed successfully, and the NSTX HHF PFC tiles are currently in the production phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Control System of Multi-Port Autonomous Reconfigurable Solar Power Plant (MARS) & HIL Platforms for Design

Multi-port autonomous reconfigurable solar power plant (MARS) provides an attractive alternative to connect photovoltaic (PV) and energy storage systems (ESSs) to high-voltage direct current (HVdc) links and high-voltage alternating current (ac) grids. In this paper, a unique hierarchical control system of MARS is proposed and evaluated. To evaluate the control system and associated algorithms in early-stage research of complex architectures like MARS, it is important to develop unique suitable hardware-in-the-loop (HIL) platforms. In this paper, the HIL platforms for MARS to evaluate the performance of the hierarchical control system and the control algorithms implemented are presented. Further, they help with the design process of control systems. The real-time simulation models and algorithms that are utilized for MARS in the HIL platforms are also discussed in the paper. The HIL experiments of the control system of MARS showcase the capability to provide continuity of operation under faults and frequency support to the power grid during loss of generation. They also showcase the stability of the proposed hierarchical control system of MARS.

14 SOLAR ENERGY↗
DOE OSTI2022

Mild hybridisation of turboprop engine with high-power-density integrated electric drives

Here this paper shares with the aerospace community a case study of turboprop mild hybridisation using a recently developed integrated drive system in the University of Nottingham, UK, within the ACHIEVE project under EU H2020 CleanSky 2 program (project No. 737814). The developed drive system enables green taxiing of a turboprop aircraft while on the ground with its engine off, and as an electrical generator when the turboprop is in the air. The entire system is designed to be able to integrate within the power auxiliary gear box (PAGB) of a turboprop aircraft. Some of the key features of the developed system include a high-speed permanent magnet machine (up to 14,200rpm) with dual three-phase design, SiC-based high power density (11.8kW/L for the power converter, 35.3kW/L and 7.2kW/kg for the machine active parts), integrated cooling design for high-temperature operation (>130°C ambient temperature), fault tolerance consideration with dual channel operation capabilities and sensorless control for entire operational conditions. This paper is giving an overview of the design process of the electrical machine, power converters, and its cooling of the entire drive. Numerical analysis (FEM and CFD) and some experimental results are presented to demonstrate the effectiveness and the desired performance of the developed integrated drive system.

42 ENGINEERING↗
DOE OSTI2022

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multiphysics Co-Optimization Design and Analysis of Double-Side Cooled Silicon Carbide-Based Power Module: Preprint

With the rapid growth of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), much more rigorous design targets have been set for automotive power electronics, including high power density, high reliability, and low cost. Novel power module and inverter technologies based on wide bandgap (WEG) semiconductors have been developed to meet these design targets, while providing optimal power semiconductor operating temperature and promising thermomechanical performance. Compared with conventional cooling techniques which are normally applied only on one side of power module, double-side cooling approach is now believed to be the solution to enable high power density and low thermal resistance of WEG semiconductor-based power electronics. In this work, we develop a three-phase power module that is double-sided cooled using dielectric fluid jet impingement. In each phase, four silicon carbide (SiC) power semiconductors are bonded to copper busbars without electrical insulation layers. A finite element analysis (FEA) model is created for thermal and thermomechanical analysis. Based on FEA modeling results, we select particular dimensions for a parametric study to optimize thermal and mechanical performance. Using a multi-objective genetic algorithm (MOGA)-based optimization method, we have minimized the maximum junction temperature and thermal stresses within the power module. The multiphysics co-optimization approach has enabled an efficient design process of power modules with greatly reduced computational cost, as compared to conventional processes that rely on exhaustive numerical simulations and iterations.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

MoorDyn V2: New Capabilities in Mooring System Components and Load Cases

MoorDyn, an open-source mooring dynamics model, is being expanded with capabilities for additional mooring system features and load cases. As floating wind turbine technology matures, mooring systems are becoming more sophisticated and more complex scenarios need to be considered in the design process. Mooring systems may have synthetic line materials, ballast/buoyancy bodies along the lines, or interconnections between platforms. Failure modes may involve multiple cascading line failures that depend on mooring system dynamics. Features recently added to MoorDyn aim to address these emerging needs. MoorDyn’s linear elasticity model has been supplemented to support user-defined stress-strain curves, which can be adjusted to represent synthetic mooring materials. Rigid six-degree-of-freedom bodies in the mooring system can now be modeled using two new model objects. “Rod” objects provide an option for rigid cylindrical bodies. They use the existing Morison equation-based hydrodynamics model and can be connected to mooring lines at either end. “Body” objects provide a generic six-degree-of-freedom rigid-body representation based on a lumped-parameter model of translational and rotational properties. Rod objects can be added to Body objects and mooring lines can be attached at any location, allowing a wide variety of submerged structures to be integrated into the mooring system. Lastly, a means of dynamically simulating mooring line failures has been implemented. These new features, currently in the C++ version of MoorDyn, are described and then demonstrated on a two-turbine shared-mooring array. A qualitative view of the results suggests the new features are functioning as expected.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2024

Subsampling of Parametric Models with Bifidelity Boosting

Least squares regression is a ubiquitous tool for building emulators (a.k.a. surrogate models) of problems across science and engineering for purposes such as design space exploration and uncertainty quantification. When the regression data are generated using an experimental design process (e.g., a quadrature grid) involving computationally expensive models, or when the data size is large, sketching techniques have shown promise at reducing the cost of the construction of the regression model while ensuring accuracy comparable to that of the full data. However, random sketching strategies, such as those based on leverage scores, lead to regression errors that are random and may exhibit large variability. To mitigate this issue, we present a novel boosting approach that leverages cheaper, lower-fidelity data of the problem at hand to identify the best sketch among a set of candidate sketches. This in turn specifies the sketch of the intended high-fidelity model and the associated data. We provide theoretical analyses of this bifidelity boosting (BFB) approach and discuss the conditions the low- and high-fidelity data must satisfy for a successful boosting. In doing so, we derive a bound on the residual norm of the BFB sketched solution relating it to its ideal, but computationally expensive, high-fidelity boosted counterpart. Finally, empirical results on both manufactured and PDE data corroborate the theoretical analyses and illustrate the efficacy of the BFB solution in reducing the regression error, as compared to the nonboosted solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Electro-Oxidative Dehydrogenation of Ethane to Ethylene Using Lanthanum-Strontium-Iron Oxide Perovskite Electrocatalysts

Developing alternative, industrially viable ethylene production routes has received important research attention. One chemical pathway of interest is the oxidative dehydrogenation (ODH) of ethane, although issues such as product selectivity, combustion hazards, and oxidizer supply have hindered the practical scale-up of this technology. The presented work describes the use of a solid oxide fuel cell (SOFC) platform employing lanthanum-strontium-iron oxide perovskite (La 1-x Sr x FeO 3-δ , or LSFx) electrocatalysts to perform electrochemical-ODH (e-ODH), a process design that has the potential to address the challenges of ODH implementation. The effects of La and Sr stoichiometry, operating temperature, and current density are reported. The highest performance was observed using a La:Sr ratio of 0.50 (LSF0.50) at 750 °C and a current density of 0.50 A·cm –2 , achieving an ethane conversion of 18.7 ± 0.3%, ethylene selectivity of 91.4 ± 1.9%, and ethylene yield of 17.1 ± 0.1%. These results demonstrate several potential advantages for utilizing a SOFC platform to perform e-ODH of ethane to ethylene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Uniform Field Electrode Generator

SAND2025-03788O Uniform Field Electrode Generator is a user-friendly tool designed to create uniform electric field electrodes, essential for high voltage applications. By generating electrodes with precise dimensions, it ensures a consistent electric field across their surfaces. This software is particularly beneficial for researchers and engineers working on projects like closing switches and studying power flow in advanced systems, such as the Z machine. Its unique approach simplifies the design process, making it accessible for users without technical expertise, while enhancing the efficiency and effectiveness of their electrical applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Mason, Tyler [Sandia National Lab. (SNL-CA), Liver↗
DOE OSTI2025

Plant Reload Optimization (prlo)

The PRLO framework is built on a modular and extensible architecture that tightly couples advanced evolutionary optimization algorithms with nuclear fuel depletion solvers (i.e., nuclear physics neutronics code). It supports exploring complex, high-dimensional design spaces constrained by user-specified operational, safety, and economic constraints. Objectives such as minimizing fresh fuel enrichment, flattening radial and axial power distributions, and maximizing discharge burnup are evaluated. PRLO’s equilibrium cycle optimization capability enables the identification of core configurations that maintain fuel cycle sustainability over extended planning horizons. Its integration with the RAVEN platform facilitates optimization of loading patterns or fuel shuffling schemes across multiple cycles. The interface with SIMULATE, a licensed industry-standard nodal code developed by Studsvik, ensures accurate neutronic and thermal-hydraulic feedback for reactor core design. PRLO’s automated workflow engine supports iterative design refinement, enabling utilities to streamline core design processes and meet evolving performance and regulatory targets.

Kim, Junyung [Idaho National Laboratory] (00090005↗
DOE OSTI2023

Levels of Digitization, Digitalization, and Automation for Advanced Reactors

Much has been written about levels of automation (LOA), but comparatively little has been written about levels of digitization (LODi) and levels of digitalization (LODa). Digitization is a digital representation of analog information and is typical of migration from analog to digital control systems, digitalization involves enhancing the functionality of digital information, and automation changes control from humans to machines. Each of these technology implementations has its own scales, and each forms a viable type of functionality that should be considered not as a continuum toward automation but rather as separate categories of solutions that meet the needs of advanced reactors. In this paper we develop separate LODi, LODa, and LOA scales and demonstrate how conflation of these technologies, using the example of computer-based procedures, can lead to confusion in the design process. With the race to develop advanced reactors, the surest metric of success and safety is proper consideration of the right technology requirements for different control systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

From the bench to the reactor: engineered filamentous fungi for biochemical and biomaterial production

Filamentous fungi can convert a wide variety of naturally occurring chemical compounds, including organic biomass and waste streams, into a range of products. They have long been used for industrial organic acid production and food preparation. In this review, we will discuss production of products such as organic acids, lipids, small molecules, enzymes, materials, and foods, and highlight advances in metabolic and protein engineering, including CRISPR-Cas9-mediated strain improvements. We discuss to what extent these products are already being made on a commercial scale, as well as what is still required to make certain promising concepts industrially and commercially relevant. Despite significant progress, the systematic application of synthetic biology to filamentous fungi remains in its infancy, with many opportunities for discovery and innovation as new strains and genetic tools are developed. The integration of fungal biotechnology into circular and bio-based economies promises to address critical challenges in waste management, resource sustainability, and the development of new materials for terrestrial and extraterrestrial applications, but requires further developments in genetic engineering and process design.

09 BIOMASS FUELS↗
DOE OSTI2023

Sustainability Engineering: Challenges, Technologies, and Applications

Sustainability Engineering: Challenges, Technologies, and Applications focuses on emerging topics within sustainability science and engineering, including the circular economy, advanced recycling technologies, decarbonization, renewable energy, and waste valorization. Readers will learn the trends driving today's sustainability research and innovation as well as the latest in sustainable process technologies. This book: addresses emerging sustainability development challenges, progress, and disruptive technologies; discusses biological sustainability, recycling technologies, and sustainable process design and manufacture; and features a comprehensive view from renowned experts who are leaders in their respective research areas. This work is aimed at an interdisciplinary audience of engineers and scientists working on solutions to advance the development and application of sustainable technologies, including - but not limited to - chemical and environmental engineers.

advanced recycling technologies↗
DOE OSTI2020

Polymer genome–based prediction of gas permeabilities in polymers

Abstract Predicting gas permeabilities of polymers a priori is a long-standing challenge within the membrane research community that has important applications for membrane process design and ultimately widespread adoption of membrane technology. From early attempts based on free volume and cohesive energy to more recent group contribution methods, the ability to predict membrane permeability has improved in terms of accuracy. However, these models usually stay “within the paper”, i.e. limited model details are provided to the wider community such that adoption of these predictive platforms is limited. In this work, we combined an advanced polymer chemical structure fingerprinting method with a large experimental database of gas permeabilities to provide unprecedented prediction precision over a large range of polymer classes. No prior knowledge of the polymer is needed for the prediction other than the repeating unit chemical formula. In addition, we have incorporated this model into the existing Polymer Genome project to make it open to the membrane research community.

Polymer Science↗
DOE OSTI2025

Directed self-assembly of block copolymers for high-precision patterning in the era of extreme ultraviolet lithography

Extreme ultraviolet (EUV) lithography enables unprecedented resolution in semiconductor patterning but faces critical challenges in developing resist materials that achieve high-precision at economically viable throughput. Directed self-assembly (DSA) of block copolymers (BCPs) offers a promising solution for pattern rectification by leveraging thermodynamically determined domain structures to decouple BCP pattern quality from the imperfect original lithographic pattern. This prospective presents an overview of recent progress on the EUV + DSA strategy, covering advances in BCP material design, processing, metrology, and pattern transfer. We highlight recent advances in high-χ BCPs with perpendicular orientation and domain spacings compatible with EUV dimensions, leveraging A-b-(B-r-C) architectures. We also discuss progress in chemical pre-pattern fabrication using both positive- and negative tone resists, along with processing strategies to minimize defects and roughness based on BCP thermodynamics and assembly kinetics. We further examine metrology platforms for characterizing the thermodynamics of BCP materials and quantifying the size and shape of BCP domains. Lastly, we review pattern transfer strategies for generating functional inorganic masks suitable for semiconductor manufacturing. Together, these advances highlight the potential of DSA to complement EUV lithography, offering a pathway to address critical challenges in achieving high-precision patterning for the semiconductor industry.

Lee, Kyunghyeon [Univ. of Chicago, IL (United Stat↗
DOE OSTI2021

An Evolutionary Algorithm Approach to Multi-Pass ERL Optics Design

An Energy Recovery Experiment at CEBAF (ER@CEBAF) is aimed at demonstrating high energy, low current, multi-pass energy recovery at the existing 12 GeV CEBAF accelerator. The beam break-up instability, limiting the maximum beam current, can be controlled through minimizing beta functions for the lowest energy pass, which gives a preference to strongly focusing optics, e.g. a semi-periodic FODO lattice. On the other hand, one needs to limit beta function excursions, caused by under focusing, at the higher energy passes, which in turn favors weakly focusing linac optics. Balancing both effects is the main objective of proposed multi-pass linac optics optimization. Here, we discuss an optics design process for ER@CEBAF transverse optics using a genetic algorithm.

Neththikumara, I.↗
DOE OSTI2023

Modeling for the phased injector upgrade for 12 GeV CEBAF

As a follow on to the 12 GeV upgrade to the Continuous Electron Beam Accelerator Facility, the front end of the DC photo-gun-based injector has gone through a phased upgrade. The first phase focused on the beamline between the gun and the RF chopper system, and the second phase addresses the beamline after the RF chopper system including replacing the capture section and quarter cryomodule with a new booster module containing a 2-cell and 7-cell cavity string. Throughout the design process, we maintained and developed three models, one for the existing injector and one for each of the upgrade phases. With these models, we evaluated proposed hardware upgrades, evaluated and determined optimized beamline element positions, developed buncher voltage requirements, and settings for optimal injector running. In this paper, we will describe the models and results from these various studies and provide a brief summary of Phase 1 commissioning.

Kazimi, R.↗
DOE OSTI2024

Equilipy: a python package for calculating phase equilibria

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

97 MATHEMATICS AND COMPUTING↗