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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Pore-scale study of effects of macroscopic pores and their distributions on reactive transport in hierarchical porous media

For applications of reactive transport in porous media, optimal porous structures should possess both high surface area for reactive sites loading and low mass transport resistance. Hierarchical porous media with a combination of pores at different scales are designed for this purpose. In this paper, using the lattice Boltzmann method, pore-scale numerical studies are conducted to investigate diffusion-reaction processes in 2D hierarchical porous media generated by self-developed reconstruction scheme. Complex interactions between porous structures and reactive transport are revealed under different conditions. Simulation results show that adding macropores can greatly enhance the mass transport, but at the same time reduce the reactive surface, leading to complex change trend of the total reaction rate. Effects of gradient distribution of macropores within the porous medium are also investigated. It is found that a front-loose, back-tight (FLBT) hierarchical structure is desirable for enhancing mass transport, increasing total reaction rate, and improving catalyst utilization. Finally, on the whole, from the viewpoint of reducing cost and improving material performance, hierarchical porous structures, especially gradient structures with the size of macropores gradually decreasing along the transport direction, are desirable for catalyst application.

42 ENGINEERING↗
DOE OSTI2023

Enabling scientific machine learning in MOOSE using Libtorch

A neural-network-based machine learning interface has been developed for the Multiphysics Object-Oriented Simulation Environment (MOOSE). The interface relies on Libtorch, the C++ front-end of PyTorch, and enables an online interaction between modern machine learning algorithms and all the existing simulation, modeling, and analysis processes available in MOOSE. New capabilities in MOOSE include the native generation and training of artificial neural networks together with options to load pretrained neural networks in TorchScript format. Furthermore, the MOOSE stochastic tools module (MOOSE-STM) has been enhanced with neural network-based surrogate and reduced-order model generation options for efficient stochastic analyses. Lastly, a reinforcement learning capability has been added to MOOSE-STM for the interactive control and optimization of complex multiphysics problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Micellar Mimicry of Intermetallic C14 and C15 Laves Phases by Aqueous Lyotropic Self-Assembly

Concentration-dependent supramolecular self-assembly of amphiphilic molecules in water furnishes a variety of nanostructured lyotropic liquid crystals (LLCs), which typically display high symmetry bicontinuous network and discontinuous micellar morphologies. Aqueous dispersions of soft spherical micelles derived from small molecule amphiphile hydration typically pack into exemplary body-centered cubic and closest-packed LLCs. However, investigations of hydrated mixtures of the ionic surfactant tetramethylammonium decanoate loaded with 40 wt % n-decane (TMADec-40) revealed the formation of a high symmetry bicontinuous double diamond LLC, as well as cubic C15 and hexagonal C14 Laves LLC phases that mirror the MgCu 2 and MgZn 2 intermetallic structure types, respectively. Detailed small-angle X-ray scattering analyses demonstrate that the complex C15 and C14 LLCs exhibit large unit cells, in which 12 or more ~3–4 nm diameter micelles of multiple discrete sizes arrange into tetrahedral close packing arrangements with exceptional long-range translational order. The symmetry breaking that drives self-assembly into these low-symmetry LLC phases is rationalized in terms of a frustrated balance between maximizing counterion-mediated micellar cohesion within the ensemble of oil-swollen particles, while simultaneously optimizing local spherical particle symmetry to minimize molecular-level variations in surfactant solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Multiphase Control for Robust and Complete Soft-Charging Operation of Dual Inductor Hybrid Converter

This paper presents a new Multiphase Dual Inductor Hybrid (MP-DIH) Converter for application in data center and telecommunication systems. The converter is based on addition of two output filter inductors to a Dickson switched-capacitor converter. The inductors are operated in multiple phases that are non-overlapped and evenly distributed over one switching cycle, completely soft-charging all flying capacitors even in the presence of practical capacitor mismatches and voltage ripples. In this converter operation, each branch of the switched-capacitor network is activated individually in one charging phase, and two interleaved inductors are employed to softly charge and discharge the capacitors to achieve high efficiency without any complex capacitor sizing or split phase operation. To verify the topology and its soft-charging advantages, a 48V-to-1.8V 20W experimental converter prototype is constructed. The converter achieves 92.4% peak efficiency for 40V-to-1.8V conversion and 92.1% peak efficiency for 48V-to-1.8V conversion at 4A load, and with 20% capacitance variations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A Review of the Research and Development of Brayton Cycle Technology in Nuclear Power Applications with a Focus on Compressor Technology

This study reviews the integration of Brayton Cycle (BC) systems in nuclear power generation, emphasizing their potential to enhance thermal efficiency and operational flexibility over traditional Rankine Cycle (RC) systems. Key working fluids, such as helium (He), supercritical carbon dioxide (sCO 2 ), nitrogen (N 2 ), and air, are evaluated for their performance, efficiency, and compatibility with nuclear systems. He is recognized for its high thermal conductivity and inertness at elevated temperatures, while sCO 2 demonstrates advantages in compactness and efficiency in midrange temperatures. This article also highlights the importance of compressor designs in optimizing BC performance and reviews, available compressor technologies. Axial and centrifugal compressor designs enable efficient gas compression while managing the thermal and mechanical stresses associated with high-pressure operations in nuclear systems. Combined with variable geometry components and advanced materials, these technologies address the challenges posed by varying load conditions. Despite the promising features of BC systems, several challenges persist, including high leakage rates and material degradation under extreme conditions, which necessitate robust sealing technologies and thorough testing. The insights gained from operational experiences at facilities, such as the Oberhausen II plant and the High-Temperature He Test Facility (HHV), underscore the complexities involved in designing high-temperature gas turbines for nuclear applications. This review concludes that as the nuclear industry evolves, BC systems hold significant promise for contributing to a sustainable energy future, particularly in the context of small modular reactors (SMRs) and microreactors. Further exploration of combined cycle configurations that combine BCs with RCs may enhance overall efficiency and flexibility in power generation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Rolling Element Bearing Dynamics in Wind Turbines

There are unique reliability challenges related to wind turbine drivetrains. Predominant failure modes are not accounted for in design standards, not attributable to material deficiencies or quality control, and are complex and independent of the component supplier. The team conducted testing and analysis to enable improvement of inherent reliability, an increase of availability with less effort and drama, and a reduction in wind plant operation and maintenance costs. The analytic model was validated through uptower experiments, and the bearing speed was directly affected by drivetrain load and speed. Bearing sliding is widely present during regular turbine operations and significant sliding occurs during transient events, which can lead to bearing failures and shortened life.

17 WIND ENERGY↗
DOE OSTI2020

Uncertainty Quantification for Capacity Expansion Planning

This report quantifies the uncertainty in output decisions from a Capacity Expansion Planning (CEP) model. The need to understand how uncertainties within CEP models and modeling assumptions affect Quantities of Interest (QoIs) such as expansion and operating costs, as well as expansion decisions remains an ongoing challenge in scientific research and industrial operations. This area of research is particularly important for models which seek to capture how large networks will evolve and operate under increased sources of variable generation, i.e., higher penetration of renewable technologies such as solar and wind generators. Uncertainty quantification (UQ) of CEP models which estimate expansion costs and decisions, and production cost models which estimate operating costs and dispatch decisions, is a key focus of research at NREL. The Regional Energy Deployment System (ReEDS) represents a state-of-the-art CEP model and considers a range of possible grid evolutions in an attempt to identify key drivers, ramifications, and decisions which contribute to better informed investment and policy decisions. However, research to quantify how uncertainties and model assumptions, such as unit commitment (UC), within ReEDS may be affecting its outputs remains challenging due to to size and complexity of the model

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often been perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.

25 ENERGY STORAGE↗
DOE OSTI2026

Lewis Acid‐Activated Charge Trapping in Dielectric Polymers for Superior High‐Temperature Electrostatic Energy Storage

Dielectric polymer capacitors are essential for electrostatic energy storage but suffer from charge transport-induced energy losses, particularly at elevated temperatures where thermally activated charge carriers exacerbate conduction. Conventional mitigation strategies rely on introducing heterogeneous interfaces to create charge traps, complicating scalable film fabrication. A homogeneous molecular trapping mechanism would circumvent these complexities, yet remains underexplored. Herein, a charge trapping strategy is devised by modifying the lowest occupied molecular orbitals of dielectric polymers through Lewis acid-base adduct formation. The use of tris(pentafluorophenyl)boron (BCF) as a Lewis acidic molecular additive introduces deeper charge traps in commercial polyetherimide (PEI) while retaining homogeneity. With only 0.5 wt.% loading, the PEI-BCF film exhibits greatly improved breakdown strength, achieving an ultrahigh discharged energy density of 7.3 J cm-3 with excellent cycle stability at 200 °C. This work establishes a facile molecular approach to decoupling charge trapping from heterogeneous interfaces, enabling high-energy-density polymer capacitors operable under extreme thermal conditions.

Fan, Lu↗
DOE OSTI2018

Biodegradability and Thermal Properties of Novel Natural Rubber/Linear Low Density Polyethylene/Thermoplastic Starch Ternary Blends

This work aimed to prepare biodegradable thermoplastic elastomers based on NR/LLDPE/TPS ternary simple blends to achieve some exclusive properties, i.e., good biodegradability in terms of water absorption and weight loss after burial, together with reasonable mechanical and thermal properties. A comparative study on biodegradability and other related properties of NR/LLDPE binary and NR/LLDPE/TPS ternary blends was performed. It was found that increasing the TPS proportion decreased storage modulus and complex viscosity. In addition, the size of dispersed TPS domains in the NR/LLDPE co-continuous matrix increased with TPS proportion, while the mechanical properties in terms of 100% moduli, tensile strength, elongation at break, and hardness decreased. This might be attributed to decreased interfacial adhesion with increasing size of TPS domains. Furthermore, increasing the TPS loading in the blend reduced the temperatures for 5 or 50% mass loss (T{sub 5} or T{sub 50}) and the degradation temperature (T{sub d}). However, the biodegradability improved, in terms of increased water absorption and weight loss after burial in soil, with the loading level of TPS.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unraveling kinking: A plasticity enhancing failure mode in high strength nano metallic laminates

Kinking is an important and plasticity-enhancing deformation/failure mode in numerous mechanically anisotropic materials including high-strength nano metallic laminates (NMLs). However, our current limited understanding of the mechanics of kinking and its dependence on microstructural attributes is insufficient for thoroughly comprehending and eventually being able to control failure behaviors of materials. In this study, we investigate kinking dependencies on microstructural attributes in NMLs via in situ micropillar compression, multiscale microstructure characterization, dislocation dynamic simulations, and crystal plasticity modeling. Additionally, by examining several NML systems (Cu/Fe, Ag/Fe, Al-4Mg/Fe), we demonstrate that the development of internal stresses during loading activates local layer-parallel glide triggering kinking in NMLs. Furthermore, this work reveals the effect of key microstructural features including layer thickness, layer waviness, interface barrier strength, and work hardening capacity on kink band formation in NMLs. More broadly, our efforts represent a generically applicable approach for probing large-strain deformation behavior of complex materials via synergetic modeling and experimental efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Demonstration of reduced-order urban scale building energy models

The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% with the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Understanding failure in austenitic steels: Key considerations for molten salt storage in CSP applications

Owing to their excellent properties, austenitic stainless steels are extensively used in boilers, furnaces, molten salt tanks, and other applications that are subjected to extreme mechanical loads and high-temperature conditions. Their high corrosion and creep resistance make them suitable for high-temperature operating environments. Additionally, good fatigue resistance and favorable mechanical and visual properties are essential. However, the premature failure of several components at elevated temperatures has been previously reported. Although the failure analysis of components in service is complex, processes such as cold work and welding have been identified as contributing factors to the performance degradation of these steels. This study aims to analyze the various documented failure modes and mechanisms in austenitic steels, including creep, cracking, stress relaxation cracking, and fatigue, to better understand the multi-objective design requirements for these alloys as structural materials for high-temperature molten salt tanks in Concentrating Solar Power (CSP) plants. Stabilized austenitic grades, such as AISI 347H, demonstrate superior resistance to creep and corrosion-related degradation when compared to non-stabilized grades like AISI 316L at temperatures relevant to concentrated solar power (CSP) applications. In contrast, nickel-based alloys offer enhanced corrosion resistance, albeit at a higher cost. This review underscores that creep, stress relaxation cracking, and thermo-mechanical fatigue are the predominant long-term failure risks in CSP hot tanks.

14 SOLAR ENERGY↗
DOE OSTI2015

Inertia driven radial breathing and nonlinear relaxation in cylindrically confined pure electron plasma

The dynamics of cylindrically trapped electron plasma has been investigated using a newly developed 2D Electrostatic PIC code that uses unapproximated, mass-included equations of motion for simulation. Exhaustive simulations, covering the entire range of Brillouin ratio, were performed for uniformly filled circular profiles in rigid rotor equilibrium. The same profiles were then loaded away from equilibrium with an initial value of rigid rotation frequency different from that required for radial force balance. Both these sets of simulations were performed for an initial zero-temperature or cold load of the plasma with no spread in either angular velocity or radial velocity. The evolution of the off-equilibrium initial conditions to a steady state involve radial breathing of the profile that scales in amplitude and algebraic growth with Brillouin fraction. For higher Brillouin fractions, the growth of the breathing mode is followed by complex dynamics of spontaneous hollow density structures, excitation of poloidal modes, leading to a monotonically falling density profile.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The influence of leaf size and shape on leaf thermal dynamics: does theory hold up under natural conditions?

Laboratory studies on artificial leaves suggest that leaf thermal dynamics are strongly influenced by the two-dimensional size and shape of leaves and associated boundary layer thickness. Hot environments are therefore said to favour selection for small, narrow or dissected leaves. Empirical evidence from real leaves under field conditions is scant and traditionally based on point measurements that do not capture spatial variation in heat load. Here in this study, we used thermal imagery under field conditions to measure the leaf thermal time constant (τ) in summer and the leaf-to-air temperature difference (ΔT) and temperature range across laminae (T range ) during winter, autumn and summer for 68 Proteaceae species. We investigated the influence of leaf area and margin complexity relative to effective leaf width (w e ), the latter being a more direct indicator of boundary layer thickness. Normalized difference of margin complexity had no or weak effects on thermal dynamics, but w e strongly predicted τ and ΔT, whereas leaf area influenced T range . Unlike artificial leaves, however, spatial temperature distribution in large leaves appeared to be governed largely by structural variation. Therefore, we agree that small size, specifically we, has adaptive value in hot environments but not with the idea that thermal regulation is the primary evolutionary driver of leaf dissection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Novel Hybrid Microbial Electrochemical System for Efficient Hydrogen Generation from Biomass (Final Technical Report)

The overall goal of this proposal was to develop a novel microbial electrochemical system for H 2 production from biomass at a cost less than $2/kg H 2 . The specific objectives of this project were: (1) design and fabricate a low-cost, robust, and highly efficient hybrid fermentation and microbial electrochemical cell (MEC) reactor, and (2) determine the techno-economic feasibility of the system for H 2 generation from lignocellulosic biomass hydrolysates and sugar-rich wastewater. We achieved the first objective by developing a system with the following characteristics: (a) a hybrid bioreactor that combines the strengths of dark fermentation and microbial electrolysis processes; (b) novel electrode assembly in the reactor that contains robust, low-cost, efficient catalyst, electrode and separator materials; (c) optimized operational conditions that lower the energy input and enhance H 2 yield and production rate. We achieved the second objective by developing a cost-performance model to identify key factors that affect performance and cost of H 2 production and guide/prioritize research. The research conducted in this project has advanced the knowledge in the fields of dark fermentation, microbial electrochemistry and technologies, and electrocatalysis. It has enhanced our understanding of how the H 2 production is affected by the bacterial culture, feedstock composition, and environmental conditions in both dark fermentation and MEC processes and what are the key microbial processes that hinder the H 2 production using single chamber MEC reactors and mixed bacterial cultures. The research has revealed the synthesis-structure-property relationship of a H 2 evolution reaction (HER) catalyst. This proposed technology represents a green and renewable approach for H 2 production from biomass. The biomass harvested in the country could provide enough H 2 to fuel light-duty vehicles in the US. When using wastewater as feedstock, the simultaneous wastewater treatment during H 2 production process can further increase the environmental sustainability. The research conducted in this project has brought the biological H 2 production technologies closer to practical applications by: 1) determining the suitable mixed bacterial cultures using complex feedstocks; 2) developing fermentative bacterial enrichment and immobilization methods for enhancing the H 2 production rate; 3) developing low-cost molybdenum phosphide (MoP) HER catalysts to lower the capital cost; 4) determining the suitable design (e.g. reactor configuration, electrode surface area to rector volume ratio, liquid/gas separator) and operational conditions (e.g. pH, temperature, feedstock loading, mixing conditions) to lower the capital and operational costs; 5) fabricating a 10-L hybrid reactor to demonstrate the potential of H 2 production. Our cost performance analysis suggests that further increasing the current density and reducing the electrode costs are critical to meet the $2/kg cost target using lignocellulosic biomass feedstock and the cost target is achievable using wastewater as feedstock if the wastewater treatment credit is considered.

08 HYDROGEN↗