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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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DOE OSTI2017

Web-Based Computational Model Builder For Nuclear Energy Advanced Modeling and Simulation (Final Report)

According to the World Nuclear Association, the U.S. is the largest producer of nuclear power worldwide. In fact, the U.S. provides over 30 percent of the world's nuclear generation of electricity. Although few new reactors have been built in the past 30 years, the association anticipates that four to six reactors may be built by 2020. The first of the reactors will be built in response to 16 license applications, which have been completed since 2007, to build 24 additional nuclear reactors. Currently, both government and industry are working to accelerate approval for the construction and design of new nuclear energy plants. The U.S. nuclear industry has already achieved significant developments in the implementation of nuclear power plants due to advancements in refueling, maintenance, and safety systems at current power plants. Meanwhile, changes in government policy, which have occurred since the late 1990s, have provided for noteworthy expansion in nuclear capacity. For example, the Energy Policy Act of 2005 evoked investment in electricity infrastructure such as nuclear power. To design future systems and continue operational improvements at existing U.S. plants, advanced modeling and simulation of nuclear reactors are crucial. We developed a Cloud/Web-based tool, HPCCloud, that enables nuclear energy firms, or other manufacturing and engineering companies, to innovate using advanced modeling and simulation. Through the Web-Based Computational Model Builder for Nuclear Energy Advanced Modeling and Simulation grant, we develop HPCCloud to simplify and democratize advanced modeling and simulation in the nuclear energy industry on a range of nuclear engineering applications. It leverages millions of investment dollars from the Department of Energy's Consortium for Advanced Simulation of Light Water Reactors (CASL) and the Office of Nuclear Energy's research and development in Nuclear Energy Advanced Modeling and Simulation (NEAMS). Our approach simplifies the workflow, alleviates the need for in-house computational science and engineering experts, and lowers the capital investments required for advanced modeling and simulation. The Cloud/Web-based simulation environment guides end-users and developers through the advanced modeling and simulation lifecycle. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where one can save, share, and even publish the full path of data from input to final analyzed results. HPCCloud addresses identified challenges to the nuclear energy industry's use of advanced modeling and simulation. With this unique Cloud/Web-based environment, we enable an ecosystem of synergistic activities, fueling new research and development for nuclear energy. HPCCloud lays the groundwork for commercialization, through customization, technology integration, and advanced research and development services.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Periodic Material-Based Seismic Base Isolators for Small Modular Reactors

Important structures such as nuclear power plants should experience very little vibrations in order to maintain the safety of the nuclear facilities during seismic events. Protection of these structures by seismic isolators requires the isolators to provide seismic isolation irrespective of the direction of excitations and to develop a stable response without rocking. Conventional seismic isolation systems, however, can only fulfill partial requirements for the seismic protection. This study adopts the principle of periodic materials for seismic isolation. These materials exhibit unique properties of frequency band gaps, where incoming waves with frequencies falling inside the frequency band gaps are forbidden. The new isolation systems, known as periodic foundations, function both as a structural foundation to support the gravitational weight of the superstructure and also as a seismic isolator. The isolation mechanism, hypothetically, can easily fulfill all the requirements for seismic protection of the critical facilities. This study focuses on the design of one-dimensional (1D) and three-dimensional (3D) periodic foundations for seismic isolation of small modular reactor (SMR) buildings. The theoretical study was first conducted to reveal the fundamental behavior of periodic foundations. Then global sensitivity analysis was utilized to study the effect of design parameters on the frequency band gaps. In addition, simple straight-forward design equations based on the sensitivity analysis are proposed for the design of periodic foundations. Utilizing the proposed equations, prototypes of 1D and 3D periodic foundations were designed to isolate an SMR building. Scaled models were fabricated and experimentally tested to validate the hypothesis and design. The periodic foundation structural systems were tested under various input waves, including seismic waves, in the horizontal and vertical directions and the torsional mode. The shake table test results show that the periodic foundations can reduce the acceleration response of the SMR building up to 90% in the horizontal direction and the torsional mode. As much as a 40% response reduction in the vertical direction is also observed. Moreover, the periodic foundation-isolated structure exhibited stable response with negligible rocking on the structure. This study proved the capability of periodic foundations to enhance the seismic safety of critical structures.

42 ENGINEERING↗
DOE OSTI2017

A Comparison of the FW-CADIS and MR-CADIS Variance Reduction Methods

The Consistent Adjoint Driven Importance Sampling (CADIS) method, which uses an adjoint deterministic estimate for making variance reduction parameters that optimize Monte Carlo (MC) shielding calculations, was introduced in 1998. This method was designed to optimize a single tally, typically an integrated response such as a detector count rate or a dose rate. Because both deterministic and stochastic methods are employed, CADIS is referred to as a hybrid method. In 2007, the forward-weighted CADIS (FW-CADIS) method was introduced to optimize several tallies at once, giving more uniform relative uncertainties among the tallies for both high-flux and low-flux areas of the problem. This method can be used for several small detectors, for semi-global problems (mesh tally over a large fraction of the problem), or for global problems (mesh tally over the entire problem). Optimization can be done for an integrated response such as a dose rate D(r) as a function of position, the total flux {phi}(r) as a function of position, or the space/energy flux {phi}(r,E). Both the CADIS and FW-CADIS methods have been in the MAVRIC sequence of SCALE for three versions (6.0 in 2009, 6.1 in 2011, and 6.2 in 2016). The ADVANTG package released in 2015 uses the CADIS and FW-CADIS methods to accelerate MCNP neutron/photon shielding calculations. In 2014, the multi-response CADIS (MR-CADIS) method was presented as a way to obtain even more uniform relative uncertainties for problems with multiple tallies than those obtained with FW-CADIS. The method does not use a forward deterministic calculation but instead uses one adjoint calculation for every tally to be optimized in the Monte Carlo calculation. This work compares the above methods.

42 ENGINEERING↗
DOE OSTI2025

Electric Drive Technologies Consortium (EDTC)/ Cost competitive, high-Performance, highly Reliable (CPR) Power Devices on 4H-SiC (Final Report)

4H-Silicon carbide (4H-SiC) is a wide bandgap semiconductor that offers superior material properties over silicon, including higher critical electric field, thermal conductivity, and electron saturation velocity. These advantages make 4H-SiC highly attractive for high-voltage, high-efficiency power electronics. However, realizing the full potential of SiC requires device technologies that are not only high-performing but also manufacturable and reliable under real-world operating conditions. This report summarizes the outcomes of a five-year R&D effort funded by the U.S. Department of Energy (DOE) under the Electric Drive Technologies Consortium (EDTC), focused on developing cost-competitive, high-performance, and highly reliable (CPR) power devices on 4H-SiC substrates. The program targeted scalable and manufacturable 1.2 kV-class SiC MOSFETs optimized for next-generation electric vehicles, renewable energy systems, and industrial power conversion. The project delivered transformative advancements in SiC power device performance and ruggedness. Particularly, Specific on-resistance (R on,sp ) was reduced by up to 37%, from ~4.0 m$\Omega \cdot$cm 2 in earlier designs to an industry-leading 2.40 m$\Omega \cdot$cm 2 , driven by optimized doping, refined JFET widths, and layout engineering. Breakdown voltages (BV) exceeded 1600 V, marking improvement over legacy baselines, and demonstrating the robustness of newly implemented junction profiles and edge terminations. Short-circuit withstand time (SCWT) saw a remarkable 4$\times$ increase, from ~2 $\mu$s to over 8 $\mu$s, achieved through the successful deployment of deep P-well structures (~1.8–2.0 $\mu$m) via channeling implantation. This innovative process breakthrough enabled precise junction formation without MeV-class implantation tools, reduced leakage under high field stress, and allowed even the shortest-channel devices (down to 0.3 $\mu$m) to achieve both high BV and excellent ruggedness—breaking the traditional trade-off between conduction efficiency and blocking capability. Several novel architectures pushed the performance envelope further. JBSFETs—featuring embedded Schottky portions—eliminated bipolar degradation and drastically reduced third-quadrant leakage, while Ladder MOSFETs introduced a clever orthogonal conduction path that achieved a 15.4% reduction in R on,sp over standard linear designs. Switching performance reached new benchmarks: short-channel devices showed a 31% reduction in total switching energy compared to 0.5 $\mu$m counterparts, while maintaining manageable gate drive requirements. Layout-optimized structures not only improved transconductance but also accelerated switching transitions, pointing to real-world benefits in converter-level efficiency. The devices also passed rigorous reliability validation. Stress-tested across TDDB, HTGB, HTRB, HVP, and burn-in, the devices screened under 30 V/10 hr and 43 V/1 s protocols consistently exhibited tighter lifetime distributions and long-term oxide robustness. These screening techniques proved effective in identifying latent defects and ensuring deployment-grade reliability. Meanwhile, advanced 3D TCAD simulations revealed and resolved electric field hotspots—particularly in HEXFET corners—where fields exceeding 4.8 MV/cm were mitigated through geometry-aware layout corrections. Overall, the results of this project demonstrate a manufacturable and scalable SiC power device platform that addresses key DOE performance targets for efficient, robust, and reliable 1.2kV 4H-SiC Power Devices. The developed technologies represent a meaningful step forward in the commercial readiness of high-voltage SiC solutions and provide a strong foundation for continued advancement in wide bandgap power electronics.

42 ENGINEERING↗
DOE OSTI2017

Quaternary FeCoNiMn-Based Nanocarbon Electrocatalysts for Bifunctional Oxygen Reduction and Evolution: Promotional Role of Mn Doping in Stabilizing Carbon

The intrinsic instability of carbon largely limits its use for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) as a bifunctional catalyst in reversible fuel cells or water electrolyzers. In this paper, we discovered that Mn doping has a promotional role in stabilizing nanocarbon catalysts for the ORR/OER in alkaline media. Stable nanocarbon composites are derived from an inexpensive carbon/nitrogen precursor (i.e., dicyandiamide) and quaternary FeCoNiMn alloy via a template-free carbonization process. In addition to FeCoNiMn metal alloys/oxides, the carbon composites comprise substantial carbon tube forests growing on a thick and dense graphitic substrate. The dense carbon substrate with high degree of graphitization results from Mn doping, while active nitrogen-doped carbon tubes stem from FeCoNi. Catalyst structures and performance are greatly dependent on the doping content of Mn. Various accelerated stress tests (AST) and life tests verify the encouraging ORR/OER stability of the nanocarbon composite catalyst with optimal Mn doping. Extensive characterization before and after ASTs elucidates the mechanism of stability enhancement resulting from Mn doping, which is attributed to (i) hybrid carbon nanostructures with enhanced resistance to oxidation and (ii) the in situ formation of the β-MnO 2 and FeCoNi-based oxides capable of preventing carbon corrosion and promoting activity. Note that the improvement in stability due to Mn doping is accompanied by a slight activity loss due to a decrease in surface area. Finally, this work provides a strategy to stabilize carbon catalysts by appropriately integrating transition metals and engineering carbon structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Nanocellulose Dewatering and Drying: Current State and Future Perspectives

The knowledge base for nanocellulose (NC) has grown exponentially over the past two decades and continues to expand with the increasing number of potential applications demonstrated in the literature and the patent space. NC has multiple forms depending on the starting cellulose source and the specific process used to produce it. Its high degree of surface reactivity makes it an ideal support structure for a wide variety of functional groups, leading to the ability to engineer materials for very specific applications. However, removing water from an NC suspension, e.g., dewatering and drying, while retaining the nanoscale properties of the NC remains a significant challenge to successful commercialization of NC materials. Processes for dewatering and drying of NC are desirable because of the high transport costs of shipping dilute aqueous suspensions, as well as end-use application requirements. Therefore, the development of nondestructive, cost-effective, scalable, and environmentally friendly dewatering and drying processes is important for commercial deployment of NC applications. This review addresses the current state of published knowledge on NC dewatering and drying and identifies research gaps that could be further explored in a precompetitive context to accelerate commercialization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

A review of micromirror arrays

The aim of this article is to provide a review of micromirror array (MMA) technologies (2631 MMA research papers and patents were reviewed for this effort). The performance capabilities of 277 MMA designs from 49 companies and 23 academic research groups are categorized and compared. The designs are categorized according to (i) their array’s dimension (e.g., 2D arrays consisting of mirrors that cover a surface, 1D arrays consisting of mirrors in a row, and 0D arrays consisting of only a single mirror), (ii) the nature of the surface of their mirrors (e.g., continuous or discrete), (iii) what combination of tip, tilt, and/or piston degrees of freedom (DOFs) they achieve, and (iv) how they are actuated. Standardized performance metrics that can be systematically applied to every MMA design (e.g., mirror area, fill factor, pitch, range of motion, maximum acceleration, actuator energy density, and number of uncontrolled DOFs) are defined and plotted for existing designs to enable their fair comparison. Theoretical bounds on what is physically possible for MMAs to achieve are also derived and depicted in these plots to highlight the amount of performance improvement that remains to be achieved by future designs and guidelines are provided to aid in the development of these future designs.

42 ENGINEERING↗
DOE OSTI2022

PACT Perovskite PV Module Stress Testing Protocol (Version 0.0)

The purpose of this protocol is to use accelerated stress testing to assess the durability of metal halide perovskite (MHP) photovoltaic (PV) modules. The protocol aims to apply field relevant stressors to packaged MHP modules to screen for early failures that may be observed in the field. The current protocol has been designed with a glass/glass-PIB edge seal, no encapsulant package in mind. PACT anticipates adding additional testing sequences to evaluate additional stressors (e.g., PID, reverse bias) in the future.

42 ENGINEERING↗
DOE OSTI2023

Stakeholder Training for IEEE 1547-2018 (Abbreviated Final Technical Report)

This project identifies and makes publicly available educational materials to assist stakeholders in adopting the revised IEEE Std 1547-2018, Standard for Interconnection and Interoperability of Distributed Energy Resources with Associated Electric Power Systems Interfaces. The new standard is significantly different than the previous 2003 version, contains new concepts and new technical requirements, and requires educational material on the application of these changes. NREL had a principal role in accelerating the revision process though its chairmanship of the IEEE Std 1547 working group to revise the standard and through technical support provided to the working group. Under this project, NREL and partners compiled and developed publicly available educational materials for IEEE Std 1547-2018, including webinars, white papers, and other resources on related topics.

14 SOLAR ENERGY↗
DOE OSTI2025

Temporally-consistent koopman autoencoders for forecasting dynamical systems

Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) harness the expressivity of deep neural networks (DNNs), the dimension reduction capabilities of autoencoders, and the spectral properties of the Koopman operator to learn a reduced-order feature space with simpler, linear dynamics. However, the effectiveness of KAEs is hindered by limited and noisy training datasets, leading to poor generalizability. To address this, we introduce the Temporally-Consistent Koopman Autoencoder (tcKAE), designed to generate accurate long-term predictions even with limited and noisy training data. This is achieved through a consistency regularization term that enforces prediction coherence across different time steps, thus enhancing the robustness and generalizability of tcKAE over existing models. We provide analytical justification for this approach based on Koopman spectral theory and empirically demonstrate tcKAE’s superior performance over state-of-the-art KAE models across a variety of test cases, including simple pendulum oscillations, kinetic plasma, and fluid flow data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Expeditious modeling of vapor transport and reactions in polymeric materials

We present a methodology for approximating dynamic adsorption of vapor coupled with diffusion in polymeric materials. In previous publications, the dynamic adsorption was represented by ordinary differential equations (ODEs) and solved in concentration and parameter space. To accelerate the calculation, we have developed a statistical approximation method using computationally cheap surrogate models (e.g., algebraic polynomials) that replace the ODE solutions of adsorption and are coupled with the diffusion equations. Since the polynomial presentation of the adsorption term is obtained in a standard format prior to modeling coupled sorption‐diffusion, the adsorption operator can be expressed as input data in the transport code. Compared to conventional operator‐splitting methods, the polynomial approximation of adsorption offers better computational efficiency. The methodology is demonstrated and validated using a dynamic Langmuir adsorption model that is coupled to diffusion and absorption models and applied to a water vapor sorption‐diffusion process in polydimethylsiloxane polymers. © 2017 American Institute of Chemical Engineers AIChE J , 63: 4079–4089, 2017

Sun, Yunwei↗
DOE OSTI2016

Investigation of the dynamic stress–strain response of compressible polymeric foam using a non-parametric analysis

Dynamic stress–strain response of rigid closed-cell polymeric foams is investigated in this work by subjecting high toughness polyurethane foam specimens to direct impact with different projectile velocities and quantifying their deformation response with high speed stereo-photography together with 3D digital image correlation. The measured transient displacement field developed in the specimens during high stain rate loading is used to calculate the transient axial acceleration field throughout the specimen. A simple mathematical formulation based on conservation of mass is also proposed to determine the local change of density in the specimen during deformation. By obtaining the full-field acceleration and density distributions, the inertia stresses at each point in the specimen are determined through a non-parametric analysis and superimposed on the stress magnitudes measured at specimen ends to obtain the full-field stress distribution. Furthermore, the process outlined above overcomes a major challenge in high strain rate experiments with low impedance polymeric foam specimens, i.e. the delayed equilibrium conditions can be quantified.

42 ENGINEERING↗
DOE OSTI2022

Fabrication and accelerated long-term stability test of asymmetrical hollow fiber-supported thin film oxygen separation membrane

Asymmetrical hollow fiber-supported thin film membrane may provide microstructural advantages for air separation and oxygen production. The fabrication of such a membrane is usually very difficult, particularly the sintering behaviors and thermal expansion coefficient (TEC) mismatch among multiple layers. This directly affects the reliability and long-term stability of the membrane. Here, in this research, the sintering behaviors of a set of simple oxides are systematically studied and ZnO is identified as a material component for composite substrate La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ (LSCF)-ZnO. The LSCF-ZnO ratios are further optimized by trading off several factors, e.g., matching the sintering behaviors and TECs of the LSCF-ZnO composite with those of LSCF thin film separation layer while enhancing the substrate strength. With the identified LSCF-ZnO ratio, the LSCF-ZnO composite hollow fiber substrate precursor is formed through slurry spinning process with porous microstructure being formed via phase inversion process. The thin film LSCF dense separation layer is then dip-coated on the substrate followed by co-sintering process. A thin, porous PrBaCo(Fe 0.6 Zr 0.2 Y 0.2 )O 5+δ (PBCFZY) catalyst layer is fabricated on the dense LSCF separation layer with dip-coating and sintering process, forming an asymmetrical membrane device LSCF-ZnO/LSCF/PBCFZY. Oxygen permeation test of the device is systematically conducted, and the fundamental mechanisms are analyzed. An accelerated long-term stability test of the membrane is also conducted (~550h, 46 thermal cycling loads), demonstrating excellent robustness and durability. The device is characterized and analyzed before and after the test. By replacing a considerable amount of high cost LSCF with low cost ZnO in the substrate, it not only enhances the stability but also reduces the capital cost of the membrane for practical applications.

42 ENGINEERING↗
DOE OSTI2021

Multilevel-in-Space-and-Energy CMFD in VERA

For full-core modeling in the Virtual Environment for Reactor Analysis (VERA), the three-dimensional multigroup eigenvalue neutron transport problem is solved by MPACT. To improve the efficiency of MPACT, advancements have been made in the transport accelerator. Multilevel-in-energy and multilevel-in-space coarse mesh finite difference (CMFD) solvers were developed to improve the efficiency of the CMFD accelerator. In this paper a new multilevel-in-space-and-energy CMFD solver is developed with coarsening in both space and energy on every level. Several different strategies are investigated for coarsening groups in energy. Modified V-cycle and multiple-cycle algorithms are evaluated for solving the multilevel equations. The performance of these solvers is compared for typical full-core reactor physics problems.

42 ENGINEERING↗
DOE OSTI2026

SEED: Semantic Energy Exploration and Discovery

The Bioenergy Knowledge Discovery Framework (KDF) hosts a vast repository of specialized data, yet traditional keyword-based search methods often struggle to provide direct answers, requiring significant domain expertise and manual effort to filter through raw documents. To overcome these barriers, this software introduces a semantic search engine that enables both specialists and non-specialists to query the KDF using natural language. By shifting from rigid keyword matching to intent-based retrieval, the tool automatically identifies and ranks the most relevant sources within the database. The system functions by processing natural language queries to extract the most pertinent information, delivering an AI-generated plain-language summary alongside exact supporting quotes from retrieved documents. This integrated approach provides users with immediate, evidence-based answers while eliminating the need for exhaustive manual review. By surfacing direct insights and contextual evidence, the software enhances the usability of existing KDF resources and democratizes access to complex bioenergy data. Ultimately, this semantic search solution accelerates the discovery process and supports faster, more informed decision-making across the bioenergy sector.

Pan, Meiyu (Melrose) [Oak Ridge National Laborator↗
DOE OSTI2014

Next Generation Environmentally-Friendly Driving Feedback Systems Research and Development

The objective of this project is to design, develop, and demonstrate a next-generation, federal safety- and emission-complaint driving feedback system that can be deployed across the existing vehicle fleet and improve fleet average fuel efficiency by at least 2%. The project objective was achieved with the driving feedback system that encourages fuel-efficient vehicle travel and operation through: 1) Eco-Routing Navigation module that suggests the most fuel-efficient route from one stop to the next, 2) Eco-Driving Feedback module that provides sensible information, recommendation, and warning regarding fuel-efficient vehicle operation, and 3) Eco-Score and Eco-Rank module that provides a means for driving performance tracking, self-evaluation, and peer comparison. The system also collects and stores vehicle travel and operation data, which are used by Algorithm Updating module to customize the other modules for specific vehicles and adapts them to specific drivers over time. The driving feedback system was designed and developed as an aftermarket technology that can be retrofitted to vehicles in the existing fleet. It consists of a mobile application for smart devices running Android operating system, a vehicle on-board diagnostics connector, and a data server. While the system receives and utilizes real-time vehicle and engine data from the vehicle’s controller area network bus through the vehicle’s on-board diagnostic connector, it does not modify or interfere with the vehicle’s controller area network bus, and thus, is in compliance with federal safety and emission regulations. The driving feedback system was demonstrated and then installed on 45 vehicles from three different fleets for field operational test. These include 15 private vehicles of the general public, 15 pickup trucks of the California Department of Transportation that are assigned to individual employees for business use, and 15 shuttle buses of the Riverside Transit Agency that are used for paratransit service. Detailed vehicle travel and operation data including route taken, driving speed, acceleration, braking, and the corresponding fuel consumption, were collected both before and during the test period. The data analysis results show that the fleet average fuel efficiency improvements for the three fleets with the use of the driving feedback system are in the range of 2% to 9%. The economic viability of the driving feedback system is high. A fully deployed system would require capital investment in smart device ($150-$350) and on-board diagnostics connector ($50-$100) as well as paying operating costs for wireless data plan and subscription fees ($20-$30 per month) for connecting to the data server and receiving various system services. For individual consumers who already own a smart device (such as smartphone) and commercial fleets that already use some kind of telematics services, the costs for deploying this driving feedback system would be much lower.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Photon Irradiation Effects on the Enduray Vision System for Nuclear Inspections

Video cameras with greater radiation hardening are needed for the operation and remote handling of equipment in nuclear reactor inspection and refueling applications. Vega Wave Systems has developed a radiation-hardened vision system for nuclear energy applications. The program described in this report provided radiation-hardness testing of this vision system using the Argonne Low-Energy Accelerator Facility (LEAF). This report presents the results of irradiation tests performed on several of Vega Wave System’s cameras at dose rates ranging from 1 kGy/hr up to 10 kGy/hr and up to total doses of >500 kGy. The results were excellent, providing proof of the camera system’s immunity to radiation effects at all levels tested.

36 MATERIALS SCIENCE↗