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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Virtual prototyping of liquid metal blanket performance in fusion pilot plant

Liquid metal blanket is a dominant design option for the next step fusion devices responsible for harvesting energy from fusion reaction, and simultaneously producing fuel for the same reaction through tritium breeding. Liquid metal blankets introduce additional complexity to the design due to fluid motion, fluid structure interaction, and magnetohydrodynamic (MHD) effects arising from the motion of the conducting fluid through the magnetic field. They are also directly affected by the plasma heat flux and neutronic fluence. PPPL is currently developing a virtual prototyping system for numerical analysis of the liquid metal blankets for future fusion devices. The system has a customized 3D computational fluid dynamics (CFD) code in its core, allowing MHD flow and conjugate heat transfer analysis in blankets fluids and solids. The code was successfully used before for dual coolant blanket analysis [A. Khodak et al., Fusion Eng. and Des. 137 (2018)]. Recently the same code was modified to allow verified simulation of MHD flows at high Hartmann numbers of several thousand typical for blanket applications. CFD code receives volumetric heat source distribution from the neutronic analysis based on MCNP code. In addition, direct tritium breeding simulation will be performed allowing optimization of the blanket performance. 2D axisymmetric version of neutronics code will be used for rapid optimization, with 3D version employed for detailed analysis. The surface heat distribution on the plasma facing wall will be defined by the software HEAT allowing 3D modeling of the heat flux based on the magnetic field distribution including gyro-orbit effects. Results of thermal analysis are imported into structural analysis code also included in the system. Finally, direct import of CAD geometry will be used for analyzing all components and as a result design option can be efficiently optimized.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Solving the Big Data (BD) Problem in Advanced Manufacturing (Subcategory for work done at Georgia Tech. Study Process and Design Factors for Additive Manufacturing Improvement)

3D printing originally known as additive manufacturing is a process of making 3 dimensional solid objects from a CAD file. This ground breaking technology is widely used for industrial and biomedical purposes such as building objects, tools, body parts and cosmetics. An important benefit of 3D printing is the cost reduction and manufacturing flexibility; complex parts are built at the fraction of the price. However, layer by layer printing of complex shapes adds error due to the surface roughness. Any such error results in poor quality products with inaccurate dimensions. The main purpose of this research is to measure the amount of printing errors for parts with different geometric shapes and to analyze them for finding optimal printing settings to minimize the error. We use a Design of Experiments framework, and focus on studying parts with cone and ellipsoid shapes. We found that the orientation and the shape of geometric shapes have significant effect on the printing error. From our analysis, we also determined the optimal orientation that gives the least printing error.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimization Methodology of Pebble Bed HTGR Start-Up and Running-in Strategy

In recent years interest in advanced reactor technologies has increased significantly. However, the methods used for analysis of traditional nuclear reactors are insufficient to consider all the different and varied advanced reactor designs without further development. One promising advanced reactor design is the pebble bed reactor (PBR). PBRs possess unique operational and fuel cycle features that require the development of specific analysis methodologies to adequately design and analyze the systems. There is a need in PBR research for a capability to analyze and optimize the process of transitioning from the start-up reactor core to the equilibrium core (known as the “running-in” of the reactor). The start-up of a PBR and the transition to the equilibrium core is a complex, multi-physics challenge that has not yet been well researched and has many opportunities for design, analysis, and optimization of the process. In this research, a methodology is defined to consider the potential strategies in PBR start-up and run-in to the equilibrium core. Multiple candidate software are considered, and their pros and cons are discussed for the PBR-specific application in the methodology. A preliminary software selection for the physics engine is made, and initial verification of key modules is performed. Software to support optimization of the reactor run-in strategies through reduced order modeling (ROM) and machine learning are considered. Challenges for a full implementation of the methodology are discussed. Additional code selections and verification of models relevant to the application are needed before full demonstration of the methodology can be achieved and an optimal strategy determined.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Ultra-high Bandwidth, Ultra-high Dynamic Range X-Ray Shock Characterization via Photonic Integrated Circuit

Nuclear weapon component assessment tests at the Z Machine rely on accurate X-ray yield measurements for model validation, design and analysis of component survivability, and source optimization. Yield measurement devices currently used do not provide the requisite certainty to enable accurate and efficient data analysis of test results, which leads to an increase in Z-shots required for evaluation, longer device development times, and higher operation costs. Additionally, current X-ray flux detectors lack high temporal resolution at the tails. Similarly, shock measurement techniques used for component assessment often lack the ability to spatially resolve wave behavior thereby limiting the ability to measure shock propagation dynamics needed to design the next generation of ND components. Here we present the development of a photonic micro-calorimeter and shock sensor consisting of meter-long waveguide spirals that are optomechanically coupled to X-ray absorbing layers to characterize yield and shock propagation at nanosecond timescales.

42 ENGINEERING↗
DOE OSTI2021

Skeletal model reduction with forced optimally time dependent modes

Skeletal model reduction based on local sensitivity analysis of time dependent systems is presented in which sensitivities are modeled by forced optimally time dependent (f-OTD) modes. The f-OTD factorizes the sensitivity coefficient matrix into a compressed format as the product of two skinny matrices, i.e. f-OTD modes and f-OTD coefficients. The modes create a low-dimensional, time dependent, orthonormal basis which capture the directions of the phase space associated with most dominant sensitivities. These directions highlight the instantaneous active species, and reaction paths. Evolution equations for the f-OTD modes and coefficients are derived, and the implementation of f-OTD for skeletal reduction is described. For demonstration, skeletal reduction is conducted of the constant pressure ethylene-air burning in a zero-dimensional reactor, and new reduced models are generated. The laminar flame speed, the ignition delay, and the extinction curve as predicted by the models are compared against some existing skeletal models in literature for the same detailed model. Finally, the results demonstrate the capability of f-OTD to eliminate unimportant reactions and species in a systematic, efficient and accurate manner.

42 ENGINEERING↗
DOE OSTI2017

Optimization of greenhouse gas emissions in second-hand consumer product recovery through reuse platforms

Highlights: • Effects of waste diversion on flow of products to reuse processes. • Framework for solid waste management that focuses on reuse processes for waste diversion. • Application of framework on the material flow and GHG emissions from clothing reuse. - Abstract: Product reuse in the solid waste management sector is promoted as one of the key strategies for waste prevention. This practice is considered to have favorable impact on the environment, but its benefits have yet to be established. Existing research describes the perspective of “avoided production” only, but has failed to examine the interdependent nature of reuse practices within an entire solid waste management system. This study proposes a new framework that uses optimization to minimize the greenhouse gas emissions of an integrated solid waste management system that includes reuse strategies and practices such as reuse enterprises, online platforms, and materials exchanges along with traditional solid waste management practices such as recycling, landfilling, and incineration. The proposed framework uses material flow analysis in combination with an optimization model to provide the best outcome in terms of GHG emissions by redistributing product flows in the integrated solid waste management system to the least impacting routes and processes. The optimization results provide a basis for understanding the contributions of reuse to the environmental benefits of the integrated solid waste management system and the exploration of the effects of reuse activities on waste prevention. A case study involving second-hand clothing is presented to illustrate the implementation of the proposed framework as applied to the material flow. Results of the case study showed the considerable impact of reuse on GHG emissions even for small replacement rates, and helped illustrate the interdependency of the reuse sector with other waste management practices. One major contribution of this study is the development of a framework centered on product reuse that can be applied to identify the best management strategies to reduce the environmental impact of product disposal and to increase recovery of reusable products.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

BATMODS-lite [SWR-25-108]

Battery Analysis and Training Models for Optimization and Design Studies (BATMODS) is a Python package with an API for pre-built battery models. The original purpose of the package was to quickly generate synthetic data for machine learning models to train with. However, the models are generally useful for any battery simulations or analysis. BATMODS-lite includes the following: 1) A library and API for pre-built battery models 2) Kinetic/transport properties for common battery materials

Randall, Corey [National Laboratory of the Rockies↗
DOE OSTI2014

Tools for Accurate and Efficient Analysis of Complex Evolutionary Mechanisms in Microbial Genomes (Final Report)

I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbial genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of efficient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the final outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Reductive Analysis with Compiler-Guided Large Language Models for Input-Centric Code Optimizations

Input-centric program optimization aims to optimize code by considering the relations between program inputs and program behaviors. Despite its promise, a long-standing barrier for its adoption is the difficulty of automatically identifying critical features of complex inputs. This paper introduces a novel technique, reductive analysis through compiler-guided Large Language Models (LLMs), to solve the problem through a synergy between compilers and LLMs. It uses a reductive approach to overcome the scalability and other limitations of LLMs in program code analysis. The solution, for the first time, automates the identification of critical input features without heavy instrumentation or profiling, cutting the time needed for input identification by 44× (or 450× for local LLMs), reduced from 9.6 hours to 13 minutes (with remote LLMs) or 77 seconds (with local LLMs) on average, making input characterization possible to be integrated into the workflow of program compilations. Optimizations on those identified input features show similar or even better results than those identified by previous profiling-based methods, leading to optimizations that yield 92.6% accuracy in selecting the appropriate adaptive OpenMP parallelization decisions, and 20-30% performance improvement of serverless computing while reducing resource usage by 50-60%.

Input-Centric Optimization↗
DOE OSTI2025

Scalable Data Center Capacity for DOE's AI Prototype: A Rapidly Available Gigawatt Data Center for DOE

The multilaboratory Gigawatt Data Center working group was commissioned to identify approaches to rapidly establish federal data centers with scalable capacities up to 1,000 MW. These state-of-the-art facilities will serve as hubs for interdisciplinary collaboration, industry partnerships, and transformative applications of artificial intelligence. The proposed strategic shift includes facilitating multilaboratory collaboration, prioritizing operational efficiency, expanding public–private partnerships, optimizing investments, ensuring long-term contractual flexibility, supporting open science and secure data enclaves, and exploiting high-speed national networks. Owing to their extensive experience and best practices, the US Department of Energy national laboratories are uniquely positioned to lead this initiative. We recommend conducting a feasibility analysis to rapidly identify the optimal sites for this initiative, and the effort will likely involve private industry for design, construction, financing, and operational integration. We also propose establishing multiple geographically diverse sites to ensure energy resilience, high operational reliability, and a diverse user base, thereby effectively addressing the nation’s critical needs.

42 ENGINEERING↗
DOE OSTI2023

Emulating the Deutsch-Josza algorithm with an inverse-designed terahertz gradient-index lens

An all-dielectric photonic metastructure is investigated for application as a quantum algorithm emulator (QAE) in the terahertz frequency regime; specifically, we show implementation of the Deustsh-Josza algorithm. The design for the QAE consists of a gradient-index (GRIN) lens as the Fourier transform subblock and patterned silicon as the oracle subblock. First, we detail optimization of the GRIN lens through numerical analysis. Then, we employed inverse design through a machine learning approach to further optimize the structural geometry. Through this optimization, we enhance the interaction of the incident light with the metamaterial via spectral improvements of the outgoing wave.

Blackwell, Ashley N.↗
DOE OSTI2019

Sensitivity Analysis of an LCC-LCC Compensated 20-kW Bidirectional Wireless Charging System for Medium-Duty Vehicles

In this paper, sensitivity analysis of an LCC-LCC compensated bidirectional wireless charging system is presented. In a wireless charging system for electric vehicle applications, the effective load impedance varies significantly with the state-of-charge (SOC)of the battery. Due to the change in system parameters, resonant frequency, and transferred power, the efficiency of the system varies significantly. Sensitivity analysis of the system characteristics reveals the optimal operating region and required control strategy to operate within that region. Sensitivity analysis is even more important for a bidirectional system with mismatched input and output voltage levels. In this paper, the sensitivity of a bidirectional 20 kW wireless charging system is investigated analytically and the results are validated experimentally. The experimental results for a geometrically matched Double-D (DD) coil-based LCC-LCC tuned bidirectional WCS with asymmetric voltage levels show that the voltage gains and input impedance of the system are highly sensitive near the resonant frequency.

Mostak, Mostak Mohammad↗
DOE OSTI2025

High-Temperature Aquifer Thermal Energy Storage (HT-ATES) Projects in Germany and the Netherlands—Review and Lessons Learned

Aquifer thermal energy storage (ATES) is a concept that can help to address heating and cooling needs through the use of the subsurface as a seasonal thermal energy storage (STES) system. Over 2800 ATES systems have been deployed with storage temperatures typically below 25 °C and only a few with higher temperatures (>40 °C), which would increase the energy density and utility of the stored thermal fluids. Until now, only a few high-temperature aquifer thermal energy storage (HT-ATES) projects have been initiated and are still in operation. These HT-ATES projects have encountered a range of technical and non-technical challenges. This study reviews ten such projects: four in Germany and six in the Netherlands. The non-technical issues include public acceptance, a lack of regulatory framework for these systems, managing overlapping uses of the subsurface, managing changes with the providers and off-takers of thermal energy, and obtaining financing to implement these projects. Common technical issues include geological factors such as incomplete characterization of the subsurface and reservoir heterogeneity; geochemical issues such as mineral scaling, corrosion, and biofouling; lower than expected thermal recovery; and issues with system design and reliability. This review highlights benefits and challenges faced by HT-ATES projects with the goal to use the lessons learned to improve the siting, design, development, and operation of such systems. Recommendations include improved initial subsurface site characterization, use of coupled process models to optimize system design and predict system performance, cascaded uses of stored thermal energy to better utilize the stored heat, monitoring networks to provide feedback on system performance, and expanded system scale to allow for continued operation even when maintenance of some system components is required. Techno-economic modeling and risk analysis could be used to optimize such HT-ATES project design and identify key factors that will affect sustained economic viability. In addition, design flexibility is important for these systems to allow for changing conditions regarding the supply and demand of thermal energy. Adopting these findings should improve the performance and reduce the risks for future HT-ATES projects worldwide.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2026

Optimizing Energy Use in Pulp & Paper with DOE’s Energy Intensive Industries Resources

The U.S. pulp and paper industry is the third-largest energy consumer in manufacturing, accounting for roughly 10% of sector energy use. Improving energy efficiency reduces operating costs and strengthens competitiveness. To support this effort, the U.S. Department of Energy (DOE), through Oak Ridge National Laboratory (ORNL), launched the Energy Intensive Industries (EII) Initiative. A two-year pilot across 45 industrial sites identified more than 4 trillion Btu/year in potential energy savings. This presentation outlines plans for a follow-up technical assistance program tailored to pulp and paper mills. Available resources include a cost-savings scoping tool, implementation planning guidance, and technical support for applying advanced methods such as Pinch Analysis for integrated process-utilities optimization. The session introduces key Pinch Analysis principles and highlights case studies demonstrating measurable improvements. ORNL also seeks industry feedback on barriers to efficiency improvements, including technology gaps and resource needs. DOE’s broader objective is to accelerate productivity and economic competitiveness across U.S. energy-intensive industries.

Kamath, Dipti [ORNL] (ORCID:0000000278739994)↗
DOE OSTI2019

Analytical Analysis of Ac and Dc Side Harmonics of Three-level Active Neutral Point Clamped Inverter with Space Vector Modulation

This paper presents a comprehensive analytical analysis of the ac and dc side harmonics of the three-level active neutral point clamped (ANPC) inverter with space vector modulation (SVM) scheme. An analytical model to calculate the harmonics of a three-level converter with SVM is developed. The ac side output voltage harmonics and dc side current harmonics characteristics are calculated and analyzed. With the developed models, the impact of interleaving on both sides harmonics are studied which considers the modulation index, interleaving angle, and power factor. The analysis provides guideline for interleaving angle optimization to reduce the ac side power filter and dc side dc-link capacitor. The relationship between electromagnetic interference (EMI) filter corner frequency and switching frequency is also analytically derived which provides guideline for switching frequency and EMI filter design optimization. Two paralleled three-level ANPC inverters are constructed and experimental results are presented to verify the analytical analysis.

Chen, Ruirui↗
DOE OSTI2023

High Temperature Electrochemical Sensors for In-Situ Corrosion Monitoring in Coal-Based Power Generation Boilers

In this project, we successfully achieved the goals we proposed: 1. optimization and development of electrochemical sensor, 2. sensor construction and package, 3. sensor testing @Longview Power Plant and data analysis, 4. lab-scale sensor optimization and corrosion database development, 5. electrochemical and corrosion monitoring validation and 6. TEA.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Optimizing Carbon Capture, Transport, and Storage: Overcoming Challenges with Machine Learning and Cost-Benefit Analysis

Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.

Shih, Chung Yan↗
DOE OSTI2016

Non-destructive Quantitative Phase Analysis and Microstructural Characterization of Zirconium Coated U-10Mo Fuel Foils via Neutron Diffraction

This report uses neutron diffraction to investigate the crystal phase composition of uranium-molybdenum alloy foils (U-10Mo) for the CONVERT MP-1 Reactor Conversion Project, and determines the effect on alpha-uranium contamination following the deposition of a Zr metal diffusion layer by various methods: plasma spray deposition of Zr powders at LANL and hot co-rolling with Zr foils at BWXT. In summary, there is minimal decomposition of the gamma phase U-10Mo foil to alpha phase contamination following both plasma spraying and hot co-rolling. The average unit cell volume, i.e. lattice spacing, of the Zr layer can be mathematically extracted from the diffraction data; co-rolled Zr matches well with literature values of bulk Zr, while plasma sprayed Zr shows a slight increase in the lattice spacing, indicative of interstitial oxygen in the lattice. Neutron diffraction is a beneficial alternative to conventional methods of phase composition, i.e. x ray diffraction (XRD) and destructive metallography. XRD has minimal penetration depth in high atomic number materials, particularly uranium, and can only probe the first few microns of the fuel plate; neutrons pass completely through the foil, allowing for bulk analysis of the foil composition and no issues with addition of cladding layers, as in the final, aluminum-clad reactor fuel plates. Destructive metallography requires skilled technicians, cutting of the foil into small sections, hazardous etching conditions, long polishing and microscopy times, etc.; the neutron diffraction system has an automated sample loader and can fit larger foils, so there is minimal analysis preparation; the total spectrum acquisition time is ~ 1 hour per sample. The neutron diffraction results are limited by spectra refinement/calculation times and the availability of the neutron beam source. In the case of LANSCE at Los Alamos, the beam operates ~50% of the year. Following the lessons learned from these preliminary results, optimizations to the process and analysis can be made, and neutron diffraction can become a viable and efficient technique for gamma/alpha phase composition determination for nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗