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At least 1,279 records · Page 71

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DOE OSTI2018

Central Receiver Optimization

Sandia National Laboratories (Sandia) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) collaborated to optimize central receivers in the temperature range of 600-900°C suitable for advanced power cycles. It was recognized that significant cost reductions can be made in concentrating solar power (CSP) if efficiency was substantially improved. Advanced cycles such as supercritical CO 2 (sCO 2 ) power cycles offer the potential for high efficiency, but the solar collector and receiver geometry must be considered together to ensure the required inlet conditions for the turbine can be met in a cost-effective manner. This project investigated heliostat life cycle costs, heliostat field layout and associated receiver geometry to better understand the optical and thermodynamic relationship between these components in this temperature range of interest, allowing subsequent optimization. This work will assist the mission of Sandia, the Department of Energy (DOE), and CSIRO to develop sustainable, cost-competitive energy technologies for public use. The purpose of this work was to investigate factors affecting performance and costs of heliostats, including in-field heliostat testing. Alternative receiver designs designed to achieve high temperatures (900 °C and above) were also explored in conjunction with the heliostat field.

Ho, Clifford K.↗

DOE OSTI2024

Variations in γ′ formers and refractory elements for enhanced creep resistance and phase stability of an advanced Ni-based superalloy

The strong demands on increasing fuel efficiency have continuously driven the optimization of superalloys for high-performance applications. In this study, modifications to the chemistry and heat treatment of HAYNES® 282® alloy (H282) were performed by varying γ′ formers and refractory elements. It was found that increasing Ti and substituting W for some of the Mo in the newly designed alloy (Q) resulted in a significant improvement of creep resistance, up to 130% increase in creep life, compared to standard H282. It was found that Orowan loops and dislocation climb were the dominant creep deformation mechanisms in alloy Q, while extensive dislocation tangling as an additional configuration was observed in the baseline alloy. Moreover, phase stability investigations for up to 5000 h at 800 °C and 900 °C revealed a reduced formation of detrimental σ and μ phases in alloy Q when compared to H282. Atom-probe tomography (APT) revealed that the formation and growth of those phases were responsible for a decrease in Mo content in the matrix, thereby leading to a decrease in solid-solution strengthening in H282 over time. Furthermore, the coarsening of γ′ precipitates was retarded by the substitution of W for Mo, particularly under creep stress. The theoretical and experimental understanding of precipitation strengthening unraveled that higher optimal strengthening occurs at larger particle size for alloy Q, compared to the commercial formulation, further explaining the origin of enhanced creep resistance in the modified alloy.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Advancements in ion diode and triode design

Selfconsistent laminar flow models, which enable to predict the optimal cathode and anode geometry in simple diodes, must be modified to account for the anode aperture and the effect of other electrodes. An equation for charge coupled to arbitrary laminar flows is here first presented and its numerical solutions are obtained with a new method, based on mesh transformations. It is found that a close match to theoretical flows requires an increase of the simple diode voltage v{sub 0} by an amount v{sub δ}, which, for a typical case designed for zero exit angle condition, are v{sub 0} = 0.7465 and v{sub δ} = 0.0294 in adimensional units. States “in” and “out” for the anode lens are also shown, where “out” is a new and nonlinear solution for the beam expansion in a drift tube.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

WE-EF-303-04: An Advanced Image Processing Method to Improve the Spatial Resolution of Proton Radiographies

Purpose: We present an optimization method to improve the spatial resolution and the water equivalent thickness accuracy of proton radiographies. Methods: The method is designed for imaging systems measuring only the residual range of protons without relying on tracker detectors to determine the beam trajectory before and after the target. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) working as a range telescope. The method uses a decomposition approach of the residual range signal measured by the PPIC and constructs subimages with small size pixels geometrically rearranged and appropriately averaged to be merged into a final single radiography. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. Results: For the step phantom, the effective spatial resolution was found to be 4 and 3 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed X-ray radiography convolved with a Gaussian kernel equal to the proton beam spot-size. For DTA=2.5 mm and RD=2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. An extension of the method allows reducing the dose given to the patient during radiography acquisition. We show that despite a dose reduction of 25 times (leading to a dose of 0.016 mGy for the current imaging set-up), the image quality of the optimized radiographies remains fairly unaffected for both the simulated and experimental results. Conclusion: The optimization method leads to a significant increase of the spatial resolution allowing recovering image details that are unresolved in non-optimized radiographies. These results represent a major step towards clinical application of proton radiography.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Reduced Order Model Improvement and Integration into Topology Optimization

The purpose of this CRADA was to integrate a reduced order model simulation capability into advanced engineering design capabilities. This work contributed to a substantial reduction in the time required to simulate an additive manufacturing process. Shorter simulation time improves the commercial viability and practical utility of the Sunata software and may lead to wider adoption of additive manufacturing processes.

Robbins, Joshua↗

DOE OSTI2021

Spot Size Optimization of the Scorpius Accelerator

The Scorpius Linear Induction Accelerator (LIA) is being developed by the Advanced Sources and Diagnostics (ASD) Project and will complement other U1a capabilities by providing a multi-pulse, DARHT-class, flash-radiography capability. Commissioning activities are expected to end in Spring of 2026. All of the diagnostics discussed in this chapter are relevant to LIAs that generate high-current relativistic electron beams, and some diagnostics will also be relevant to other accelerators. The Scorpius Accelerator will be the world’s most advance LIA. Although significant technological advancements have been incorporated throughout the machine, many performance aspects of Scorpius will be similar to those of FXR and DARHT Axis-I and -II. These LIAs offer the same challenges, whether it is suppressing beam instabilities, improving diagnostic accuracy, validating computer simulations and beam tunes, or reducing beam-target interaction effects. However, the ultimate figure of merit is consistent between these LIAs, which is spot size and dose.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Design Optimization for Printed Melt Wire Arrays Encapsulation

As part of the Nuclear Energy Enabling Technology (NEET) Advanced Sensor and Instrumentation (ASI) Program, Idaho National Laboratory (INL) has recently established in-house capabilities to fabricate and test new advanced-manufactured sensors for measuring peak irradiation temperature within a nuclear test reactor. Although methods of real-time temperature monitoring, such as thermocouples, may be used, the complexity of feedthroughs and attachments to collect real-time measurements greatly increases the cost of the experiment. Instead, passive monitoring techniques may be used for peak- temperature measurement that exploit the melting point of well-characterized materials (standard melt wires) to infer peak reactor temperatures. However, limited available space for instrumentation during experiments introduces an additional challenge. To accommodate this, INL has expanded its temperature- detection instrumentation capabilities to include advanced manufactured (AM) melt wires for peak irradiation temperature measurements. These melt wires can determine peak temperatures while also accommodate space limitations in irradiation experiments. In an effort to improve performance reliability of AM meltwire capabilities, a process was developed and tested to identify the significance of entrapping a high purity inert atmosphere within the packaging of printed melt wire arrays. The materials used in this study were aluminum, zinc, and tin encapsulated in high purity helium within a stainless steel (SS) 316 container. Tin, with a low melting point of approximately 230°C, Zn with a mid-melting point of approximately 420°C, and Al with a high melting point of approximately 660°C. This report describes the design, fabrication process, furnace testing and X-ray Computed Tomography (XCT) evaluation. Results show a successful outcome in creating an inert gas encapsulation and high-resolution evaluation methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Optimization of LSCF Air Electrodes for Infiltration

Presentation at the 48th International Conference and Exposition on Advanced Ceramics and Composites (ICACC 2024).

Liu, Jian↗

DOE OSTI2024

CARD: CFD for Advanced Reactor Design

Software Tools and Expertise To Address Multiphase Flow Challenges in<p>Research, Design, and Optimization</p><p>This is the annual CARD project update to be presented at the 2024 FECM/NETL Spring R&D Project Review Meeting.</p>

Dietiker, Jeff↗

DOE OSTI2012

Progress towards an Optimization Methodology for Combustion-Driven Portable Thermoelectric Power Generation Systems

Enormous military and commercial interests exist in developing quiet, lightweight, and compact thermoelectric (TE) power generation systems. This paper investigates design integration and analysis of an advanced TE power generation system implementing JP-8 fueled combustion and thermal recuperation. Design and development of a portable TE power system using a JP-8 combustor as a high temperature heat source and optimal process flows depend on efficient heat generation, transfer, and recovery within the system are explored. Design optimization of the system required considering the combustion system efficiency and TE conversion efficiency simultaneously. The combustor performance and TE sub-system performance were coupled directly through exhaust temperatures, fuel and air mass flow rates, heat exchanger performance, subsequent hot-side temperatures, and cold-side cooling techniques and temperatures. Systematic investigation of this system relied on accurate thermodynamic modeling of complex, high-temperature combustion processes concomitantly with detailed thermoelectric converter thermal/mechanical modeling. To this end, this work reports on design integration of systemlevel process flow simulations using commercial software CHEMCADTM with in-house thermoelectric converter and module optimization, and heat exchanger analyses using COMSOLTM software. High-performance, high-temperature TE materials and segmented TE element designs are incorporated in coupled design analyses to achieve predicted TE subsystem level conversion efficiencies exceeding 10%. These TE advances are integrated with a high performance microtechnology combustion reactor based on recent advances at the Pacific Northwest National Laboratory (PNNL). Predictions from this coupled simulation established a basis for optimal selection of fuel and air flow rates, thermoelectric module design and operating conditions, and microtechnology heat-exchanger design criteria. This paper will discuss this simulation process that leads directly to system efficiency power maps defining potentially available optimal system operating conditions and regimes. This coupled simulation approach enables pathways for integrated use of high-performance combustor components, high performance TE devices, and microtechnologies to produce a compact, lightweight, combustion driven TE power system prototype that operates on common fuels.

Heat Transfer↗

DOE OSTI2024

Confinement performance predictions for a high field axisymmetric tandem mirror

This paper presents Hammir tandem mirror confinement performance analysis based on Realta Fusion's first-of-a-kind model for axisymmetric magnetic mirror fusion performance. This model uses an integrated end plug simulation model including, heating, equilibrium, and transport combined with a new formulation of the plasma operation contours (POPCONs) technique for the tandem mirror central cell. Using this model in concert with machine learning optimization techniques, it is shown that an end plug utilizing high temperature superconducting magnets and modern neutral beams enables a classical tandem mirror pilot plant producing a fusion gain Q > 5. The approach here represents an important advance in tandem mirror design. The high fidelity end plug model enables calculations of heating and transport in the highly non-Maxwellian end plug to be made more accurately. The detailed end plug modelling performed in this work has highlighted the importance of classical radial transport and neutral beam absorption efficiency on end plug viability. The central cell POPCON technique allows consideration of a wide range of parameters in the relatively simple near-Maxwellian central cell, facilitating the selection of more optimal central cell plasmas. These advances make it possible to find more conservative classical tandem mirror fusion pilot plant operating points with lower temperatures, neutral beam energies, and end plug performance requirements than designs in the literature. Despite being more conservative, it is shown that these operating points have sufficient confinement performance to serve as the basis of a viable fusion pilot plant provided that they can be stabilized against MHD and trapped particle modes.

FOS: Physical sciences↗

DOE OSTI2021

PPPL Laboratory Directed Research and Development (Project Final Reports, FY2018 - FY2020)

The U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) is a collaborative national center for fusion energy science, basic sciences, and advanced technology. The Laboratory has three major missions: (1) to develop the scientific knowledge and advanced engineering to enable fusion to power the U.S. and the world; (2) to advance the science of nanoscale fabrication for technologies of tomorrow; and (3) to further the development of the scientific understanding of the plasma universe from laboratory to astrophysical scales. PPPL’s Laboratory Directed Research and Development (LDRD) program supports and encourages creativity and innovation and contributes to its long-term viability. New scientific and technical research areas emerge and are nurtured through the program. Furthermore, new capabilities are developed to enable the Laboratory to meet its and DOE’s missions. The program is used to systematically diversify the Laboratory’s programs and mission. In the last few years, the program has started projects in nanomaterial synthesis, microelectronics, advanced x-ray spectroscopy, high-energy-density physics, superconducting magnet technology, machine learning and artificial intelligence, 3D magnetic fields to optimize fusion plasmas, integration of permanent magnets with simple high-field magnets to reduce the cost of producing complex 3D magnetic fields, advanced computational methods for predictive understanding and control of fusion plasma, development of quantum computing algorithms for plasma physics, liquid metal plasma-facing components for fusion reactors, virtual engineering, and plasma-based space propulsion. The program is also the vehicle to recruit and train talented scientists and engineers with the new skills needed to perform the Laboratory’s mission. Many of the new hires through the program go on to become world-class scientists and engineers in their fields. This report provides descriptions and accomplishments of those LDRD projects that were completed during fiscal years 2018 through 2020.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Confinement performance predictions for a high field axisymmetric tandem mirror

This paper presents a Hammir tandem mirror confinement performance analysis based on Realta Fusion’s first-of-a-kind model for axisymmetric magnetic mirror fusion performance. This model uses an integrated end plug simulation model including, heating, equilibrium and transport combined with a new formulation of the plasma operation contours (POPCONs) technique for the tandem mirror central cell. Using this model in concert with machine learning optimization techniques, it is shown that an end plug utilizing high temperature superconducting magnets and modern neutral beams enables a classical tandem mirror pilot plant producing a fusion gain Q > 5. The approach here represents an important advance in tandem mirror design. The high-fidelity end plug model enables calculations of heating and transport in the highly non-Maxwellian end plug to be made more accurately. The detailed end plug modelling performed in this work has highlighted the importance of classical radial transport and neutral beam absorption efficiency on end plug viability. The central cell POPCON technique allows consideration of a wide range of parameters in the relatively simple near-Maxwellian central cell, facilitating the selection of more optimal central cell plasmas. These advances make it possible to find more conservative classical tandem mirror fusion pilot plant operating points with lower temperatures, neutral beam energies and end plug performance requirements than designs in the literature. Despite being more conservative, it is shown that these operating points have sufficient confinement performance to serve as the basis of a viable fusion pilot plant provided that they can be stabilized against magnetohydrodynamic and trapped particle modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Gradient boosting machine for modeling the energy consumption of commercial buildings

Accurate savings estimations are important to promote energy efficiency projects and demonstrate their cost-effectiveness. The increasing presence of advanced metering infrastructure (AMI) in commercial buildings has resulted in a rising availability of high frequency interval data. These data can be used for a variety of energy efficiency applications such as demand response, fault detection and diagnosis, and heating, ventilation, and air conditioning (HVAC) optimization. This large amount of data has also opened the door to the use of advanced statistical learning models, which hold promise for providing accurate building baseline energy consumption predictions, and thus accurate saving estimations. The gradient boosting machine is a powerful machine learning algorithm that is gaining considerable traction in a wide range of data driven applications, such as ecology, computer vision, and biology. In the present work an energy consumption baseline modeling method based on a gradient boosting machine was proposed. To assess the performance of this method, a recently published testing procedure was used on a large dataset of 410 commercial buildings. The model training periods were varied and several prediction accuracy metrics were used to evaluate the model's performance. The results show that using the gradient boosting machine model improved the R-squared prediction accuracy and the CV(RMSE) in more than 80 percent of the cases, when compared to an industry best practice model that is based on piecewise linear regression, and to a random forest algorithm.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Optimized System for On-Route Fast Charging of Battery-Electric Shuttle Buses

Electrifying cars, buses, and trucks is an attractive means of reducing energy use and emissions because it involves more efficient drivetrain components and minimal restructuring of the transportation network. Transit buses, driving fixed routes, help minimize driver range anxiety by properly sizing energy storage systems. A major challenge to fully electrifying transit buses is providing the amount of energy they consume in a day of driving. To enable a full day of operation without charging, batteries need to be large, which could be expensive and heavy. This work utilizes real-world transit bus data used in a battery-electric drivetrain model to co-optimize charger locations, charger power levels, and vehicle battery sizes.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Atomic Layer Deposition (ALD) of Metal and Metal Oxide Films: A Surface Science Study (Final Report)

36 MATERIALS SCIENCE↗

DOE OSTI2026

Atomic Layer Deposition (ALD) of Metal and Metal Oxide Films: A Surface Science Study (Final Report)

This is the final report for this project. The long-term objective of our project is to develop a general molecular-level picture of the surface chemistry associated with ALD processes. Our central hypothesis is that the chemistry of ALD precursors can differ significantly from that seen in solution. Awareness of such differences should provide general guidelines on what to watch for when synthesizing new ALD precursors and designing and optimizing new ALD processes, especially in terms of minimizing the incorporation of impurities in the growing films and of carrying out depositions under mild pressure and temperature conditions. The main objective of our research project has been to advance the fundamental knowledge of the surface chemistry of ALD precursors needed for the design and optimization of film deposition processes. A modern surface-science approach has been implemented to both elucidate the mechanism of the reactions of the precursors on the surface and characterize the composition and morphology of the growing films. In general, emphasis is being placed on: • Identifying the primary reactions that may lead to the deposition of clean films; •Identifying the secondary reactions that may help the ALD process, by, for instance, helping with the reduction (or oxidation) of the metal atom; • Identifying the secondary reactions that may lead to the deposition of undesirable impurities in the growing films; • Determining the kinetic parameters of the relevant surface reactions in order to define the optimum conditions for film deposition and to minimize impurity deposition. • Characterizing the nature of the resulting films, with focus on their stoichiometry and on the final oxidation states of the constituent elements; and • Using the information obtained to propose better precursors for given ALD processes.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling

Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property can lead to significant advancements in scientific discovery. Graph Neural Networks (GNNs) represent the state-of-the-art approach for modeling atomistic material data thanks to their capacity to capture complex relational structures. While machine learning performance has historically improved with larger models and datasets, GNNs for atomistic materials modeling remain relatively small compared to large language models (LLMs), which leverage billions of parameters and terabyte-scale datasets to achieve remarkable performance in their respective domains. To address this gap, we explore the scaling limits of GNNs for atomistic materials modeling by developing a foundational model with billions of parameters, trained on extensive datasets in terabytescale. Our approach incorporates techniques from LLM libraries to efficiently manage large-scale data and models, enabling both effective training and deployment of these large-scale GNN models. This work addresses three fundamental questions in scaling GNNs: the potential for scaling GNN model architectures, the effect of dataset size on model accuracy, and the applicability of LLM-inspired techniques to GNN architectures. Specifically, the outcomes of this study include (1) insights into the scaling laws for GNNs, highlighting the relationship between model size, dataset volume, and accuracy, (2) a foundational GNN model optimized for atomistic materials modeling, and (3) a GNN codebase enhanced with advanced LLM-based training techniques. Our findings lay the groundwork for large-scale GNNs with billions of parameters and terabyte-scale datasets, establishing a scalable pathway for future advancements in atomistic materials modeling.

Li, Chaojian [ORNL] (ORCID:0000000340309777)↗