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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments at LLNL [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for critical ity safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2026

Design and fabrication of a four-rod radio frequency quadrupole with a variable aperture

Radiofrequency quadrupole (RFQ) linear accelerators with variable aperture cell parameters offer an effective means of accelerating high-intensity ion beams exceeding 100 mA and have been implemented in various RFQ designs. However, in a four-rod RFQ, the use of dielectric perturbation methods to measure the voltage distribution behind the rod electrodes is not applicable when implementing variable aperture geometries, because changes in the rod shape influence the electric field at the location of the perturbation element. Therefore, it was necessary to design the rod profile for each cell such that the electric field distribution behind the rods remains unaffected by changes in the aperture. In this study, we present a method to adjust the voltage distribution by modifying the geometry of the rod electrodes according to each cell's aperture parameters. This design approach enables the integration of variable aperture cells into a four-rod RFQ linac, significantly enhancing the achievable beam current. To ensure uniform capacitance and maintain a constant rod-electrode voltage despite variations in the average aperture radius, we developed a systematic method for shaping the rod electrodes. This method was refined using two-dimensional (2D) and three-dimensional (3D) electromagnetic field simulations to optimize the electrode cross-sectional profiles. The fabricated rod electrodes were then installed in a four-rod RFQ, and the electric field distribution was measured using the perturbation method and tuned by adjusting the base plates. As a result, the measured variation of ±1.1 % confirms that this design methodology can produce a sufficiently uniform voltage distribution for high-current beam acceleration. These results demonstrate the practical feasibility of a variable-aperture four-rod RFQ linac.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Investigating the Origins of Cyclic Variability in Internal Combustion Engines Using Wall-Resolved Large Eddy Simulations

Modern internal combustion engines (ICE) operate at the ragged edge of stable operation characterized by high cycle-to-cycle variations (CCV). A key scientific challenge for ICE is the understanding, modeling, and control of CCV in engine performance, which can contribute to partial burns, misfire, and knock. The objective of this study is to use high-fidelity numerical simulations to improve the understanding of the causes of CCV. Nek5000, a leading high-order spectral element, open source code, is used to simulate the turbulent flow in the engine combustion chamber. Multicycle, wall-resolved large-eddy simulations (LESs) are performed for the General Motors (GM), Transparent Combustion Chamber (TCC-III) optical engine under motored operating conditions. The mean and root-mean-square (rms) of the in-cylinder flow fields at various piston positions are validated using particle image velocimetry (PIV) measurements during the intake and compression strokes. The large-scale flow structures, including the swirl and tumble flow patterns, are analyzed in detail and the causes for cyclic variabilities in these flow features are explained. The energy distribution across the different scales of the flow are quantified using one-dimensional (1D) energy spectra, and the effect of the tumble breakdown process on the energy distribution is examined. Finally, the insights from this study can help us develop improved engine designs with reduced cyclic variabilities in the in-cylinder flow leading to enhanced engine performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Micro-architected flow through electrodes for energy storage

Disclosed are electrochemical reactors with electrodes that have variable porosity across the electrode. The electrodes are designed and micro-architected to have variable porosity and 3D flow. In one aspect, an electrochemical cell apparatus is disclosed. The apparatus includes an electrochemical vessel and an electrochemical fluid contained in the electrochemical vessel. The apparatus further includes a porous electrode submerged in the electrochemical fluid in the electrochemical vessel, the porous electrode having different porosities in different areas of the porous electrode. The different porosities inhibit electrochemical fluid flow and increase electrical conductivity in first areas of the porous electrode with decreased porosity compared to second areas, and enable increased electrochemical fluid flow and decrease electrical conductivity in the second areas of the porous electrode with increased porosity compared to the first areas.

Beck, Victor Alfred↗
DOE OSTI2024

Experimental and Analytical Verification of ASME Section IiII Division 5 Creep-Fatigue Design Rules

The continuous advancement of structural materials and the growing demands for more reliable and economical structural components in high-temperature reactor applications have necessitated the development of comprehensive design methodologies and design rules. Mechanical degradation of structural components at elevated temperatures subjected to cyclic deformation is controlled by the creep-fatigue damage. Over the past few decades, diligent research efforts have been dedicated to refining the development of elevated temperature design rules in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section III, Division 5 and to develop conservative design rules that can effectively guard against the risk of creep-fatigue failure. In ASME Section III, Division 5, for a design to pass the creep-fatigue acceptance criteria, creep damage and fatigue damage are evaluated separately, and these damages must not violate the bi-linear creep-fatigue interaction diagram, i.e., the so-called D-diagram. The creep-fatigue damage evaluation procedure assumes that the effects of the actual cyclic loading sequence can be bounded by assuming that the individual loading cycles are uniformly distributed throughout the component design life. In this study, creep-fatigue experiments with variable amplitudes and loading sequencies were designed and performed on Alloy 617 at high temperatures. The results were analyzed to evaluate the loading history effect on creep-fatigue damage accumulation and to verify the assumptions for the creep-fatigue evaluation design rules.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Concurrent Optimization of Capital Cost and Expected O&M

Concentrating solar power (CSP) technologies can utilize heat from concentrated sunlight from a field of tracking mirrors to generate electricity, reform fuel, provide process heat, or augment fossil plant heat sources. Electricity-generating power tower systems focus light from thousands of independent heliostats onto a thermal receiver, which uses the focused light to warm a heat transfer fluid (HTF), typically, a molten nitrate salt. The HTF is then sent to a power generation cycle or diverted into thermal energy storage (TES) for later use. Thermal storage is – in principle – a straightforward proposition. However, optimal utilization of a TES resource is complex and multi-faceted: thermal energy may be dispatched to produce electricity immediately upon first availability, or thermal energy may be reserved for next-day peak periods at risk of filling storage and dumping energy, or a portion of the thermal energy can be reserved to maintain equipment temperatures, reducing power cycle startup time, etc. Many possible dispatch permutations variously emphasize producing peak power, operating through transients, expediting daily startup, etc. The best operation strategy can change day-to-day throughout the year, depending on the weather and market pricing forecasts. The project we describe in this report develops a software package that allows users to explore design optimization, operations decisions, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The software we develop is the first comprehensive design tool of its kind to incorporate all of these aspects while being deployed as open source.

14 SOLAR ENERGY↗
DOE OSTI2023

Design of a Two-Body Wave Energy Converter Featuring Controllable Geometry: Preprint

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continuing proving themselves as a promising modern renewable energy field. A wave energy converter (WEC) concept, currently being explored, is hoping to add an extra control option to WEC design is the variable-geometry WEC (VGWEC). These VGWECs attempt to incorporate controllable geometric features to adjust the floating body hydrodynamics to favor either power absorption, load shedding, or other operational goals. These variable geometry components have been proposed to be controlled on a sea-state-to-sea-state or wave-to-wave time scale depending on the force (or toque) and bandwidth limitations of the actuators required to manipulate just the controllable geometric hull features. The opportunities of having control over both the WEC geometry components and the power-take-off (PTO) have the potential to improve overall system performance and reliability if a cost-effective solution can be found for a given WEC architecture. This paper will present the recent developments and results of a VGWEC concept that incorporates variable geometry modules into a two-body WEC. In the proposed VGWEC concept, the variable geometry modules consist of air inflatable bags in the surface float and a water inflatable ring in the subsurface body. The surface float is tethered directly to the subsurface body through tether lines each connected to a separate PTO. Adjusting the geometry of both the surface and subsurface bodies along with the PTO coefficients can be shown to maximize power in design sea states while reducing motion response and PTO forces when transitioning to sea states where rated power is reached and load shedding is prioritized in hopes of increasing the sea state operational map.

geometry control↗
DOE OSTI2026

AMMT Round Robin 316H HFIR Irradiation Test Matrix and Readiness for Insertion

The Round Robin 316H HFIR-2 irradiation campaign, conducted under the Advanced Materials and Manufacturing Technologies (AMMT) Program, is designed to evaluate the variability in irradiation response of laser powder bed fusion (LPBF) stainless steel (SS)-316H across multiple national laboratories, powder heats, and processing conditions, with comparison to wrought counterparts. A total of 11 materials are intended for irradiation in the High Flux Isotope Reactor (HFIR), targeting two irradiation temperatures (400°C and 600°C) and one level of irradiation damage (2 dpa). This irradiation campaign utilizes the standardized general tensile (GENTEN) capsule design to accommodate subsized tensile specimens of these materials. Thermal analyses were performed to ensure appropriate temperature control by design and uniformity within the capsules. All the capsules for this irradiation except one have been successfully assembled, welded, and tested and are ready for HFIR insertion. The last capsule requires re-build following a failed weld. All eight capsules are intended to be inserted in HFIR cycle 517, which is scheduled to start September 8, 2026. This report summarizes the design, material selection, and readiness for insertion of the capsules.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Designing Operationally Flexible Diafiltration Membrane Systems for Critical Mineral Separations

This talk presents the design of operationally flexible diafiltration membrane systems for Li/Co recovery, and applies robust optimization methodologies using these flexible systems to generate optimal designs immune to membrane manufacturing variability and uncertain process inlet conditions. The results highlight the use of robust optimization to find design strategies and insights that may reduce technical risks arising from model uncertainties.

Yao, Jason↗
DOE OSTI2024

Treatment and Mineral Recovery from Combustion Residual Leachate and Produced Water

This talk presents the design of operationally flexible diafiltration membrane systems for Li/Co recovery, and applies robust optimization methodologies using these flexible systems to generate optimal designs immune to membrane manufacturing variability and uncertain process inlet conditions. The results highlight the use of robust optimization to find design strategies and insights that may reduce technical risks arising from model uncertainties.

Able, Chad↗
DOE OSTI2024

Visual Analytics of Multivariate Networks With Representation Learning and Composite Variable Construction

Multivariate networks are commonly found in real-world data-driven applications. Uncovering and understanding the relations of interest in multivariate networks is not a trivial task. This article presents a visual analytics workflow for studying multivariate networks to extract associations between different structural and semantic characteristics of the networks (e.g., what are the combinations of attributes largely relating to the density of a social network?). The workflow consists of a neural-network-based learning phase to classify the data based on the chosen input and output attributes, a dimensionality reduction and optimization phase to produce a simplified set of results for examination, and finally an interpreting phase conducted by the user through an interactive visualization interface. A key part of our design is a composite variable construction step that remodels nonlinear features obtained by neural networks into linear features that are intuitive to interpret. We demonstrate the capabilities of this workflow with multiple case studies on networks derived from social media usage and also evaluate the workflow with qualitative feedback from experts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Data-driven wind turbine wake modeling via probabilistic machine learning

Wind farm design primarily depends on the variability of the wind turbine wake flows to the atmospheric wind conditions and the interaction between wakes. Physics-based models that capture the wake flow field with high-fidelity are computationally very expensive to perform layout optimization of wind farms, and, thus, data-driven reduced-order models can represent an efficient alternative for simulating wind farms. In this work, we use real-world light detection and ranging (LiDAR) measurements of wind-turbine wakes to construct predictive surrogate models using machine learning. Specifically, we first demonstrate the use of deep autoencoders to find a low-dimensional latent space that gives a computationally tractable approximation of the wake LiDAR measurements. Then, we learn the mapping between the parameter space and the (latent space) wake flow fields using a deep neural network. Additionally, we also demonstrate the use of a probabilistic machine learning technique, namely, Gaussian process modeling, to learn the parameter-space-latent-space mapping in addition to the epistemic and aleatoric uncertainty in the data. Finally, to cope with training large datasets, we demonstrate the use of variational Gaussian process models that provide a tractable alternative to the conventional Gaussian process models for large datasets. Furthermore, we introduce the use of active learning to adaptively build and improve a conventional Gaussian process model predictive capability. Overall, we find that our approach provides accurate approximations of the wind-turbine wake flow field that can be queried at an orders-of-magnitude cheaper cost than those generated with high-fidelity physics-based simulations.

Deep neural networks↗
DOE OSTI2022

Creep anisotropy modeling and uncertainty quantification of an additively manufactured Ni-based superalloy

The advantages offered by additive manufacturing over traditional processes has driven a great deal of industrial and academic interest in recent years. However, the process is relatively new and requires additional investigation to become sufficiently mature for wide scale industrial adoption. Electron beam melting powder bed fusion is one technology that has shown promise for fabricating high temperature resistant materials such as nickel based superalloys. The resulting microstructures typically exhibit a strong fiber texture in the build direction giving rise to anisotropic time-dependent deformation behavior. In order to accelerate the qualification of these materials for industrial adoption accurate numerical models are needed for simulating their behavior. In this work a crystal plasticity model including non-Schmid effects is presented for capturing creep anisotropy observed in additively manufactured IN738LC. The model is calibrated via a probabilistic framework where model parameters are treated as random variables. An iterative sequential design strategy is utilized to efficiently identify the probability density of the unknown model parameters. As a case study the model is utilized to investigate the behavior of randomly oriented equiaxed grain clusters sometimes observed embedded in the additively manufactured columnar structure. A synthetic realization is simulated and uncertainty is propagated through to the full-field response. Results indicate that these features are the source of significant creep relaxation and strain accumulation which partially explains observed grain boundary decohesion at these locations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

N-Terminal Decarboxylation as a Probe for Intramolecular Contact Formation in $γ$-Glu-(Pro) n -Met Peptides

The kinetics of intramolecular-contact formation between remote functional groups in peptides with restricted conformational flexibility were examined using designed peptides with variable-length proline bridges. As probes for this motion, free radicals were produced using the • OH-induced oxidation at the C-terminal methionine residue of γ-Glu-(Pro) n -Met peptides ( n = 0–3). The progress of the radicals’ motion along the proline bridges was monitored as the radicals underwent reactions along the peptides’ backbones. Of particular interest was the reaction between the sulfur atom located in the side chain of the oxidized Met residue and the unprotonated amino group of the glutamic acid moiety. Interactions between them were probed by the radiation-chemical yields (expressed as G values) of the formation of C-centered, α-aminoalkyl radicals (αN) on the Glu residue. These radicals were monitored directly or via their reaction with p -nitroacetophenone (PNAP) to generate the optically detected PNAP •– radical anions. The yields of these αN radicals were found to be linearly dependent on the number of Pro residues. A constant decrease by 0.09 μM J –1 per spacing Pro residue of the radiation-chemical yields of G (αN) was observed. Previous reports support the conclusion that the αN radicals in these cases would have to result from (S$\therefore$N) + -bonded cyclic radical cations that arose as a result from direct contact between the ends of the peptides. Furthermore, by analogy with the rate constants for the formation of intramolecularly (S$\therefore$S) + -bonded radical cations in Met-(Pro) n -Met peptides ( J. Phys. Chem. B 2016 , 120 , 9732), the rate constants for the formation of intramolecularly (S$\therefore$N) + -bonded radical cations are activated to the same extent for all of the γ-Glu-(Pro) n -Met peptides. Thus, the continuous decrease of G (αN) with the number of Pro residues (from 0 to 3) suggests that the formation of a contact between the S-atom in the C-terminal Met residue and the N-atom of a deprotonated N-terminal amino group of Glu is controlled in peptides with 0 to 3 Pro residues by the relative diffusion of the S •+ and unoxidized N-atom. The overall rate constants of cyclization to form the (S$\therefore$N)-bonded radical cations were estimated to be 3.8 × 10 6 , 1.8 × 10 6 , and 8.1 × 10 5 s –1 for peptides with n = 0, 1, and 2 Pro residues, respectively. If activation is the same for all of the peptides, then these rate constants are a direct indication for the end-to-end dynamics along the chain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Causes and consequences of experimental variation in Nicotiana benthamiana transient expression

Infiltration of Agrobacterium tumefaciens into Nicotiana benthamiana has become a foundational technique in plant biology, enabling efficient delivery of transgenes in planta with technical ease, robust signal, and relatively high throughput. Despite transient expression’s prevalence in disciplines such as synthetic biology, little work has been done to describe and address the variability inherent in this system, a concern for experiments that rely on highly quantitative readouts. In a comprehensive analysis of N. benthamiana agroinfiltration experiments, we model sources of variability that affect transient expression. Our findings emphasize the need to validate normalization methods under the specific conditions of each study, as distinct normalization schemes do not always reduce variation either within or between experiments. Using a dataset of 1915 plants collected over three years, we develop a model of variation in N. benthamiana transient expression, using power analysis to determine the number of individual plants required for a given effect size. Drawing on our longitudinal data, these findings inform practical guidelines for minimizing variability through strategic experimental design and power analysis, providing a foundation for more robust and reproducible use of N. benthamiana in quantitative plant biology and synthetic biology applications.

Tang, Sophia N. [Joint BioEnergy Institute (JBEI),↗