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DOE OSTI2022

A Robust Processing Approach for Producing Highly Loaded Dispersion Fuels

A robust fabrication method, resulting in higher yields, to produce highly loaded U3Si2-Al dispersion fuels for converting research reactors from a high enriched to a low enriched uranium fuel needs to be developed. To reliably produce a highly loaded dispersion fuel, process changes need to be implemented where the traditional approach has experienced challenges and poor yields. The present work describes the key changes needed. Parts of the work were done with uranium silicide and parts were completed with a representative silicide surrogate. The major deviations from traditional fabrication methods are associated with a refinement in particle size distribution, method for compacting to achieve complex shapes, and welding of the aluminum picture frame used to encapsulate the fuel compact. Methods for rolling and arc melting are also discussed. By using the methods described within, fabricating a highly loaded dispersion fuel that can meet stringent fuel homogeneity and geometry requirements at higher yields and lower costs may be possible.

U3Si2, HFIR, dispersion fuel, Uranium, Research Re↗

DOE OSTI2022

A single-atom library for guided monometallic and concentration-complex multimetallic designs

Atomically dispersed single-atom catalysts have the potential to bridge heterogeneous and homogeneous catalysis. Dozens of single-atom catalysts have been developed, and they exhibit notable catalytic activity and selectivity that are not achievable on metal surfaces. Although promising, there is limited knowledge about the boundaries for the monometallic single-atom phase space, not to mention multimetallic phase spaces. Here, single-atom catalysts based on 37 monometallic elements are synthesized using a dissolution-and-carbonization method, characterized and analyzed to build the largest reported library of single-atom catalysts. In conjunction with in situ studies, we uncover unified principles on the oxidation state, coordination number, bond length, coordination element and metal loading of single atoms to guide the design of single-atom catalysts with atomically dispersed atoms anchored on N-doped carbon. We utilize the library to open up complex multimetallic phase spaces for single-atom catalysts and demonstrate that there is no fundamental limit on using single-atom anchor sites as structural units to assemble concentration-complex single-atom catalyst materials with up to 12 different elements. Furthermore, our work offers a single-atom library spanning from monometallic to concentration-complex multimetallic materials for the rational design of single-atom catalysts.

36 MATERIALS SCIENCE↗

NASA NTRS1980

Spacecraft loads methodology - Transient vs. shock spectra method

The methodology for the establishment of spacecraft loads is strongly influenced by project constraints which include the cost, schedule and allowable weight. The most rigorous approach is the transient loads analysis which requires a composite mathematical model of the spacecraft and launch vehicle. The structural member loads for the entire composite structure are computed by applying the forcing functions, which represent various dynamic environments during the mission, to the composite model. Although this method ideally leads to a lightweight design, it is costly and time consuming due to complex interfaces involving many organizations. To reduce complexity and cost a shock spectra method has been used to design spacecraft structures. This method utilizes envelopes of shock spectra of launch vehicle accelerations obtained from analysis and/or flight measurements. Since only limited information on the launch vehicle model is involved in this process the design loads iteration cycle can be rapidly performed within the payload organization. In the present paper, these two methods will be evaluated by comparing the loads for several spacecraft. Flight measured loads will also be used in the evaluation.

Chen, J. C.↗

DOE OSTI2023

Highly Robust and Efficient Blechert-Type Cyclic(alkyl)(amino)carbene Ruthenium Complexes for Olefin Metathesis

The first Blechert-type ruthenium complexes containing cyclic(alkyl)(amino)carbene (CAAC) ligands are reported. Furthermore, these catalysts demonstrate remarkable thermal stability in solution and excellent catalytic performances at low catalytic loading (up to 0.005 mol%) in ring-closing metathesis (RCM), macro-RCM, ring-closing enyne metathesis (RCEYM), cross-metathesis (CM), ethenolysis and ring-opening cross metathesis (ROCM). Moreover, up to 95% ee was obtained in asymmetric ring-opening cross metathesis (AROCM) and 57% ee asymmetric cross-metathesis (ACM)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Modeling Electric Vehicle Charging Load Using Origin-Destination Data

The accelerating adoption of electric vehicles (EVs) poses challenges to the power grid, necessitating precise representation of mobility patterns for effective infrastructure upgrades. Traditional simulation-based charging demand estimation faces limitations in generating trip chains reflective of actual travel patterns without complex network modeling. Hence, an innovative agent-based trip chain generation model is introduced to overcome these challenges. Drawing from the National Household Travel Survey (NHTS) and the NextGen NHTS origin-destination add-on data for Clarke County, Georgia, this study proposes a simulation method capturing both temporal and spatial mobility patterns without relying on extensive network topology data. The resulting trip chains predict EV charging load at the Census Block Group level, validated with a 1.03 correlation to actual trip counts, affirming their reflective accuracy. Two charging scenarios, residential-only and charging-everywhere, reveal distinct demand profiles. The charging-everywhere scenario aligns closely with the trip profile, while the residential-only scenario exhibits an afternoon peak slightly surpassing the former. This study contributes a data-driven charging demand estimation methodology, offering critical insights for grid resiliency planning amid the evolving landscape of EV adoption.

Pan, Melrose↗

DOE OSTI2021

Reduced Order Model of Transactive Bidding Loads

Transactive energy (TE) has been identified to provide better grid efficiency and reliability by market-based transactive exchanges between energy producers and energy consumers. Simulations of TE systems are crucial to evaluate the benefits and impacts of different transactive mechanisms. However, such simulations can be time consuming due to the information exchange between various participants and complex co-simulation environments. In this paper, we develop a reduced order model to speed up the simulation of transactive systems in TE simulation platform (TESP) while achieving very low error between the reduced order and full model results. Specifically, the developed reduced order model consists of an aggregate responsive load agent which utilizes two Recurrent Neural Networks (RNNs) with Long Short-Term Memory units (LSTMs) to enable transactive elements to collectively participate in the TE system. The proposed aggregate responsive load (ARL) agent is able to produce similar transactive behaviors to the full simulation model while achieving significant simulation time reduction. Finally, we also show that the developed model enables generalization of simulation results across different dates and across different number of loads included in the simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Simultaneous shape and topology optimization of inflatable soft robots

Simultaneous shape and topology optimization is used to design pressure-activated inflatable soft robots. The pressure loaded boundary is meshed conformingly and shape optimized, while the morphology of the robot is topology optimized. The design objective is to exert maximum force on an object, i.e. to produce soft “grippers”. The robot’s motion is modeled using nearly incompressible finite deformation hyperelasticity. To ensure stability of the robot, the buckling load factors obtained via linearized buckling analyses are constrained. The finite element method is used to evaluate the optimization cost and constraint functions and the adjoint method is employed to compute their sensitivities. The numerical examples produce pressure-driven soft robots with varying complexity. We also compare our simultaneous optimization results to those obtained via sequential topology and then shape optimization.

42 ENGINEERING↗

NASA NTRS2000

Simulating Fatigue Crack Growth in Spiral Bevel Gears

The majority of helicopter transmission systems utilize spiral bevel gears to convert the horizontal power from the engine into vertical power for the rotor. Due to the cyclical loading on a gear's tooth, fatigue crack propagation can occur. In rotorcraft applications, a crack's trajectory determines whether the gear failure will be benign or catastrophic for the aircraft. As a result, the capability to predict crack growth in gears is significant. A spiral bevel gear's complex shape requires a three dimensional model of the geometry and cracks. The boundary element method in conjunction with linear elastic fracture mechanics theories is used to predict arbitrarily shaped three dimensional fatigue crack trajectories in a spiral bevel pinion under moving load conditions. The predictions are validated by comparison to experimental results. The sensitivity of the predictions to variations in loading conditions and crack growth rate model parameters is explored. Critical areas that must be understood in greater detail prior to predicting more accurate crack trajectories and crack growth rates in three dimensions are identified.

Spievak, Lisa E.↗

DOE OSTI2026

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗

NASA NTRS2008

Reliability and Confidence Interval Analysis of a CMC Turbine Stator Vane

High temperature ceramic matrix composites (CMC) are being explored as viable candidate materials for hot section gas turbine components. These advanced composites can potentially lead to reduced weight, enable higher operating temperatures requiring less cooling and thus leading to increased engine efficiencies. However, these materials are brittle and show degradation with time at high operating temperatures due to creep as well as cyclic mechanical and thermal loads. In addition, these materials are heterogeneous in their make-up and various factors affect their properties in a specific design environment. Most of these advanced composites involve two- and three-dimensional fiber architectures and require a complex multi-step high temperature processing. Since there are uncertainties associated with each of these in addition to the variability in the constituent material properties, the observed behavior of composite materials exhibits scatter. Traditional material failure analyses employing a deterministic approach, where failure is assumed to occur when some allowable stress level or equivalent stress is exceeded, are not adequate for brittle material component design. Such phenomenological failure theories are reasonably successful when applied to ductile materials such as metals. Analysis of failure in structural components is governed by the observed scatter in strength, stiffness and loading conditions. In such situations, statistical design approaches must be used. Accounting for these phenomena requires a change in philosophy on the design engineer s part that leads to a reduced focus on the use of safety factors in favor of reliability analyses. The reliability approach demands that the design engineer must tolerate a finite risk of unacceptable performance. This risk of unacceptable performance is identified as a component's probability of failure (or alternatively, component reliability). The primary concern of the engineer is minimizing this risk in an economical manner. The methods to accurately determine the service life of an engine component with associated variability have become increasingly difficult. This results, in part, from the complex missions which are now routinely considered during the design process. These missions include large variations of multi-axial stresses and temperatures experienced by critical engine parts. There is a need for a convenient design tool that can accommodate various loading conditions induced by engine operating environments, and material data with their associated uncertainties to estimate the minimum predicted life of a structural component. A probabilistic composite micromechanics technique in combination with woven composite micromechanics, structural analysis and Fast Probability Integration (FPI) techniques has been used to evaluate the maximum stress and its probabilistic distribution in a CMC turbine stator vane. Furthermore, input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Since the measured data for the ceramic matrix composite properties is very limited, obtaining a probabilistic distribution with their corresponding parameters is difficult. In case of limited data, confidence bounds are essential to quantify the uncertainty associated with the distribution. Usually 90 and 95% confidence intervals are computed for material properties. Failure properties are then computed with the confidence bounds. Best estimates and the confidence bounds on the best estimate of the cumulative probability function for R-S (strength - stress) are plotted. The methodologies and the results from these analyses will be discussed in the presentation.

Murthy, Pappu L. N.↗

NASA NTRSDate not supplied

Launch Vehicle Loads Analysis Using Pressure-Sensitive Paint

Pressure transducers have been the instrumentation of choice for measuring unsteady flow phenomena. With recent advances in high-speed cameras, high-powered LEDs, and fast-response, pressure-sensitive paint, the unsteady pressure-sensitive paint (uPSP) technique has become a valuable alternative for production wind tunnel facilities, enabling time-resolved measurements of unsteady pressure fluctuations over a dense spatial grid on a wind tunnel model. Launch vehicle ground tests have proven to be a particularly well-matched application for uPSP due to the high signal level relative to tunnel background acoustics, relatively simple camera optical access, and rigidity of the model in wind-on test conditions. This presentation will highlight recent advances in data reduction of uPSP measurement data from recent launch vehicle wind tunnel tests at the NASA Ames Unitary Plan Wind Tunnel Complex (UPWT). The system can provide both localized surface pressure spectra as well as regional or zonal estimates of turbulence correlation model parameters. In addition, integrated vehicle-scale loads can be provided for buffet analysis. Data is reduced at the on-premise NASA Advanced Supercomputer (NAS) Division for just-in-time delivery of results during an ongoing wind tunnel test.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

Launch Vehicle Loads Analysis Using Pressure-Sensitive Paint

pressure-sensitive paint↗

DOE OSTI2015

Investigating size effects of complex nanostructures through Young-Laplace equation and finite element analysis

Analytical studies on the size effects of a simply-shaped beam fixed at both ends have successfully explained the sudden changes of effective Young's modulus as its diameter decreases below 100 nm. Yet they are invalid for complex nanostructures ubiquitously existing in nature. In accordance with a generalized Young-Laplace equation, one of the representative size effects is transferred to non-uniformly distributed pressure against an external surface due to the imbalance of inward and outward loads. Because the magnitude of pressure depends on the principal curvatures, iterative steps have to be adopted to gradually stabilize the structure in finite element analysis. Computational results are in good agreement with both experiment data and theoretical prediction. Furthermore, the investigation on strengthened and softened Young's modulus for two complex nanostructures demonstrates that the proposed computational method provides a general and effective approach to analyze the size effects for nanostructures in arbitrary shape.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

THF co-solvent pretreatment prevents lignin redeposition from interfering with enzymes yielding prolonged cellulase activity

Background: Conventional aqueous dilute sulfuric acid (DSA) pretreatment of lignocellulosic biomass facilitates hemicellulose solubilization and can improve subsequent enzymatic digestibility of cellulose to fermentable glucose. However, much of the lignin after DSA pretreatment either remains intact within the cell wall or readily redeposits back onto the biomass surface. This redeposited lignin has been shown to reduce enzyme activity and contribute to rapid enzyme deactivation, thus, necessitating significantly higher enzyme loadings than deemed economical for biofuel production from biomass. Results: In this study, we demonstrate how detrimental lignin redeposition on biomass surface after pretreatment can be prevented by employing Co-solvent Enhanced Lignocellulosic Fractionation (CELF) pretreatment that uses THF–water co-solvents with dilute sulfuric acid to solubilize lignin and overcome limitations of DSA pretreatment. We first find that enzymatic hydrolysis of CELF-pretreated switchgrass can sustain a high enzyme activity over incubation periods as long as 5 weeks with enzyme doses as low as 2 mg protein/g glucan to achieve 90% yield to glucose. A modified Ninhydrin-based protein assay revealed that the free-enzyme concentration in the hydrolysate liquor, related to enzyme activity, remained unchanged over long hydrolysis times. DSA-pretreated switchgrass, by contrast, had a 40% drop in free enzymes in solution during incubation, providing evidence of enzyme deactivation. Furthermore, measurements of enzyme adsorption per gram of lignin suggested that CELF prevented lignin redeposition onto the biomass surface, and the little lignin left in the solids was mostly integral to the original lignin–carbohydrate complex (LCC). Scanning electron micrographs and NMR characterization of lignin supported this observation. Conclusions: Enzymatic hydrolysis of solids from CELF pretreatment of switchgrass at low enzyme loadings was sustained for considerably longer times and reached higher conversions than for DSA solids. Analysis of solids following pretreatment and enzymatic hydrolysis showed that prolonged cellulase activity could be attributed to the limited lignin redeposition on the biomass surface making more enzymes available for hydrolysis of more accessible glucan.

09 BIOMASS FUELS↗

DOE OSTI2022

3D ion gyro-orbit heat load predictions for NSTX-U

Abstract High power tokamaks operate with divertor heat loads capable of destroying the plasma facing components (PFCs). High fidelity heat load predictions are necessary to ascertain the PFC state for design and during operation. Typical heat flux calculations are 2D, time invariant, and assume that power flows directly along the magnetic field lines (the optical approximation). These assumptions neglect the complex 3D geometries employed to protect the PFCs, the time varying nature of the plasma and PFC thermal state, and the helical trajectories of ions with finite Larmor radii (the gyro-orbit approximation). An integrated software framework, the heat flux engineering analysis toolkit (HEAT), was developed to generate time varying optical heat loads applied to real engineering computer aided design (CAD) (Looby et al 2022 Fusion Sci. Technol. 78 10–27). Recently, an ion-gyro orbit module has been added to HEAT. This module calculates the helical trajectories of ions as they gyrate about the magnetic field lines using kinetic theory macro-particles to accelerate the calculation. First, the new gyro-orbit module will be presented. Next, a comparison to existing research is performed. Finally, an analysis of the gyro-orbit heat loads for NSTX-U is presented for diverted discharges using the engineering CAD models utilized for PFC fabrication. Including these gyro-orbit effects can enhance the PFC performance by ‘smearing’ out the magnetic shadows associated with the castellated fish-scaled geometry. Simultaneously, the helical trajectories can degrade performance when they load narrow regions on edges and corners with high heat fluxes. Analysis of the trade-offs between these competing effects is included, and regions for further investigation are identified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗

DOE OSTI2024

Efficient Modeling of Floating Wind Arrays Including Current Loads and Seabed Bathymetry: Preprint

Capabilities for modeling the effects of seabed bathymetry and current drag loads on a floating wind farm are now available in an open-source model for quasi-static analysis. In this model, mooring lines and dynamic cables are represented by a quasistatic solver that can quickly represent complex mooring/cabling arrangements and arrays of floating bodies. To account for seabed bathymetry, we expand the model to include a surface mesh that captures changes in water depth over a rectangular grid. We formulate modifications to the catenary equations that capture a mooring line's profile and tensions when contacting a slope seabed. To account for current drag loads on mooring lines and dynamic cables, we formulate a novel technique that rotates the reference frame so that the vector sum of the the weight and the current force are used in the catenary equations, while accounting for the seabed orientation. To complete the system, current drag loads on floating substructures are handled by inclusion of strip-theory drag calculations. These new capabilities are verified by comparing with results from the established offshore dynamics models MoorDyn and OrcaFlex in equivalent steady-state scenarios. The results show very good agreement for both sloped seabeds and current loads. With computation times of the quasi-static model typically under one second, the model additions are a useful capability toward rapidly evaluating a floating wind array's response to environmental loads under realistic site conditions.

bathymetry↗

DOE OSTI2023

Triplet Fusion Upconversion for Photocuring 3D-Printed Particle-Reinforced Composite Networks

High energy photons (λ < 400 nm) are frequently used to initiate free radical polymerizations to form polymer networks, but are only effective for transparent objects. This phenomenon poses a major challenge to additive manufacturing of particle-reinforced composite networks since deep light penetration of short-wavelength photons limits the homogeneous modification of physicochemical and mechanical properties. Herein, the unconventional, yet versatile, multiexciton process of triplet–triplet annihilation upconversion (TTA-UC) is employed for curing opaque hydrogel composites created by direct-ink-write (DIW) 3D printing. TTA-UC converts low energy red light (λ max = 660 nm) for deep penetration into higher-energy blue light to initiate free radical polymerizations within opaque objects. Further, as proof-of-principle, hydrogels containing up to 15 wt.% TiO 2 filler particles and doped with TTA-UC chromophores are readily cured with red light, while composites without the chromophores and TiO 2 loadings as little as 1–2 wt.% remain uncured. Importantly, this method has wide potential to modify the chemical and mechanical properties of complex DIW 3D-printed composite polymer networks.

36 MATERIALS SCIENCE↗