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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Analysis of the weighted shifted boundary method for the Poisson and Stokes problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods, and relies on reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by properly shifting the location and values of the boundary conditions. This avoids integration over cut cells and the associated implementation issues. Recently, the Weighted SBM (WSBM) was proposed for the Navier-Stokes equations with free surfaces and the Stokes flow with moving boundaries. The attribute “weighted” in the name WSBM stems from the fact that its variational form is weighted with the elemental volume fraction of active fluid. The motivation for the development of the WSBM was the preservation of the volume of active fluid to a higher degree of accuracy, which in turn resulted in improved stability and robustness characteristics in moving-boundary, time-dependent simulations. In this article, we present the numerical analysis of the WSBM formulations for the Poisson and Stokes problems. We give mathematical conditions under which the bilinear forms defining the discrete variational formulations are uniformly coercive (Poisson problem) or inf-sup stable (Stokes problem). By these results, stability and optimal convergence is proven in the natural norm; L2-error estimates can also be derived.

Approximate domain boundaries↗
DOE OSTI2022

MIDAS-DC-AC Tool: Fully Automating the Acquisition of AC Power Flow Solution (MIDAS-DC2AC)

MIDAS DC2AC is an automated tool for achieving a converged AC power flow solution from any dispatch, e.g., determined using DC power flow model based optimal power flow. The entire process is free of human interference. It is usually encountered in practice that, even with a DC power flow solution, acquiring the solved AC power flow solution, if exists, sometimes could be a challenging task, especially during the planning stage. It is also difficult to distinguish the unsolvable cases from diverging iterations. Manual adjustments to approach the desired power flow condition has been largely relied on in the past using lots of engineering heuristics. This tool provides a systematic way to first achieve a solvable AC power flow case by modifying the power flow condition, and then try to track the AC power flow solution while gradually removing the adopted changes. If all adopted changes can be completely removed, then the original AC power flow solution is obtained. Otherwise, insights for actionable controls are derived to help operation and planning. Currently, this tool has been implemented in Python using SIEMENS PTI PSS/E as power flow solver, where only adjusting generator terminal voltage set point is considered as an available means to try to turn an unsolved power flow to a solved one. In future, more means should be considered, including the operation of tap-changing transformers, switched shunts and redispatch of active power.

Tan, Jin↗
DOE OSTI2022

DC-AC Tool: Fully Automating the Acquisition of AC Power Flow Solution

DC2AC is an automated tool for achieving a converged AC power flow solution from any dispatch, e.g., determined using DC power flow model based optimal power flow. The entire process is free of human interference. It is usually encountered in practice that, even with a DC power flow solution, acquiring the solved AC power flow solution, if exists, sometimes could be a challenging task, especially during the planning stage. It is also difficult to distinguish the unsolvable cases from diverging iterations. Manual adjustments to approach the desired power flow condition has been largely relied on in the past using lots of engineering heuristics. This tool provides a systematic way to first achieve a solvable AC power flow case by modifying the power flow condition, and then try to track the AC power flow solution while gradually removing the adopted changes. If all adopted changes can be completely removed, then the original AC power flow solution is obtained. Otherwise, insights for actionable controls are derived to help operation and planning. Currently, this tool has been implemented in Python using SIEMENS PTI PSS/E as power flow solver, where only adjusting generator terminal voltage set point is considered as an available means to try to turn an unsolved power flow to a solved one. In future, more means should be considered, including the operation of tap-changing transformers, switched shunts and redispatch of active power.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mechanistic Insights and Rational Design of Ca-Doped CeO 2 Catalyst for Acetic Acid Ketonization

Carboxylic acid ketonization has recently gained significant attention to produce biomass-derived hydrocarbon fuels as it not only removes the highly reactive carboxylic functional group but also increases the size of the carbon chain. In this work, Ca-doped CeO 2 -based catalysts were investigated for acetic acid ketonization using a combined experimental and computational approach. Acetic acid conversion was performed across a range of temperatures including higher temperatures relevant to catalytic hot gas filtration (450 °C). Ca addition slightly decreases overall acetic acid ketonization reactivity yet stabilizes the catalyst at the higher temperatures necessary for catalytic hot gas filtration. From density functional theory calculations of the ketonization reaction mechanism, the C–C coupling and water formation steps are identified as two of the most energy-consuming steps on a CeO 2 surface with a proximal oxygen vacancy and the presence of a Ca dopant stabilizes the key intermediates. Calculations predict an optimal structure comprising three Ca ensembles to minimize the reaction free energies for C–C coupling and water formation steps. These findings provide a priori information to guide future experiments for ketonization catalyst design and development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

3D small-gain formula allowing strong focusing and harmonic lasing for a ring-based x-ray free electron laser oscillator

We present a detailed derivation of a formula for the small-gain calculation for an x-ray free electron laser oscillator (XFELO) based on a medium-energy (3–4 GeV) storage ring. We found harmonic lasing and strong focusing are essential for this beam energy range. Taking the small-signal low-gain formula developed by Kim and his colleagues, we modified it in such a way that the gain can be calculated without the “no focusing approximation,” and a strong focusing can be applied, as well as harmonic lasing. In this formula, the gain is represented as a product of two factors with one of them depending only on the harmonic number, undulator period, and gap. Using this factor, we show that it is favorable to use harmonic lasing to achieve hard x-ray FEL working in the small-signal low-gain regime with the medium-energy electron beam. Our formula also allows FEL optimization by varying the vertical gradient of the undulator, the vertical dispersion, and the horizontal and vertical focusing, independently. As an example, we applied this formula to study the feasibility of an XFELO option for the National Synchrotron Light Source II (NSLS-II) upgrade. Since a quite high peak current is required for the FEL, collective effects of beam dynamics in medium-energy synchrotrons significantly affect the electron beam parameters. We carried out a multiparameter optimization taking collective effects into account. Note, even though our example is for a ring-based XFELO at 3 to 4 GeV, the formula and, in particular, the approach developed here may be applied to other types of FELs. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Structural Basis of T4 Phage Lysis Control: DNA as the Signal for Lysis Inhibition

Optimal phage propagation depends on the regulation of the lysis of the infected host cell. In T4 phage infection, lysis occurs when the holin protein (T) forms lesions in the host membrane. However, the lethal function of T can be blocked by an antiholin (RI) during lysis inhibition (LIN). LIN sets if the infected cell undergoes superinfection, then the lysis is delayed until host/phage ratio becomes more favorable for the release of progeny. It has been thought that a signal derived from the superinfection is required to activate RI. Here we report structures that suggest a radically different model in which RI binds to T irrespective of superinfection, causing it to accumulate in a membrane as heterotetrameric 2RI–2T complex. Moreover, we show the complex binds non-specifically to DNA, suggesting that the gDNA from the superinfecting phage serves as the LIN signal and that stabilization of the complex by DNA binding is what defines LIN. Finally, we show that soluble domain of free RI crystallizes in a domain-swapped homotetramer, which likely works as a sink for RI molecules released from the RI–T complex to ensure efficient lysis. These results constitute the first structural basis and a new model not only for the historic LIN phenomenon but also for the temporal regulation of phage lysis in general.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Base-Free Catalytic Transfer Hydrogenation of Alkyl Formates and Organic Esters at Mild Temperature

The pincer-ligated ruthenium complex ( iPr PN H P)Ru(CO)H 2 ( iPr PN H P = ( i Pr 2 PC 2 H 4 ) 2 NH) is an active catalyst for the transfer hydrogenation of alkyl formates (HCO 2 R) and organic esters (RCO 2 R′) to the corresponding alcohols under base-free reaction conditions at mild temperatures. Specifically, a range of alkyl formate esters were reduced to MeOH and the corresponding alcohols in high yields using ( iPr PN H P)Ru(CO)H 2 as the catalyst and isopropanol ( i PrOH) as the hydrogen donor at 30 °C. The first step in the process is the metal-catalyzed transesterification of the alkyl formate with i PrOH to generate isopropyl formate, which is then reduced. The use of i PrOH as the hydrogen donor is crucial. ( iPr PN H P)Ru(CO)H 2 can also catalyze the transfer hydrogenation of a broad range of organic esters, including cyclic, acyclic, heteroatom-substituted, and long-chain bio-derived esters, to the corresponding alcohols in good yields using ethanol (EtOH) as the hydrogen donor at 55 °C. Computational studies were used to elucidate the proposed pathway for alkyl formate reduction and the underlying reasons why i PrOH is the most effective hydrogen donor for alkyl formate reduction, while EtOH is optimal for organic ester reduction. Overall, this work describes a highly active catalyst for alkyl formate and organic ester transfer hydrogenation and provides mechanistic insight into the factors responsible for the strong catalytic performance. Finally, these findings will be valuable for designing catalysts for both transfer hydrogenation and related reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hamiltonian variational ansatz without barren plateaus

Variational quantum algorithms, which combine highly expressive parameterized quantum circuits (PQCs) and optimization techniques in machine learning, are one of the most promising applications of a near-term quantum computer. Despite their huge potential, the utility of variational quantum algorithms beyond tens of qubits is still questioned. One of the central problems is the trainability of PQCs. The cost function landscape of a randomly initialized PQC is often too flat, asking for an exponential amount of quantum resources to find a solution. This problem, dubbed barren plateaus , has gained lots of attention recently, but a general solution is still not available. In this paper, we solve this problem for the Hamiltonian variational ansatz (HVA), which is widely studied for solving quantum many-body problems. After showing that a circuit described by a time-evolution operator generated by a local Hamiltonian does not have exponentially small gradients, we derive parameter conditions for which the HVA is well approximated by such an operator. Based on this result, we propose an initialization scheme for the variational quantum algorithms and a parameter-constrained ansatz free from barren plateaus.

Physics↗
DOE OSTI2022

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2021

Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery

Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.

42 ENGINEERING↗
DOE OSTI2024

Unifying thermochemistry concepts in computational heterogeneous catalysis

Thermophysical properties of adsorbates and gas-phase species define the free energy landscape of heterogeneously catalyzed processes and are pivotal for an atomistic understanding of the catalyst performance. These thermophysical properties, such as the free energy or the enthalpy, are typically derived from density functional theory (DFT) calculations. Enthalpies are species-interdependent properties that are only meaningful when referenced to other species. The widespread use of DFT has led to a proliferation of new energetic data in the literature and databases. However, there is a lack of consistency in how DFT data is referenced and how the associated enthalpies or free energies are stored and reported, leading to challenges in reproducing or utilizing the results of prior work. Additionally, DFT suffers from exchange–correlation errors that often require corrections to align the data with other global thermochemical networks, which are not always clearly documented or explained. In this review, we introduce a set of consistent terminology and definitions, review existing approaches, and unify the techniques using the framework of linear algebra. This set of terminology and tools facilitates the correction and alignment of energies between different data formats and sources, promoting the sharing and reuse of ab initio data. Standardization of thermochemistry concepts in computational heterogeneous catalysis reduces computational cost and enhances fundamental understanding of catalytic processes, which will accelerate the computational design of optimally performing catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A flexible linear diffusion acceleration to k-eigenvalue neutron transport with SN discontinuous finite element method

In this paper, we derive a flexible linear diffusion acceleration (LDA) for k-eigenvalue neutron transport discretized with discontinuous finite element method (DFEM) and discrete ordinates(SN). This LDA is based on our two pieces of previous works: the flexible non linear diffusion acceleration (NDA) for DFEM-SN and LDA for k-eigenvalue neutron transport using pre-conditioned Jacobian-free Newton-Krylov with self-adjoint angular flux (SAAF), continuous finite element method(CFEM), and SN. We point out the differences between LDA and NDA for DFEM-SN and the difference between DFEM-SN and SAAF-CFEM-SN for LDA. Numerical tests are presented to compare the convergence behaviour of NDA and LDA. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

The algal microbiome protects Desmodesmus intermedius from high light and temperature stress

The mutualistic impacts of bacterial communities on algal growth and biomass accumulation are well documented, but it is unknown how temperature and light stress influence these mutualistic interactions. Here, we generated a bacteria-free (axenic) culture of the green alga Desmodesmus intermedius C046 and compared its growth and yield in the laboratory to its native xenic counterpart - featuring a microbiome that has been maintained with its algal host for at least 5 years – under unstressed and high light, high temperature stress conditions. We then added exogenous microbiomes from high light marine environments to the axenic culture to quantify the contribution of these newly generated microbial consortia in improving D. intermedius growth, yield, and resilience to high light and heat. The native microbiome increased growth and biomass accumulation, under both unstressed and stressed conditions. Three of the five newly derived microbiomes had increased growth compared to the axenic and negligible, decreased, or increased growth impacts compared to the xenic culture. Stress conditions led to decreased algal exudation, larger algal cells when grown alone, but smaller algal cells with an associated microbiome. In conclusion, our results suggest that the algal microbiome plays a role in microalgal response to heat and light stress, and efforts for screening new algal strains for high biomass productivity under those stress conditions should include a strategy for microbiome optimization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Bias-Variance Trade-Off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs

Physics-Informed Neural Networks (PINNs) have triggered a paradigm shift in scientific computing, leveraging mesh-free properties and robust approximation capabilities. While proving effective for low-dimensional partial differential equations (PDEs), the computational cost of PINNs remains a hurdle in high-dimensional scenarios. This is particularly pronounced when computing high-order and high-dimensional derivatives in the physics-informed loss. Randomized Smoothing PINN (RS-PINN) introduces Gaussian noise for stochastic smoothing of the original neural net model, enabling the use of Monte Carlo methods for derivative approximation, which eliminates the need for costly automatic differentiation. Despite its computational efficiency, especially in the approximation of high-dimensional derivatives, RS-PINN introduces biases in both loss and gradients, negatively impacting convergence, especially when coupled with stochastic gradient descent (SGD) algorithms. We present a comprehensive analysis of biases in RS-PINN, attributing them to the nonlinearity of the Mean Squared Error (MSE) loss as well as the intrinsic nonlinearity of the PDE itself. We propose tailored bias correction techniques, delineating their application based on the order of PDE nonlinearity. The derivation of an unbiased RS-PINN allows for a detailed examination of its advantages and disadvantages compared to the biased version. Specifically, the biased version has a lower variance and runs faster than the unbiased version, but it is less accurate due to the bias. To optimize the bias-variance trade-off, we combine the two approaches in a hybrid method that balances the rapid convergence of the biased version with the high accuracy of the unbiased version. In addition to methodological contributions, we present an enhanced implementation of RS-PINN. Extensive experiments on diverse high-dimensional PDEs, including Fokker-Planck, Hamilton-Jacobi-Bellman (HJB), viscous Burgers’, Allen-Cahn, and Sine-Gordon equations, illustrate the bias-variance trade-off and highlight the effectiveness of the hybrid RS-PINN. Empirical guidelines are provided for selecting biased, unbiased, or hybrid versions, depending on the dimensionality and nonlinearity of the specific PDE problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Towards an Integrated Process for CO 2 Capture and Utilization: Cultivation of Scenedesmus acutus Using Gaseous CO 2 and NH 3

Integrating CO 2 scrubbing from flue gas with its utilization in algae cultivation represents a potential means of lowering the cost of CO 2 capture. Towards this goal, this study sought to assess the feasibility of using gaseous a CO 2 /NH 3 stream, derived from CO 2 capture using aqueous ammonia, as a C- and N-source for algae cultivation. Scenedesmus acutus was cultured in 800 mL photobioreactors using gaseous CO 2 /NH 3 in mole ratios varying from 7 to 18. Excellent growth of Scenedesmus acutus was observed, the average growth rate for CO 2 /NH 3 = 10 of 0.171 ± 0.015 g/L·day exceeding that obtained using 1% CO 2 /N 2 and urea as the N-source (0.099 ± 0.28 g/L·day). Under optimal growth conditions (CO 2 /NH 3 mole ratio of 10), CO 2 utilization ranged from 57% to 72%, while the NH 3 utilization was >90%. The CO 2 /NH 3 feed rate was also found to exert a significant effect on algae productivity, excessive feed rates leading to accumulation of NH 3 in the culture at concentrations that were toxic to the algae. Consequently, to avoid the toxic effects of high NH 3 concentrations (>2.0 mM), it proved necessary to balance the NH 3 supply with the algae growth rate so that excessive NH 3 accumulation was prevented. This indicates that for practical applications, a CO 2 /NH 3 feed control strategy would be required that takes into account the ammonium ion concentration in solution and the pH so as to avoid significant concentrations of free NH 3 . Furthermore, analysis of the harvested biomass revealed a high protein (≥ 47 wt%) and a low ash content (< 3.6 wt%), suggesting it would be well suited for use as animal feed or as a feedstock for the production of bioplastics.

03 NATURAL GAS↗