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DOE OSTI2023

Computational diagnostics for flame acceleration and transition to detonation in a hydrogen/air mixture

A new computational diagnostic method for pressure-induced compressibility is proposed by projecting its local contribution to the chemical explosive mode (CEM) in the chemical explosive mode analysis (CEMA) framework. The new method is validated for the study of detonation development during the deflagration-to-detonation transition (DDT) process. The flame characteristics are identified through the quantification of individual CEM contributions of chemical reaction, diffusion, and pressure-induced compressibility. Numerical simulations are performed to investigate the DDT processes in a stoichiometric hydrogen-air mixture. A Godunov algorithm, fifth-order in space, and third-order in time are used to solve the fully compressible Navier-Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model (CDM) described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The new diagnostic method is first applied to onedimensional (1D) canonical flame configurations followed by two-dimensional (2D) simulations of DDT in an obstructed channel where different detonation initiation scenarios are examined using the new CEMA projection formulation. Detailed examinations of the idealized configuration of detonation initiation through shock focusing mechanism at a flame front are also studied using the new formulation. A comparison of the currently proposed CEMA projection and the original formulation by the authors suggests that including the pressure-induced compressibility is essential for the use of CEMA in DDT process. The results also show that the new formulation of CEMA projection can successively capture the detonation initiation through either a gradient mechanism or a direct initiation mechanism, and therefore can be used as an effective local analytical tool for the computational diagnostics of detonation initiation in a DDT process. It was found that detonation development is characterized by a strong contribution of chemistry role to the CEM which is pivotal to the initiation of detonation. The role of compressibility is found enhanced at the edge of the detonation front where diffusion was found to have minimal effects on detonation development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Multiphase phase-field approach for solid–solid phase transformations via propagating interfacial phase in HMX

In this study, a thermodynamically consistent multiphase phase-field theory has been formulated to describe temperature-induced solid–solid phase transformations via an interfacial phase. This theory satisfies all thermodynamic equilibrium and stability conditions. It allows us to formulate the analytical solutions of the interface profile, energy, width, and velocity for each of the propagating solid–melt and solid–solid interfaces. The formation of the intermediate melt during solid–solid phase transformation has been studied hundreds of degrees below melting temperature in the HMX energetic crystal. The effect of the penalizing term in the phase-field model and two nanoscale material parameters on the appearance and degree of disordering of intermediate melt has been analyzed for the non-equilibrium interface. The developed approach is applicable to phase transitions in geological, pharmaceutical, ferroelectric, colloidal, and superhard materials where phase transformations occur via the intermediate phase.

Roy, Arunabha M. (ORCID:000000034790726X)↗

DOE OSTI2021

Involute Working Group – FSI Analysis of Fuel Plates Using Finite Volume and Finite Element Methods

The three involute plate research reactors RHF, HFIR, and FRM II have expressed an interest in using computational software to carry their steady-state safety analysis. Since these tools represent a significant departure from the methods used currently (one-dimensional), the acceptability of the new approach by regulators requires thorough verification and validation of these tools. Therefore, Argonne National Laboratory and the three involute-plate reactors formed an informal group called the Involute Working Group aiming at qualifying computational tools to perform steady-state safety analysis. The present report focuses on a comparison of finite volume and finite element methods to model solids in fluid-structure interaction problems with the goal to estimate the coolant flow-induced fuel plate deflections obtained with the two methods. The finite volume method will be obsoleted in STARCCM+ by the end of 2021, nevertheless, this evaluation is important because the method was used by ANL researchers to model the response of the fuel plates, despite its drawbacks, which are discussed in the report. It was essential to check how those estimates compare to the results obtained with the finite element method that is considered superior for structural analysis. Various geometries, i.e., flat, cylindrical and circle-involute fuel plates, as well as coolant flow speed, were considered. The comparison shows that, independently of the plate geometry, the finite volume method significantly underestimates the deflection as compared to finite element method for coarser meshes. When the discretization is developed as a result of a mesh sensitivity study using finite element method, the result obtained using finite volume method can be a few times smaller than the corresponding finite element method solution. A code-to-code comparison , between STAR-CCM+ and LS-DYNA was included in the analysis. Within the LS-DYNA models, two types of finite element formulations were used: solid and shell finite elements. Mesh sensitivity study showed that both approaches converge to a similar value that was obtained with STAR-CCM+ finite element solver. The evaluation of the computational solvers was extended by adding two benchmark cases from the STAR-CCM+ Verification Suite and presented in the Appendix A. The selected cases are: (1) bending of a cantilever beam under external load, and (2) cylindrical shell deformation analysis, known in the literature as ‘Scordelis-Lo roof’. The problems were solved with finite volume, and finite element methods, and the results confirmed the previously discussed findings. The analysis shows that the finite element solver is superior to the finite volume solver in terms of representation of model geometry and estimating the structural behavior of fuel plates. Depending on the ratio of the load to the flexibility of the plate, the finite volume solver can greatly under- or overestimate the structural response if a very carefully selected mesh is not used.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Nozzle-Free Printing of CNT Electronics Using Laser-Generated Focused Ultrasound

Printed electronics have made remarkable progress in recent years and inkjet printing (IJP) has emerged as one of the leading methods for fabricating printed electronic devices. However, challenges such as nozzle clogging, and strict ink formulation constraints have limited their widespread use. To address this issue, a novel nozzle-free printing technology is explored, which is enabled by laser-generated focused ultrasound, as a potential alternative printing modality called Shock-wave Jet Printing (SJP). Specifically, the performance of SJP-printed and IJP-printed bottom-gated carbon nanotube (CNT) thin film transistors (TFTs) is compared. While IJP required ten print passes to achieve fully functional devices with channel dimensions ranging from tens to hundreds of micrometers, SJP achieved comparable performance with just a single pass. For optimized devices, SJP demonstrated six times higher maximum mobility than IJP-printed devices. Furthermore, the advantages of nozzle-free printing are evident, as SJP successfully printed stored and unsonicated inks, delivering moderate electrical performance, whereas IJP suffered from nozzle clogging due to CNT agglomeration. Moreover, SJP can print significantly longer CNTs, spanning the entire range of tube lengths of commercially available CNT ink. The findings from this study contribute to the advancement of nanomaterial printing, ink formulation, and the development of cost-effective printable electronics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

In this paper, we present mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Quantum simulations of excited states with active-space downfolded Hamiltonians

Many-body techniques based on the double unitary coupled cluster ansatz (DUCC) can be used to downfold electronic Hamiltonians into low-dimensional active spaces. It can be shown that the resulting dimensionality reduced Hamiltonians are amenable for quantum computing. Recent studies performed for several benchmark systems using quantum phase estimation (QPE) algorithms demonstrated that these formulations can recover a significant portion of ground-state dynamical correlation effects that stem from the electron excitations outside of the active space. These results have also been confirmed in studies of ground-state potential energy surfaces using quantum simulators. In this letter, we study the effectiveness of the DUCC formalism in describing excited states. We also emphasize the role of the QPE formalism and its stochastic nature in discovering/identifying excited states or excited-state processes in situations when the knowledge about the true configurational structure of a sought after excited state is limited or postulated (due to the specific physics driving excited-state processes of interest). In this context, we can view the QPE algorithm as an engine for verifying various hypotheses for excited-state processes and providing statistically meaningful results that correspond to the electronic state(s) with the largest overlap with a postulated configurational structure. We illustrate these ideas on examples of strongly cor- related molecular systems, characterized by small energy gaps and high density of quasi-degenerate states around the Fermi level.

quantum chemistry, quantum computing, computationa↗

DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Light-Front Field Theory on Current Quantum Computers

We present a quantum algorithm for simulation of quantum field theory in the light-front formulation and demonstrate how existing quantum devices can be used to study the structure of bound states in relativistic nuclear physics. Specifically, we apply the Variational Quantum Eigensolver algorithm to find the ground state of the light-front Hamiltonian obtained within the Basis Light-Front Quantization (BLFQ) framework. The BLFQ formulation of quantum field theory allows one to readily import techniques developed for digital quantum simulation of quantum chemistry. This provides a method that can be scaled up to simulation of full, relativistic quantum field theories in the quantum advantage regime. As an illustration, we calculate the mass, mass radius, decay constant, electromagnetic form factor, and charge radius of the pion on the IBM Vigo chip. This is the first time that the light-front approach to quantum field theory has been used to enable simulation of a real physical system on a quantum computer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Progressive Hedging Decomposition for Solutions of Large-Scale Process Family Design Problems

Rapid, wide-scale deployment of green process systems, such as carbon capture or water desalination systems, is essential for combatting climate change. Methods relying on traditional design or modularity fail to capture the benefits of both economies of numbers and economies of scale. We have proposed process family design, which designs a family of processes simultaneously exploiting opportunities for common elements. In previous work, we explored different optimization formulations to solve this problem. In this work, we develop a decomposition approach to tackle larger problems efficiently. We solve a water desalination case study, which is too large to solve within a reasonable timeframe with the discretization formulation. We exploit the block angular structure of the discretization problem to decompose and solve using Progressive Hedging (PH). We use the open-source Python package mpi-sppy to execute PH which allows us to leverage parallelization and a HPC cluster to further improve solution time.

Stinchfield, Georgia↗

DOE OSTI2024

Optimizing dietary rumen-degradable starch to rumen-degradable protein ratio improves lactation performance and nitrogen utilization efficiency in mid-lactating Holstein dairy cows

The dietary rumen-degradable starch (RDS) to rumen-degradable protein (RDP) ratio, denoted as the RDS-to-RDP ratio (SPR), has been proven to enhance in vitro rumen fermentation. However, the effects of dietary SPR in vivo remain largely unexplored. This study was conducted to investigate the effect of dietary SPR on lactation performance, nutrient digestibility, rumen fermentation patterns, blood indicators, and nitrogen (N) partitioning in mid-lactating Holstein cows. Seventy-two Holstein dairy cows were randomly assigned to three groups (24 head/group), balanced for (mean ± standard deviation) days in milk (116 ± 21.5), parity (2.1 ± 0.8), milk production (42 ± 2.1 kg/d), and body weight (705 ± 52.5 kg). The cows were fed diets with low (2.1, control), medium (2.3), or high (2.5) SPR, formulated to be isoenergetic, isonitrogenous, and iso-starch. The study consisted of a one-week adaptation phase followed by an eight-week experimental period. The results indicated that the high SPR group had a lower dry matter intake compared to the other groups ( p < 0.05). A quadratic increase in milk yield and feed efficiency was observed with increasing dietary SPR ( p < 0.05), peaking in the medium SPR group. The medium SPR group exhibited a lower milk somatic cell count and a higher blood total antioxidant capacity compared to other groups ( p < 0.05). With increasing dietary SPR, there was a quadratic improvement ( p < 0.05) in the total tract apparent digestibility of crude protein, ether extract, starch, neutral detergent fiber, and acid detergent fiber. Although no treatment effect was observed in rumen pH, the rumen total volatile fatty acids concentration and microbial crude protein synthesis increased quadratically ( p < 0.05) as dietary SPR increased. The molar proportion of propionate linearly increased ( p = 0.01), while branched-chain volatile fatty acids linearly decreased ( p = 0.01) with increasing dietary SPR. The low SPR group (control) exhibited higher concentration of milk urea N, rumen ammonia N, and blood urea N than other groups ( p < 0.05). Despite a linear decrease ( p < 0.05) in the proportion of urinary N to N intake, increasing dietary SPR led to a quadratic increase ( p = 0.01) in N utilization efficiency and a quadratic decrease ( p < 0.05) in the proportion of fecal N to N intake. In conclusion, optimizing dietary SPR has the potential to enhance lactation performance and N utilization efficiency. Based on our findings, a medium dietary SPR (with SPR = 2.3) is recommended for mid-lactating Holstein dairy cows. Nevertheless, further research on rumen microbial composition and metabolites is warranted to elucidate the underlying mechanisms of the observed effects.

Chen, Panliang↗

DOE OSTI2024

Interacting chiral form field theories and $$ T\overline{T} $$-like flows in six and higher dimensions

Abstract In this paper we initiate the study of six-dimensional non-linear chiral two-form gauge theories as deformations of free chiral two-form gauge theories driven by stress-tensor$$ T\overline{T} $$ T T ¯ -like flows. To lay the background for this study, we elaborate on the relationship between different Lagrangian formulations of duality-invariantp-form theories and corresponding$$ T\overline{T} $$ T T ¯ -like flows in various dimensions. To this end we propose a new formulation which (i) is a generalization of the four-dimensional construction by Ivanov, Nurmagambetov and Zupnik (INZ) and (ii) turns into the PST formulation upon integrating out an auxiliary self-dual field. We elucidate space-time covariant properties of the PST formulation by clarifying and making use of its relation to the INZ-type formulation and to a so-called “clone” construction.

Physics↗

DOE OSTI2022

Probing the role of solids loading and mix procedure on the properties of acoustically mixed materials for additive manufacturing

We report resonant acoustic mixing has been of particular interest for use in additive manufacturing since viscous, solids-loaded materials can be difficult to mix and inhomogeneity has adverse effects on print quality. In this study, we detail a method to iterate through different formulations and mix procedures and assess mixture quality. The approach utilizes a constant pressure-driven flow test to collect statistics on flow rate through a standard geometry. This test is first applied to well mixed formulations containing particulate solids and find that the results are sensitive to viscosity produced by solids content. We then consider the formulations at various stages of mixing and find that the spread in the volume measurements is indicative of the mixing quality; poorly mixed material yields measurements with wide distributions. We believe this testing approach can be useful when screening new formulations, developing mixing processes, or for quality control.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Failure Mode Identification of Insulin Drug Products – Impact of Relevant Stress Conditions on the Quality of the Drug

Fast-acting insulin drug products (DPs) are carried and administered by diabetic patients to maintain their blood glucose level throughout the day, exposing the DPs to stress conditions. Apidra, Novolog, and Humalog insulin DPs were tested under various stress conditions. Dynamic light scattering (DLS), and size exclusion chromatography (SEC) were used to monitor the stability and aggregation. Thermal stress alone did not influence the stability. However, 24 hr exposure to vigorous mechanical stress shifted the DLS size peaks of Novolog and Humalog from 5 ± 1 nm to > 50.9 ± 25.6 nm, and the SEC native protein peak areas decreased 52% for Novolog and 18.4% for Humalog. Combined stress accelerated protein aggregation more drastically. Novolog and Humalog size shifted (>75 nm) after 3 hr and the peak area decreased > 97.9% after 6 hr exposure, indicating that high temperature accelerated the aggregation triggered by agitation. Soluble aggregates were captured by DLS early on compared to SEC. Apidra was comparably stable indicating DP formulation plays a critical role in stability. Here this study provides a greater understanding of potential failure modes patients and care givers may encounter while handling insulin DPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Using Ionic Liquid Additive to Enhance Lubricating Performance for Low-Viscosity Engine Oil

Energy efficient lubricants are essential for sustainable transportation, and the trend is to develop and implement lower viscosity lubricants with more effective additives. Ionic liquids (ILs) have been reported as candidate additives with superior friction and wear reducing capabilities. Unlike most literature relying on bench-scale testing of simple oil–IL blends, this study produced low-viscosity (SAE 0W-12) fully formulated engine oils using a phosphonium-organophosphate IL as an antiwear additive and evaluated them in both bench-scale tribological testing and full-scale fired engine dynamometer testing. The experimental formulation containing a combination of ZDDP and IL outperformed the formulations using either ZDDP or IL alone, as well as a commercial SAE 0W-20 engine oil in terms of mitigating boundary friction, wear, and contact fatigue-induced micropitting. Furthermore, racing engine dynamometer tests demonstrated 3–4 °C lower oil temperature, 4–5 ft-lbs higher horsepower output, and up to 9.9% better fuel economy for the IL-containing SAE 0W-12 experimental oil compared with selected commercial SAE 5W-30 and 0W-20 engine oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks

Tabulated chemistry models are widely used to simulate large-scale turbulent fires in applications including energy generation and fire safety. Tabulation via piecewise Cartesian interpolation suffers from the curse-of-dimensionality, leading to a prohibitive exponential growth in parameters and memory usage as more dimensions are considered. Artificial neural networks (ANNs) have attracted attention for constructing surrogates for chemistry models due to their ability to perform high-dimensional approximation. However, due to well-known pathologies regarding the realization of suboptimal local minima during training, in practice they do not converge and provide unreliable accuracy. Partition of unity networks (POUnets) are a recently introduced family of ANNs which preserve notions of convergence while performing high-dimensional approximation, discovering a mesh-free partition of space which may be used to perform optimal polynomial approximation. In this work, we assess their performance with respect to accuracy and model complexity in reconstructing unstructured flamelet data representative of nonadiabatic pool fire models. Our results show that POUnets can provide the desirable accuracy of classical spline-based interpolants with the low memory footprint of traditional ANNs while converging faster to significantly lower errors than ANNs. For example, we observe POUnets obtaining target accuracies in two dimensions with 40 to 50 times less memory and roughly double the compression in three dimensions. We also address the practical matter of efficiently training accurate POUnets by studying convergence over key hyperparameters, the impact of partition/basis formulation, and the sensitivity to initialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

From closed shells to open shells: Coupled-cluster calculations of atomic nuclei

Coupled-cluster theory is a powerful tool for first-principles calculations of atomic nuclei, enabling accurate predictions of nuclear observables across the Segrè chart. While coupled-cluster computations are especially efficient at shell closures, extensions have been developed to tackle open-shell nuclei, by exploiting the equation-of-motion method or by expanding the coupled-cluster wave function on top of a symmetry-breaking (either deformed or superfluid) reference state. In this study, we provide a comprehensive comparison of these different formulations applied to the calcium and nickel isotopes using nuclear two-and three-body interactions from chiral effective field theory. Here, based on ground-state energies, two-neutron separation energies, and two-neutron shell gaps, different coupled-cluster computations—based on symmetry-broken reference states and equationof-motion techniques— offer consistent descriptions of bulk properties across medium-mass isotopic chains.

Marino, Francesco [Johannes Gutenberg-Universität ↗

DOE OSTI2023

Model Predictive Voltage Control of Large-Scale PV or Hybrid PV-BESS Plants

Increased penetration level of inverter-based resources (IBRs) and renewable energy in the power grid has called for more requirements from the control of IBRs. In this paper, the voltage-reactive power control of a photovoltaic (PV) power plant or hybrid PV-battery energy storage system (BESS) plant connected to a bulk power grid, whilst meeting the grid requirements, is studied. In this paper, a continuous-set model predictive control (MPC) formulation is proposed for voltage-reactive power control. For the same, an aggregated dynamic PV plant model is developed based on the recursive system equivalencing method. The formulation is then implemented in PSCAD simulation on a 125 MW PV plant or hybrid PV-BESS plant. The MPC implementation achieves 10.13% voltage improvement based on PSCAD simulation results in a balanced fault case study. Simulation results further demonstrate that MPC provides improved voltage support over the conventional proportional-integral (PI) controller post-fault occurrence.

Abu rub, Omar↗