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Results for “dynamical process”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗
DOE OSTI2025

Imaging of dynamic processes in materials with a laser-wakefield accelerator

Betatron x rays generated from laser-wakefield accelerators are a promising source for imaging dynamic processes in materials. Here, we present proof-of-concept imaging of microstructural evolution in a hypermonotectic Al-Bi alloy, which consists of liquid Bi particles in a solid Al matrix. The images capture the elongation and fragmentation of Bi particles upon isothermal annealing. Because of the femtosecond time scale of the betatron source, the images are not subject to motion blur, whereas the accessibility of the source allows for studies of long-term processes such as annealing. The high-resolution data reveal that the evolution of Bi particles is mediated by an interplay of grain-boundary wetting and morphological instability, in stark contrast to an earlier proposal for (inverse) coarsening.

Alloys↗
DOE OSTI2021

Dynamic process intensification: Fundamentals and implementation to ternary distillation

Distillation remains a key technology for separating liquid mixtures. Its versatility comes with the disadvantage of high energy consumption. We previously used empirical arguments to introduce dynamic process intensification (DPI) as a strategy for improving the energy efficiency of binary distillation. In this article, we focus on ternary distillation; we begin by providing a rigorous basis for DPI, then formulate the problem of identifying the operating states for DPI as a nonlinear optimization problem. Via an extensive case study considering a hydrocarbon mixture, we demonstrate that reboiler energy use can be reduced by more than 2.3% relative to an equivalent column operating at steady state. Here, we prove that this result is due to the fact that DPI aims to satisfy product flow and quality constraints on average in time, affording broader opportunities for optimizing column economics than steady-state operation, where constraints are met strictly at all times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Markov Chain Monte Carlo Predictions of Neutron-rich Lanthanide Properties as a Probe of r -process Dynamics

Lanthanide element signatures are key to understanding many astrophysical observables, from merger kilonova light curves to stellar and solar abundances. To learn about the lanthanide element synthesis that enriched our solar system, we apply the statistical method of Markov Chain Monte Carlo to examine the nuclear masses capable of forming the r-process rare-earth abundance peak. We describe the physical constraints we implement with this statistical approach and demonstrate the use of the parallel chains method to explore the multidimensional parameter space. We apply our procedure to three moderately neutron-rich astrophysical outflows with distinct types of r-process dynamics. We show that the mass solutions found are dependent on outflow conditions and are related to the r-process path. We describe in detail the mechanism behind peak formation in each case. We then compare our mass predictions for neutron-rich neodymium and samarium isotopes to the latest experimental data from the CPT at CARIBU. Here, we find our mass predictions given outflows that undergo an extended (n,γ)⇌(γ,n) equilibrium to be those most compatible with both observational solar abundances and neutron-rich mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗
DOE OSTI2020

Optimizing Sub-Sampled STEM Imaging for Beam Sensitive Materials and Dynamic Processes

The goal of this research is to quantify how sub-sampling and inpainting (broadly classified as methods in Artificial Intelligence) can be used to obtain the highest resolution images under any experimental conditions, and to use this to reproducibly control dynamic in-situ processes in gases and liquids on the nanoscale. As atomic diffusion under non-extreme conditions is typically in the sub-ms time domain, the ability to use this sub-sampling approach to reduce the effect of the electron beam and to speed-up the imaging process represents the optimum combination of spatial and temporal resolution achievable in a conventional microscope. This LDRD funding demonstrated the feasibility of imaging dynamics in complex energy systems using this methodology by establishing the optimum experimental sampling conditions (optimizing the number of pixels, speed, contrast and resolution) for each experiment. For in-situ liquid cell experiments this analysis shows that simply by distributing the same dose and dose rate maximally in space and time, the kinetics for radiolysis products can be modified significantly. The final stage of this work, i.e. the experimental demonstration of its use for nucleation and growth, was severely curtailed by issues with COVID19. However, all the experiments are designed and currently underway, with the goal to complete the final demonstration and publication as soon as safety concerns for laboratory access are met.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum Simulation of Molecular Dynamics Processes─A Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware

Here, we explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this issue, we designed a shallower quantum circuit for preparing a Gaussian-like initial wave packet, which improves the performance of real hardware. Next, quantum circuits are implemented to apply the kinetic and potential energy operators for the evolution of a wave function over time. The results of our modeling on classical emulators of quantum hardware agree perfectly with the results obtained using the traditional (classical) methods. This serves as a benchmark and demonstrates that the quantum algorithms and Qiskit codes we developed are accurate. However, the results obtained on the actual quantum hardware available today, such as IBM’s superconducting qubits and IonQ’s trapped ions, indicate large discrepancies due to hardware limitations. This work highlights both the potential and challenges of using quantum computers to solve fundamental quantum molecular dynamics problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Time-resolved electrical potential pump – X-ray photoelectron spectroscopy probe developments for investigating dynamic processes occurring at electrochemical interfaces

Electrode–electrolyte interfaces are of critical importance in several fields, including renewable energy, corrosion, and environmental chemistry. However, investigating these interfaces under operational conditions poses considerable challenges due to the limitations of the instrumentation employed. While recent advancements in in situ and operando techniques have enhanced our comprehension of the steady-state properties of solid-liquid interfaces, the dynamic behaviors of these systems remain inadequately explored. This study introduces a time-resolved X-ray photoelectron spectroscopy (XPS) technique designed to capture transient reaction intermediates and charging dynamics at electrified interfaces. The presented proof-of-principle study demonstrates that electrochemical processes, represented by an equivalent electrical circuit (EEC) model, can be probed and understood using square wave voltage pulses of a potentiostat synchronized to the modified data acquisition of an XPS setup. This method offers a valuable alternative to traditional pump–probe techniques, facilitating the investigation of a broader range of electrochemical systems. A dedicated software package for analyzing time- and energy-resolved XPS with a focus on extracting parameters of the EEC is geared towards benchmarking different EECs in future real-world electrochemical experiments.

Electrochemistry↗
DOE OSTI2026

A Kinetic Model-Driven Techno-Economic Analysis of Plastic Pyrolysis: Linking Process Dynamics to Economic Viability

This study employs a kinetic model integrated into Aspen Plus to predict pyrolysis product distribution under various conditions. A techno-economic assessment calculated the minimum selling price (MSP) of pyrolysis oil under different operating conditions for the baseline capacity of 100 kta, and across eight processing capacities ranging from 30 to 150 kta. The lowest MSP under the baseline capacity is estimated at $\$$420/ton, which is 33% lower than the 2023 average US crude oil price ($\$$74.6/bbl, equivalent to $\$$634/ton based on the density of pyrolysis oil). Under Monte Carlo simulation, accounting for variability in key economic and technical parameters, the mean MSP is estimated at $\$$1137/ton. The economic viability depends on feedstock price remaining below $\$$320/ton, defining the break-even feedstock price threshold. Sensitivity analysis further identifies capital investment and transportation cost as key economic drivers. Capacities beyond 90 kta show limited economies of scale benefits. Reducing product storage time cuts capital costs by 7% but raises operational risk. Uncertainty analysis suggests the economic feasibility of pyrolysis oil is unlikely to compete with crude oil without policy incentives.

petrochemicals↗
DOE OSTI2023

High-speed X-ray study of process dynamics caused by surface features during continuous-wave laser polishing

During high-speed X-ray imaging of laser surface polishing experiments of specimens of 316L stainless steel at Argonne National Lab's Advanced Photon Source, it was discovered that the induced keyhole changes shape and dimensions while crossing an engineered surface feature without altering process parameters. It was observed that the post-surface feature keyhole was deeper than that of the pre surface feature keyhole. Here, this work reports on the first in-situ observation of the effect of localized surface geometry on underlying melt pool behavior. This has implications for defect formation mechanisms during laser melting processes that rely on melt pool geometry.

42 ENGINEERING↗
DOE OSTI2021

Dynamic processes in transient phases during self-assembly of organic semiconductor thin films

Understanding and manipulating crystallization processes has been an important challenge for solution-processed organic thin films, both for fundamental studies and for fabricating thin films with near-intrinsic charge transport properties. We report an in situ X-ray scattering study of the crystallization of 2-decyl-7-phenyl-[1]benzothieno[3,2-b][1]benzothiophene (Ph-BTBT-C 10 ) during its deposition from solution. At temperatures modestly below the smectic-E/crystalline phase boundary, the crystallization goes through a transient liquid crystal state before reaching the final stable crystalline phase. Significant dynamics occur in the first few seconds of the transition, which are observed through fluctuations in the X-ray scattering intensity, and are correlated with the time interval that the transient thin film coexists with the evaporating solvent. The transition to the stable crystalline phase takes minutes or even hours under these conditions, which may be a result of the asymmetry of the molecule. Transient phases are of potential interest for applications, since they can act as a route to self-assembly of organic thin films. However, our observations show that the long-lived monolayer-stacked intermediate state does not act as a template for the bilayer-stacked crystalline phase. Rather, the grain structure is replaced through nucleation, where the nucleation free-energy barrier is related to a potential barrier that prevents molecules to flip their long axis by 180°.

36 MATERIALS SCIENCE↗
DOE OSTI2023

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The evolution dynamical processes of Ural blocking through the lens of local finite-amplitude wave activity budget analysis

Understanding the formation and evolution mechanisms of Ural blocking (UB) is of great importance for the prediction of UB and relevant extremes in east Asia. Using the 6-hourly ERA-Interim reanalysis data, this study quantifies the conservative and nonconservative processes in the lifecycle of UB through the lens of the hybrid Eulerian-Lagrangian local finite-amplitude wave activity (LWA) diagnostics. It is found that (i) as a wave activity source, eddy heat flux works to not only initiate the UB, but also prevent the wave activity of the blocking from dispersing downstream---the key characteristic of blocking; (ii) both the wave propagation and wave advection mechanisms are indispensable for the evolution of UB, playing a tug-of-war on the downstream development of wave activity; (iii) Throughout the lifespan of UB, diabatic heating provides the most important damping mechanism for the wave activity both upstream and downstream; and (IV) irreversible PV mixing appears to compensate the eddy PV flux during the wave breaking stage of blocking.

Blocking, wave activity, eddy-mean flow interactio↗
DOE OSTI2020

Composition and Dynamical Processes of Ions in Giant Magnetospheres: The Importance of In Situ Measurements for Advancing the Current Knowledge [Slides]

In this white paper, we emphasize the importance of in situ ion composition measurements provided by plasma mass spectrometers in planetary magnetospheres (Uranus and Neptune) aimed for future planetary missions. We present our current understanding on magnetospheres of Uranus and Neptune that are largely based on Plasma Science Investigation (PLS, faraday cups) and Low Energy Charged Particle (LECP) instrument on Voyager 2 and what measurements need to be made to improve it. We emphasize that the future missions equipped with plasma mass spectrometers must visit these magnetospheres again to advance our current knowledge. Finally, this white paper summarizes key science questions that needs to be addressed which all of them requires a direct ion composition measurements from a plasma spectrometer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles

Dynamic wireless charging of electric vehicles (EV) is an emerging charging technology to enable non-contact wireless charging while the vehicle is moving. Compared to stationary wireless charging, in-motion wireless charging involves dynamic processes in which an EV is passing over the charging pads (transmitters). This in motion process makes the dynamic electromagnetic (EM) environment more complicated, and EM safety needs to be ensured under all circumstances. This is due to the fact that the entire vehicle body may be exposed to magnetic fields while the vehicle moves over the energized transmitter. This paper investigates several typical charging scenarios when EVs approach, pass over, and move away from the charging pads. Quasi-dynamic models, which are preliminarily verified by coils’ inductance measurements, are developed to analyze the dynamic process. Based on the quasi-dynamic analysis, shielding solutions are also studied to ensure EM safety for the dynamic wireless charging processes.

24 POWER TRANSMISSION AND DISTRIBUTION↗