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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Dynamic Process Intensification of Binary Distillation via Periodic Operation

This paper applies the concept of dynamic intensification (defined as changes to the dynamics, operation strategy, and/or control of a process that lead to a substantially more efficient processing path) to binary distillation columns. The resulting strategy consists of manufacturing a target product as a blend of two auxiliary products, both having lower energy demands than a reference value, which corresponds to producing the target product(s) in a column operating at steady state. Here, a discussion of the appropriate control structures and switching strategies between the two auxiliary products is provided. An extensive case study concerning the separation of a methanol–1-propanol mixture was carried out, demonstrating that energy savings in the order of 1.4% are possible with no disruption in product quality or production rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

An efficient MILP framework for integrating nonlinear process dynamics and control in optimal production scheduling calculations

The emphasis currently placed on enterprise-wide decision making and optimization has led to an increased need for methods of integrating nonlinear process dynamics and control information in scheduling calculations. The inevitable high dimensionality and nonlinearity of first-principles dynamic process models makes incorporating them in scheduling calculations challenging. In this work, we describe a general framework for deriving data-driven surrogate models of the closed-loop process dynamics. Focusing on Hammerstein–Wiener and finite step response (FSR) model forms, we show that these models can be (exactly) linearized and embedded in production scheduling calculations. The resulting scheduling problems are mixed-integer linear programs with a special structure, which we exploit in a novel and efficient solution strategy. A polymerization reactor case study is utilized to demonstrate the merits of this method. Finally, our framework compares favorably to existing approaches that embed dynamics in scheduling calculations, showing considerable reductions in computational effort.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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 OSTI2018

Transition state redox during dynamical processes in semiconductors and insulators

Activation barriers associated with ion diffusion and chemical reactions are vital to understand and predict a wide range of phenomena, such as material growth, ion transport, and catalysis. In the calculation of activation barriers for non-redox processes in semiconductors and insulators, it has been widely assumed that the charge state remains fixed to that of the initial electronic ground state throughout a dynamical process. In this work, we demonstrate that this assumption is generally inaccurate and that a rate-limiting transition state can have a different charge state from the initial ground state. This phenomenon can significantly lower the activation barrier of a dynamical process that depends strongly on charge state, such as carbon vacancy diffusion in 4H-SiC. With inclusion of such transition state redox, the activation barrier varies continuously with Fermi level, in contrast to the step-line feature predicted by the traditional fixed-charge assumption. In this study, a straightforward approach to include the transition state redox effect is provided, the typical situations where the effect plays a significant role are identified, and the relevant electron dynamics are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Dynamic Processes in Nanostructured Crystals Under Ion Irradiation

The paper presents detailed investigations of dynamic processes occurring in nanostructured Si(Fe) material under the radiation exposure, namely: heating, thermoelastic stress generation, elastic disturbances of the surrounding medium similar to weak shock waves, and dislocation generation. The performance calculations are proposed for elastic properties of the nanostructured material with a glance to size effects in nanoparticles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Computational Investigation of Melt Pool Process Dynamics and Pore Formation in Laser Powder Bed Fusion

In the laser powder bed fusion additive manufacturing process, the presence of porosity may result in cracks and significantly affects the part performance. A comprehensive understanding of the melt pool process dynamics and porosity evolution can help to improve build quality. In this study, a novel multi-physics computational fluid dynamics (CFD) model has been applied to investigate the fluid dynamics in melt pools and resultant pore defects. To accurately capture the melting and solidification process, major process physics, such as the surface tension, evaporation as well as laser multi-reflection, have been considered in the model. A discrete element method is utilized to model the generation of powder spreading upon build plate by additional numerical simulations. Multiple single track experiments have been performed to obtain the melt pool shape and cross-sectional dimension information. The predicted melt pool dimensions were found to have a reasonable agreement with experimental measurements, e.g., the errors are in the range of 1.3 to 10.6% for melt pool width, while they are between 1.4 and 15.9% for melt depth. Pores are captured by both CFD simulation and x-ray computed tomography measurement for the case with a laser power of 350 W and laser speed of 100 mm/s. The formation of keyholes maybe related to the melt pool front wall angle, and it is found that the front wall angle increases with the increase in laser line energy density. In addition, a larger laser power or smaller scanning speed can help to generate keyhole-induced pores; they also contribute to produce larger sized pores.

36 MATERIALS SCIENCE↗
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 OSTI2019

Temperature dependence of nanoscale dynamic processes measured in living millipedes by high resolution inelastic and elastic neutron scattering

We have used high energy-resolution neutron scattering to probe nanoscale dynamic processes in living millipedes (Narceus americanus). We have measured the temperature dependence of the intensity of scattered neutrons that do not exchange energy with the living samples on the 1.5 ns time scale, thereby excluding the signal from the highly mobile intra- and extra-cellular bulk-like aqueous constituents in the sample. This measured “elastic” scattering intensity reflects a non-monotonic temperature dependence, with a noticeable systematic decrease detected between 295 and 303 K on warming up from 283 to 310 K. This decrease demonstrates an excellent inverse correlation with the non-monotonic, as a function of temperature, increase in the slow diffusivity previously observed in planarian flatworms and housefly larvae. This correlation indicates the existence of a biological mechanism, possibly common between different classes (Insects and Myriapods) and even phyla (Arthropods and Platyhelminthes), that dampens the slow nanoscopic dynamics in ectothermic organisms in response to the temperature of the environment exceeding the physiologically optimal range.

60 APPLIED LIFE SCIENCES↗
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 OSTI2018

Dynamic process intensification of binary distillation based on output multiplicity

Process intensification focuses largely on process and equipment design . Much less emphasis has been placed on operational changes to achieve cost savings and increased efficiency. Here, this article introduces the concept of dynamic intensification, defined as changes to the dynamics, operating strategy and/or control of a process that lead to a substantially more efficient processing path. This idea is illustrated in the context of binary distillation. Output multiplicity properties are exploited to establish a new periodic operating mode based on switching between two auxiliary products, which, on a time–average basis, is more energy efficient than steady–state operation. An extensive case study is presented concerning the distillation of a propanol–acetic acid mixture, confirming the theoretical developments. In contrast to previous research (e.g., on cyclic distillation), the present concept has significant advantages as it relies on existing hardware and exploiting system nonlinearity, rather than using specialized equipment operated in a discontinuous fashion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 OSTI2019

Dynamic Processes of CO 2 Storage in the Field: 1. Multiscale and Multipath Channeling of CO 2 Flow in the Hierarchical Fluvial Reservoir at Cranfield, Mississippi

A consistent picture of dynamic channeling, invasion, spreading, and breakthrough (CISB) of supercritical CO 2 in the hierarchical fluvial reservoir at Cranfield, Mississippi is presented after 10 years of integration and analysis of complementary field monitoring and characterization data. The dynamic CISB with small-scale CO 2 -flow channels in the F1-F2-F3 cross section (F1, F2, and F3 are one injection and two monitoring wells) was imaged by daily electrical resistance tomography (ERT) and time-lapse crosswell seismic surveys. One, three, and four CO 2 flow channels logged at F1, F2, and F3, respectively, were dynamically connected with strong temporal variations in CO 2 saturation during 221 days of drainage with injection rate doubling twice and 81 days of imbibition. Three intermediate-scale CO 2 flow channels (with highest CO 2 saturation) normal to the cross section were ERT-imaged during late-time drainage. A large-scale, sinuous fluvial CO 2 flow channel was imaged by repeat surface seismic survey at the end of the imbibition. The fluvial sandstone channel sinuously bypasses the F1-F2-F3 cross section in a point bar, but the channel is connected to the cross section through an intermediate-scale sandstone channel, forming a complicated flow channel network. The multiscale flow channel network (in the fluvial channel-point bar system) revealed from the observed CISB enables us to consistently interpret the hydrological monitoring data of three tracer tests, each conducted during an injection rate step, and preinjection hydraulic-thermal-tracer tests. Finally, this interpretation of the CISB and flow channel network can guide future modeling and data inversion to best understand the effects of natural heterogeneity on CO 2 storage efficiency and residual trapping.

58 GEOSCIENCES↗
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↗