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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Pairing mechanism among ionic liquid ions in aqueous solutions. A molecular dynamics study

In this study, we carried out molecular dynamics simulations to examine the molecular mechanism for ionic liquid pair association in aqueous solutions. We chose the commonly studied imidazolium-based ionic liquid pairs. We computed potentials of mean force (PMF) for four systems—1,3-dimethlylimidazoliumchloride; 1,3-dimethlylimidazolium iodide; 1-methly-3-octylimidazolium chloride; and 1-methly-3-octylimidazolium iodide. Our PMF studies show a stronger interaction for the ion pairs of systems involving dimethlylimidazolium as the cation species compared to that of the systems containing octylimidazolium. This result indicates a decrease in ion-pair association as the cation alkyl tail length increases. We also studied the kinetics of ion-pair dissociation using different rate theories such as the Grote-Hynes and Kramer’s theories. As expected, the computed rate results significantly deviated from results obtained from transition state theory because it does not account for dynamical solvent effects. Dissociative barrier curvatures are found to be very small for the systems investigated because the transmission coefficients computed using Grote-Hynes theory and Kramer’s theory are approximately equal. Our analysis of the rotational dynamics of cations revealed that the time scales for molecular reorientation are longer for cations with longer alkyl tails. This work was supported by the U.S. Department of Energy (DOE), Office of Basic Energy Sciences (BES), Division of Chemical Sciences, Geosciences, and Biosciences. Pacific Northwest National Laboratory is a multiprogram national laboratory operated for DOE by Battelle. The calculations were carried out using computer resources provided by BES.

Annapureddy, Harsha V.↗
DOE OSTI2015

Relaxation processes in a system with logarithmic growth

Here, we discuss relaxation and aging processes in the one- and two-dimensional ABC models. In these driven diffusive systems of three particle types, biased exchanges in one direction yield a coarsening process characterized in the long-time limit by a logarithmic growth of ordered domains that take the form of stripes. From the time-dependent length, derived from the equal-time spatial correlator, and from the mean displacement of individual particles different regimes in the formation and growth of these domains can be identified. Analysis of two-times correlation and response functions reveals dynamical scaling in the asymptotic logarithmic growth regime as well as complicated finite-time and finite-size effects in the early and intermediate time regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

The RAPTR furnace: a rapid heating and cooling sample furnace for in situ X-ray scattering studies of temperature-induced reactions

In situX-ray scattering provides valuable insights into the mechanisms and kinetics of reactions and structural transformations. For reactions and structural transformations primarily driven by temperature, and not coupled to chemical/electrochemical triggers, our ability to initiate and quench processes thermally is a practical limit for probing fast reactive phenomena. Meaningful quantitative analysis requires the dynamic phenomena to be triggered on fast time scales relative to the reaction/transformation kinetics. This article describes a new sample furnace, the Rapid-Actuating Pneumatic Thermal Reactor or RAPTR, for time-resolvedin situX-ray scattering studies initiated by temperature. The RAPTR quickly heats and cools samples by translating them into and out of a pre-heated hot zone. Using diffraction thermometry, it is shown that the samples can be heated/cooled in 10 s or less, with temperatures up to ∼1000°C being accessible. The application of the RAPTR furnace is demonstrated by exploring a fast solid-state reaction: the synthesis of scheelite-type lead tungstate, PbWO 4 , from PbO and WO 3 for which Pb 3 WO 6 is identified as a previously unrecognized reaction intermediate.

Chemistry↗
DOE OSTI2018

Oscillations of the Degree of Circular Polarization in the Optical Spin Hall Effect

The optical spin Hall effect appears when elastically scattered exciton polaritons couple to an effective magnetic field inside of quantum wells in semiconductor microcavities. Theory predicts an oscillation of the pseudospin of the exciton polaritons in time. Here, we present a detailed analysis of momentum space dynamics of the exciton polariton pseudospin. Compared to what is predicted by theory, we find a higher modulation of the temporal oscillations of the pseudospin. We attribute the higher modulation to additional components of the effective magnetic field which have been neglected in the foundational theory of the optical spin Hall effect. Adjusting the model by adding non-linear polariton-polariton interactions, we find a good agreement in between the experimental results and simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A File Format and API for Dynamic Radar Cross Section Data

Often the Radar Cross-Section (RCS) of a target is incorrectly assumed to be a single number by those unfamiliar with electromagnetic scattering. In actuality, a target's RCS depends on many factors. These factors include radar signal frequency, radar observation angle, as well as target orientation. Another possible parameter (often not considered) is time. The RCS of targets may change over time due to movement, environmental changes, etc. In order to accurately represent the dynamic RCS of a target in a time-stepped analysis, the ability to interface with large RCS datasets efficiently is desired. To this end, a file format and API (written in C++) were developed and are described in this report.

42 ENGINEERING↗
DOE OSTI2021

“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

Background: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. Objective: The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. Methods: We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. Results: Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to non-misinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. Conclusions: Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will

5g↗
DOE OSTI2022

Effects of Port Angle on Scavenging of an Opposed Piston Two-Stroke Engine

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/ boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios. Results indicate that scavenging performance is correlated with the bulk swirl ratio generated by these port angles. Scavenging performance is also sensitive to the pressure ratio across the engine. It was concluded that, for a given pressure ratio, the smallest port angle produces the best scavenging; however, previous work indicates lower bulk swirl ratio during combustion can have an impact on emissions formation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Validation of the Modelling of Corrosion Driven Expansion in Grouted Waste-forms - 16125

One of the current preferred solutions for the disposal of Intermediate Level radioactive waste in the UK is grout encapsulation inside steel boxes for long term storage. These boxes are then to be entombed in a Geological Disposal Facility once one is available. However, both prior to and during geological disposal, waste contents can react with the water present in the encapsulant grout and begin to corrode. This corrosion product occupies a larger volume (by several hundred percent) than the original material and the corrosion occurs over the course of decades and centuries, long after the encapsulant grout has set and hardened. The expanding waste then creates stresses in the encapsulant causing both it and the surrounding box to deform and, in extreme circumstances, and after long times, for the structural integrity of the box to fail. This behaviour needs to be quantified before the box can be approved for use as any excessive deformation could lead to a loss of containment or, since the boxes are stacked on top of each other, to a significant accident in the stores. Due to the long timescales involved, physical testing of the phenomenon in full scale is impossible. Instead, a combination of chemical modelling and finite element analysis is used to predict the extent of the corrosion in the waste and its effect of the integrity of the box. There are a number of difficulties in modelling the corrosion-driven expansion and subsequent deformation of the boxes. Although the corrosion occurs over a very long time scale, the event is highly non-linear and dynamic. All of the material models, including the steel and grout are non-linear. The deformation is in the order of 10s of centimetres, well beyond the static elastic range. Finally, the components must be allowed to move relative to each other which involve a lot of part to part contacts. This means that simple static modelling, which would solve quite quickly, cannot be used. Instead a dynamic analysis code, LS-DYNA, has been used to expand the product over time to simulate the corrosion-driven expansion. This software is generally used for modelling car crashes or scenarios where waste containers have been dropped. The analyses therefore include a significant inertial component. This paper will detail the NNL's approach to modelling this long-term, quasi-static phenomenon in the dynamic, impact oriented software code LS-DYNA. It will cover the problems inherent in this approach, the errors that it creates as well as the tests and solutions that NNL worked on in order to overcome them and be confident that the solution could be validated. This work will ultimately be used to determine the maximum inventory which can be stored in each box based on the waste content and the potential extent of expansion as well as any modification that could be made to the box design or the processing streams that may improve the storage solution. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Anisotropic universe with anisotropic sources

We analyze the state space of a Bianchi-I universe with anisotropic sources. Here we consider an extended state space which includes null geodesics in this background. The evolution equations for all the state observables are derived. Dynamical systems approach is used to study the evolution of these equations. The asymptotic stable fixed points for all the evolution equations are found. We also check our analytic results with numerical analysis of these dynamical equations. The evolution of the state observables are studied both in cosmic time and using a dimensionless time variable. Then we repeat the same analysis with a more realistic scenario, adding the isotropic (dust like dark) matter and a cosmological constant (dark energy) to our anisotropic sources, to study their co-evolution. The universe now approaches a de Sitter space asymptotically dominated by the cosmological constant. The cosmic microwave background anisotropy maps due to shear are also generated in this scenario, assuming that the universe contains anisotropic matter along with the usual (dark) matter and vacuum (dark) energy since decoupling. We find that they contribute dominantly to the CMB quadrupole. We also constrain the current level of anisotropy and also search for any cosmic preferred axis present in the data. We use the Union 2 Supernovae data to this extent. An anisotropy axis close to the mirror symmetry axis seen in the cosmic microwave background data from Planck probe is found.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Following the mass adoption of external accelerators for high performance computing, the overall performance of many applications has become increasingly dependent on relatively small accelerated kernels. As static analysis is fundamentally limited by dynamic values and external definitions, standard ahead-of-time compilation is not always sufficient to achieve the best performance. Furthermore, many users looking to port an existing application to run on an external accelerator will not want to fundamentally restructure their programs. These and other problems can be addressed through both link-time optimization (LTO) and just-in-time (JIT) compilation, but until now had sparse and inconsistent support from the compiler. In this work, we present a new compilation method that enables device-side LTO as well as a transparent JIT compilation tool-chain for OpenMP target offloading. Our contributions include an entirely new device linking and embedding scheme to enable LTO as well as a novel JIT engine to efficiently optimize OpenMP offloading regions at run-time. We also introduce a persistent caching system to improve end-to-end runtime using the JIT engine and minimize kernel launching overheads. We measure the performance of our LTO and JIT implementation via several real-world scientific applications. With our optimizations we observe significant improvements through LTO on large applications as well as significant end-to-end execution time improvement using JIT.

Tian, Shilei↗
DOE OSTI2016

Efficient sensitivity analysis method for chaotic dynamical systems

The direct differentiation and improved least squares shadowing methods are both developed for accurately and efficiently calculating the sensitivity coefficients of time averaged quantities for chaotic dynamical systems. The key idea is to recast the time averaged integration term in the form of differential equation before applying the sensitivity analysis method. An additional constraint-based equation which forms the augmented equations of motion is proposed to calculate the time averaged integration variable and the sensitivity coefficients are obtained as a result of solving the augmented differential equations. The application of the least squares shadowing formulation to the augmented equations results in an explicit expression for the sensitivity coefficient which is dependent on the final state of the Lagrange multipliers. The LU factorization technique to calculate the Lagrange multipliers leads to a better performance for the convergence problem and the computational expense. Numerical experiments on a set of problems selected from the literature are presented to illustrate the developed methods. The numerical results demonstrate the correctness and effectiveness of the present approaches and some short impulsive sensitivity coefficients are observed by using the direct differentiation sensitivity analysis method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Investigating Carboxysome Morphology Dynamics with a Rotationally Invariant Variational Autoencoder

Carboxysomes are a class of bacterial microcompartments that form proteinaceous organelles within the cytoplasm of cyanobacteria and play a central role in photosynthetic metabolism by defining a cellular microenvironment permissive to CO2 fixation. Critical aspects of the assembly of the carboxysomes remain relatively unknown, especially with regard to the dynamics of this microcompartment. Progress in understanding carboxysome dynamics is impeded in part because analysis of the subtle changes in carboxysome morphology with microscopy remains a low-throughput and subjective process. Here we use deep learning techniques, specifically a Rotationally Invariant Variational Autoencoder (rVAE), to analyze fluorescence microscopy images of cyanobacteria bearing a carboxysome reporter and quantitatively evaluate how carboxysome shell remodelling impacts subtle trends in the morphology of the microcompartment over time. Toward this goal, we use a recently developed tool to control endogenous protein levels, including carboxysomal components, in the model cyanobacterium Synechococcous elongatus PCC 7942. By utilization of this system, proteins that compose the carboxysome can be tuned in real time as a method to examine carboxysome dynamics. We find that rVAEs are able to assist in the quantitative evaluation of changes in carboxysome numbers, shape, and size over time. Further, we propose that rVAEs may be a useful tool to accelerate the analysis of carboxysome assembly and dynamics in response to genetic or environmental perturbation and may be more generally useful to probe regulatory processes involving a broader array of bacterial microcompartments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dynamic Evaluation of the Upper Tyler Formation and Well Stimulation Fluid Interactions Using Micro-CT Imaging

Abundant concentrations of swelling clays in the oil-bearing upper Tyler Formation inhibit unconventional well stimulation techniques and associated long-term oil and gas production success. Laboratory evaluation of the geochemical interactions between the formation material and various stimulation fluids may help identify innovative approaches that provide a solution to successful well stimulation and subsequent oil production. The objective of this research was to understand the complexities of well stimulation fluid and clay mineral interactions within the Tyler Formation and identify potential fracturing fluid formulations that mitigate swelling properties of the clays in the reservoir to enhance stimulation success and promote long-term oil and gas production. Collaboration with the National Energy Technology Laboratory (NETL), utilizing their Tescan DynaTOM micro-CT analysis instrumentation, provided an innovative approach to understand real-time, dynamic interactions of the formation material and various potential stimulation fluids. Results are anticipated to identify key mechanisms occurring at the micro-scale level and provide insight into modified stimulation techniques uniquely suited for successful production applications.

enhanced oil recovery↗
DOE OSTI2014

Optimization Method to Branch and Bound Large SBO State Spaces Under Dynamic Probabilistic Risk Assessment via use of LENDIT Scales and S2R2 Sets

Traditional Probabilistic Risk Assessment (PRA) methods have been developed and are quite effective in evaluating risk associated with complex systems, but lack the capability to evaluate complex dynamic systems. These time and energy scales associated with the transient may vary as a function of transition time to a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems, while complete, results in issues associated with combinatorial explosion. In order to address the combinatorial complexity arising from the number of possible state configurations and discretization of transition times, a characteristic scaling metric (LENDIT – length, energy, number, distribution, information and time) is proposed as a means to describe systems uniformly and thus provide means to describe relational constraints expected in the dynamics of a complex (coupled) systems. Thus when LENDIT is used to characterize four sets – ‘state, system, resource and response’ (S2R2) – describing reactor operations (normal and off-normal), LENDIT and S2R2 in combination have the potential to ‘branch and bound’ the state space investigated by DPRA. In this paper we introduce the concept of LENDIT scales and S2R2 sets applied to a branch-and-bound algorithm and apply the methods to a station black out transient (SBO).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Dynamics from noisy data with extreme timing uncertainty

Imperfect knowledge of the times at which ‘snapshots’ of a system are recorded degrades our ability to recover dynamical information, and can scramble the sequence of events. In X-ray free-electron lasers, for example, the uncertainty—the so-called timing jitter—between the arrival of an optical trigger (‘pump’) pulse and a probing X-ray pulse can exceed the length of the X-ray pulse by up to two orders of magnitude, marring the otherwise precise time-resolution capabilities of this class of instruments. The widespread notion that little dynamical information is available on timescales shorter than the timing uncertainty has led to various hardware schemes to reduce timing uncertainty. These schemes are expensive, tend to be specific to one experimental approach and cannot be used when the record was created under ill-defined or uncontrolled conditions such as during geological events. Here we present a data-analytical approach, based on singular-value decomposition and nonlinear Laplacian spectral analysis, that can recover the history and dynamics of a system from a dense collection of noisy snapshots spanning a sufficiently large multiple of the timing uncertainty. In this work, the power of the algorithm is demonstrated by extracting the underlying dynamics on the few-femtosecond timescale from noisy experimental X-ray free-electron laser data recorded with 300-femtosecond timing uncertainty. Using a noisy dataset from a pump-probe experiment on the Coulomb explosion of nitrogen molecules, our analysis reveals vibrational wave-packets consisting of components with periods as short as 15 femtoseconds, as well as more rapid changes, which have yet to be fully explored. Our approach can potentially be applied whenever dynamical or historical information is tainted by timing uncertainty.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Machine Learning-Based Model Predictive Control of Two-Time-Scale Systems

In this study, we present a general form of nonlinear two-time-scale systems, where singular perturbation analysis is used to separate the dynamics of the slow and fast subsystems. Machine learning techniques are utilized to approximate the dynamics of both subsystems. Specifically, a recurrent neural network (RNN) and a feedforward neural network (FNN) are used to predict the slow and fast state vectors, respectively. Moreover, we investigate the generalization error bounds for these machine learning models approximating the dynamics of two-time-scale systems. Next, under the assumption that the fast states are asymptotically stable, our focus shifts toward designing a Lyapunov-based model predictive control (LMPC) scheme that exclusively employs the RNN to predict the dynamics of the slow states. Additionally, we derive sufficient conditions to guarantee the closed-loop stability of the system under the sample-and-hold implementation of the controller. A nonlinear chemical process example is used to demonstrate the theory. In particular, two RNN models are constructed: one to model the full two-time-scale system and the other to predict solely the slow state vector. Both models are integrated within the LMPC scheme, and we compare their closed-loop performance while assessing the computational time required to execute the LMPC optimization problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Light-induced protein structural dynamics in bacteriophytochrome revealed by time-resolved x-ray solution scattering

Bacteriophytochromes (BphPs) are photoreceptors that regulate a wide range of biological mechanisms via red light–absorbing (Pr)–to–far-red light–absorbing (Pfr) reversible photoconversion. The structural dynamics underlying Pfr-to-Pr photoconversion in a liquid solution phase are not well understood. We used time-resolved x-ray solution scattering (TRXSS) to capture light-induced structural transitions in the bathy BphP photosensory module of Pseudomonas aeruginosa. Kinetic analysis of the TRXSS data identifies three distinct structural species, which are attributed to lumi-F, meta-F, and Pr, connected by time constants of 95 μs and 21 ms. Structural analysis based on molecular dynamics simulations shows that the light activation of PaBphP accompanies quaternary structural rearrangements from an “II”-framed close form of the Pfr state to an “O”-framed open form of the Pr state in terms of the helical backbones. This study provides mechanistic insights into how modular signaling proteins such as BphPs transmit structural signals over long distances and regulate their downstream biological responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Analysis of Hydrocyclone Geometry via Rapid Optimization Based on Computational Fluid Dynamics

Abstract Hydrocyclones exploit density gradients for the centrifugal separation of dispersions in a continuous liquid. Selection of the geometrics for optimal separation is case specific, like the media characteristics. The existing optimization method based on computational fluid dynamics (CFD) provides a powerful analytical tool but requires long computational times. The most common praxis for CFD optimization is via the single‐factor optimization method (SFOM). In this study, a novel approach is presented as an improved rapid optimization method that implements a dynamic‐mesh and user‐defined function optimization method (DUOM). The DUOM adapts the dynamic‐mesh approach from other applications to the optimization analysis of hydrocyclones. The DUOM reduced the computational time by 31.1 %, compared to the SFOM.

Liu, Lin↗