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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Numerical similarity solution for a variable coefficient K(m, n) equation

A technique for finding numerical similarity solutions to an initial boundary value problem (IBVP) for generalized K(m, n) equations is described. The equation under consideration is nonlinear and has variable coefficients. The original problem is transformed with the aid of Lie symmetries to an initial value problem (IVP) for a nonlinear third-order ordinary differential equation. The existence and uniqueness of the solution are examined, and the problem is consequently solved with the aid of a finite-difference scheme for various values of the governing parameters. In lieu of an exact symbolic solution, the scheme is validated by comparing the numerical solutions with the approximate analytic solutions obtained with the aid of the method of successive approximations in their region of validity. The accuracy, efficiency, and consistency of the scheme are demonstrated. Numerical solutions to the original initial boundary value problem are constructed for selected parameter values with the aid of the transforms. The qualitative behavior of the solutions as a function of the governing parameters is analyzed, and it is found that the examined IBVPs for generalized K(m, n) equations with variable coefficients that are functions of time, do not admit solitary wave or compacton solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quasilinear theory: the lost ponderomotive effects and why they matter

Quasilinear theory (QLT) has been used for modeling wave–plasma interactions for decades but remains largely heuristic. Plasma inhomogeneity, ponderomotive effects, microscopic fluctuations, and collisions are not easily accommodated from first principles in QLT, and typically are ignored entirely, due to the limitations of the standard Fourier–Laplace global-mode approach. This results in inconsistencies, for example, violation of the action conservation for nonresonant waves. However, these issues can be avoided, and the theory can be substantially generalized and corrected, if QLT is formulated using more suitable analytical tools, particularly, the Weyl symbol calculus. Here, an attempt is made to deliver an accessible review of this modern formulation, provide intuitive calculations for special cases, and elaborate on the connection with the ‘oscillation-center QLT’ originally proposed by Dewar (Phys Fluids 16:1102, 1973). A Fokker–Planck equation for a ‘dressed’ distribution is derived from the Klimontovich equation and captures quasilinear diffusion, ponderomotive forces, and interactions with background fields for a generic Hamiltonian, so many known formulations of QLT for specific plasma models become corollaries of a single unifying theory. Also, waves are allowed to be off-shell (not constrained by a dispersion relation), which allows them to accommodate microscopic fluctuations. This leads to a collision integral of the Balescu–Lenard type that has all the usual properties but is not restricted to any specific plasma model. For on-shell waves, a generalized version of the classic oscillation-center QLT is obtained. Finally, combined with the wave-kinetic equation, this formulation not only conserves particles, momentum, and energy, like the classic QLT but also reinstates the action conservation for nonresonant waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Conservation laws, bilinear forms and solitons for a fifth-order nonlinear Schrödinger equation for the attosecond pulses in an optical fiber

Under investigation in this paper is a fifth-order nonlinear Schrödinger equation, which describes the propagation of attosecond pulses in an optical fiber. Based on the Lax pair, infinitely-many conservation laws are derived. With the aid of auxiliary functions, bilinear forms, one-, two- and three-soliton solutions in analytic forms are generated via the Hirota method and symbolic computation. Soliton velocity varies linearly with the coefficients of the high-order terms. Head-on interaction between the bidirectional two solitons and overtaking interaction between the unidirectional two solitons as well as the bound state are depicted. For the interactions among the three solitons, two head-on and one overtaking interactions, three overtaking interactions, an interaction between a bound state and a single soliton and the bound state are displayed. Graphical analysis shows that the interactions between the two solitons are elastic, and interactions among the three solitons are pairwise elastic. Stability analysis yields the modulation instability condition for the soliton solutions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Generalized Bose–Hubbard Hamiltonians exhibiting a complete non-Hermitian degeneracy

Highlights: • Hot topic: physics with non-Hermitian Hamiltonians. • Computer algebra used to construct new, next-to-BH models. • Degeneracy verification via variable-precision arithmetics. • Unfolding patterns at N>5 (recent problem solved). - Abstract: The method of construction of the tridiagonal and symmetric complex-matrix Hamiltonians H{sup (N)}(z) exhibiting an exceptional-point (EP) degeneracy of the Nth (i.e., maximal) order at a preselected parameter z=z{sup (EPN)}=1 is proposed and tested. In general, the implementation of the method requires the use of computer-assisted symbolic manipulations, especially at the larger matrix dimensions N. The well known PT−symmetric N-by-N-matrix Bose–Hubbard Hamiltonians as well as their recent N≤5 non-Bose–Hubbard alternatives are obtained as special solutions. Several other N≥6 non-Bose–Hubbard models H{sup (N)}(z) exhibiting the maximal EPN degeneracy are also constructed and analyzed in detail. In particular, their z−dependent, real or complex spectra of energies are displayed and discussed near as well as far from z{sup (EPN)}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The response field and the saddle points of quantum mechanical path integrals

Highlights: • Moyal quantum mechanics and Marinov’s path integral. • Classical and semiclassical limits of Marinov’s path integral. • Oscillating functional integrals. • Instantons of the Marinov’s path integral. In quantum statistical mechanics, Moyal’s equation governs the time evolution of Wigner functions and of more general Weyl symbols that represent the density matrix of arbitrary mixed states. A formal solution to Moyal’s equation is given by Marinov’s path integral. In this paper we demonstrate that this path integral can be regarded as the natural link between several conceptual, geometric, and dynamical issues in quantum mechanics. A unifying perspective is achieved by highlighting the pivotal role which the response field, one of the integration variables in Marinov’s integral, plays for pure states even. The discussion focuses on how the integral’s semiclassical approximation relates to its strictly classical limit; unlike for Feynman type path integrals, the latter is well defined in the Marinov case. The topics covered include a random force representation of Marinov’s integral based upon the concept of “Airy averaging”, a related discussion of positivity-violating Wigner functions describing tunneling processes, and the role of the response field in maintaining quantum coherence and enabling interference phenomena. The double slit experiment for electrons and the Bohm–Aharonov effect are analyzed as illustrative examples. Furthermore, a surprising relationship between the instantons of the Marinov path integral over an analytically continued (“Wick rotated”) response field, and the complex instantons of Feynman-type integrals is found. The latter play a prominent role in recent work towards a Picard–Lefschetz theory applicable to oscillatory path integrals and the resurgence program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Crybb2 associates with Tmsb4X and is crucial for dendrite morphogenesis

Highlights: • A structural protein of ocular lens, Crybb2, has function in neuronal development. • Crybb2 contributes to dendritogenesis in vitro and in vivo. • Tmsb4X up-regulated in Crybb2 mutants mouse brain. • Overexpression of Tmsb4X inhibits dendritogenesis phenocopied the Crybb2 knock-down in hippocampal neuron. Dendrite morphogenesis is a complex but well-orchestrated process. Various studies reported the involvement of alteration in dendrite morphology in different brain disorders, including neuropsychiatric disorders. Initially, βB2-crystallin (gene symbol: Crybb2/CRYBB2) has been described as a structural protein of the ocular lens. Mutations of the corresponding gene, Crybb2, lead to cataract. Recent studies in mice suggested that mutations in Crybb2 cause alterations in hippocampal morphology and function, albeit its function in hippocampal neuron development remained elusive. In the current study, we found that Crybb2 contributes to dendritogenesis in vitro and in vivo. Furthermore, screening of previous data on differential expression-arrays, we found Tmsb4X up-regulated in Crybb2 mutants mouse brain. Additionally, Tmsb4X was co-expressed with Crybb2 at actin-enriched cell ruffles. Over-expression of Tmsb4X in cultured hippocampal neurons inhibited dendritogenesis, which phenocopied Crybb2 knock-down. The current study uncovers a new function of Crybb2 in brain development, especially in dendritogenesis, and the possible interplay partner Tmsb4X involved in this process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

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

Rapid multiphase-field model development using a modular free energy based approach with automatic differentiation in MOOSE/MARMOT

In this paper, we present a novel rapid phase-field model development capability using a modular free energy based approach in the finite element based MOOSE framework. The phase-field equations are implemented in a general form as separate code form the model specific data such as the thermodynamic free energy density and mobility functions. This isolates researchers from complicated code and allows them to focus on implementing new material models. In addition, using a native symbolic differentiation algorithm, all required derivatives of the free energy density are automatically determined, removing sources for potential human error, and guaranteeing optimally preconditioned equation systems through fully populated Jacobian matrices. Free energy terms contributing to a phase-field model are abstracted into self contained objects that can be combined at will at simulation run time. Combining multiple chemical and mechanical free energy contributions allows the construction of coupled phase-field, mechanics, and multiphase models. Through just-in-time compilation, we greatly reduce the computational time required to evaluate the differentiated expressions. Lastly, we demonstrate the new capability on a variety of example simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Towards physics-informed explainable machine learning and causal models for materials research

From emergent material descriptions to estimation of properties stemming from structures to optimization of process parameters for achieving best performance – all key facets of materials science and related fields have experienced tremendous growth with the introduction of data-driven models. This gradual progression goes at par with developments of machine learning workflows, from purely data-driven shallow models to those that are well-capable in encoding more complex graphs, symbolic representations, invariances, and positional embeddings. Furthermore, this perspective aims at summarizing strategic aspects of such transitions while providing insights into the requirements of bringing in explainable, interpretable predictive models, and causal learning to aid in materials design and discovery. Although the focus remains on a variety of functional materials by providing a handful of case studies, the applications of such integrated methodologies are universal to facilitate fundamental understandings of materials physics while enabling autonomous experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Innovative large overbraided carbon fiber composite beams in historical Friendship Bell Pavilion

The International Friendship Bell Pavilion located in the City of Oak Ridge, Tennessee symbolizes the spirit of the peace and friendship shared by the city of Oak Ridge and city of Naka, Japan. The Bell Pavilion features an 8000-pound bronze cast bell along with futuristic materials and advanced manufacturing technologies. The team has developed innovative overbraided carbon fiber arched beams in conjunction with the bronze bell. Carbon fiber was utilized in these beams because of its lightweight, strong, stiff, and durable characteristics. A sandwich design used a high-performance foam core, overbraided with triaxial carbon fibers. This is the world’s largest overbraided composite structure for parks and recreation. For the first time in such an application, 17 free floating, 33-foot (10 m) long arched carbon fiber composite beams cantilever from a central concrete-steel superstructure over the bronze bell. The arc radius of the bottom of each beam is uniquely different giving an appearance of an open dome when standing underneath the structure.

Parks and Recreation↗
DOE OSTI2022

Q-POP-Thermo: A general-purpose thermodynamics solver for ferroelectric materials

We report that Q-POP-Thermo is a program designed to compute thermodynamic monodomain equilibrium states and their properties for ferroelectric single crystals and thin films based on the Landau-Ginzburg-Devonshire (LGD) Theory. Utilizing symbolic manipulation with the SymPy Library, the governing equations along with appropriate boundary conditions are solved for speedy minimization of the free energy of a crystal. Utilizing the popular Differential Evolution algorithm, with appropriate hybridization, multiple phase diagrams, such as the pressure-temperature phase diagram for bulk single crystals and the common strain-temperature phase diagram for monodomain thin-film systems can be readily generated. Furthermore, a variety of material properties of stable ferroelectric phases, including dielectric, piezoelectric, and electrocaloric properties, can simultaneously be calculated. Validation studies are presented for both thin-film and single crystal systems to test the effectiveness and capability of the open-source program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Towards high data-rate diffusive molecular communications: A review on performance enhancement strategies

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance enhancement strategies is surveyed; key research directions are identified. Signaling design and associated design constraints are presented. Here, studies on fundamental information theoretic limits of DiMC channel are reviewed. Classical and novel transceiver designs are discussed with an emphasis on methods for ISI mitigation and performance-complexity tradeoffs. Key parameter estimation strategies such as synchronization and channel estimation are considered in conjunction with asynchronous and timing error robust receiver methods. Finally, source and channel coding in the context of DiMC is presented.

42 ENGINEERING↗
DOE OSTI2016

Equation-based languages – A new paradigm for building energy modeling, simulation and optimization

Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization. We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller that adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. As a result, exploiting the equation-based language led to 2, 200 times faster solution

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Development and Evaluation of HVAC Operation Schedule Detection Algorithm

Small- and medium-sized (<50,000 sf) commercial buildings (SMBs) represent over 94% of the U.S. commercial building stock and consume over 1018 kJ (~1015 Btus) of total site energy. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability and no monitoring or failure management. Therefore, many of them are operated inefficiently and consume excess energy. SMBs typically use packaged rooftop units (RTUs) that are controlled by an individual thermostat. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy/cost savings. This paper is focused only on the detection of the occupancy schedule using the zone temperature. The paper describes the methodology to detect the occupancy schedule, the metric used to validate the algorithm and the validation results. The algorithm has been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithm was successful in detecting the occupancy schedule using a symbolic aggregate approximation (SAX) technique. The results showed that the occupancy schedule detection algorithm using the SAX method performs well under summer (hot) and winter (cold) weather conditions when energy use is the highest. The algorithm can also distinguish different schedules and generate clusters of occupancy scheduling based on zone temperature measurements alone.

Kim, Woohyun↗
DOE OSTI2015

Neurobehavioral effects of arsenic exposure among secondary school children in the Kandal Province, Cambodia

The research was carried out at 3 study sites with varying groundwater arsenic (As) levels in the Kandal Province of Cambodia. Kampong Kong Commune was chosen as a highly contaminated site (300–500 μg/L), Svay Romiet Commune was chosen as a moderately contaminated site (50–300 μg/L) and Anlong Romiet Commune was chosen as a control site. Neurobehavioral tests on the 3 exposure groups were conducted using a modified WHO neurobehavioral core test battery. Seven neurobehavioral tests including digit symbol, digit span, Santa Ana manual dexterity, Benton visual retention, pursuit aiming, trail making and simple reaction time were applied. Children's hair samples were also collected to investigate the influence of hair As levels on the neurobehavioral test scores. The results from the inductively coupled plasma-mass spectrometry (ICP-MS) analyses of hair samples showed that hair As levels at the 3 study sites were significantly different (p<0.001), whereby hair samples from the highly contaminated site (n=157) had a median hair As level of 0.93 μg/g, while the moderately contaminated site (n=151) had a median hair As level of 0.22 μg/g, and the control site (n=214) had a median hair As level of 0.08 μg/g. There were significant differences among the 3 study sites for all the neurobehavioral tests scores, except for digit span (backward) test. Multiple linear regression clearly shows a positive significant influence of hair As levels on all the neurobehavioral test scores, except for digit span (backward) test, after controlling for hair lead (Pb), manganese (Mn) and cadmium (Cd). Children with high hair As levels experienced 1.57–4.67 times greater risk of having lower neurobehavioral test scores compared to those with low hair As levels, after adjusting for hair Pb, Mn and Cd levels and BMI status. In conclusion, arsenic-exposed school children from the Kandal Province of Cambodia with a median hair As level of 0.93 µg/g among those from the highly contaminated study site, showed clear evidence of neurobehavioral effects. - Highlights: • We measured the level of arsenic concentration in school secondary school children's hair. • As contamination in groundwater is the major source effect on the neurobehavioral performance of school children. • School children in highly and moderately contaminated sites are at risk of As exposure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Acute particulate matter affects cardiovascular autonomic modulation and IFN-γ methylation in healthy volunteers

Highlights: • In healthy subjects, acute exposure to PM affects vagal autonomic control of the heart. • PM exposure increases methylation of a pro-inflammatory gene, i.e. methylation of interferon γ (IFN- γ). • PM per se is able to trigger autonomic deregulation and inflammation in a dose-dependent manner. Air particulate matter (PM) is associated with increased cardiovascular morbidity and mortality. Altered autonomic functions play a key role in PM-induced cardiovascular disease. However, previous studies have not address the impact of PM on sympathetic and parasympathetic control of heart function, independently, and using controlled conditions, i.e., increasing titration of PM of known composition, in absence of other potential confounding factors. To fill this gap, here we used symbolic analysis that is capable of detecting non-mutual changes of the two autonomic branches, thus considering them as independent, and concentrations of PM as they could be measured at peak levels in Milan during a polluted winter day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multidimensional and multitemporal energy injustices: Exploring the downstream impacts of the Belo Monte hydropower dam in the Amazon

Energy transition technologies, such as hydroelectric dams, have been seen as symbols of progress, modernity, cheap energy, environmental sustainability, and resource abundance, leading to overestimating their benefits and underestimating their drawbacks. In this study, we use the tenets approach of energy justice and a qualitative case study to explore, from a multidimensional and multitemporal perspective, the impacts faced by the inhabitants of a community located downstream from the Belo Monte hydroelectric dam. Through in-depth interviews and observations, data were collected at three points: during the late stage of construction (2016) and early operation (2017, 2019). Furthermore, we found that individuals face multiple and diverse energy injustices at various stages of the dam construction, and its severity changes over time. For instance, distributional issues were more predominant at the beginning of data collection since fisheries, their main livelihood activity was impacted by dam construction. Then, other justice issues, such as capabilities, emerged in the last years of data collection.

13 HYDRO ENERGY↗
DOE OSTI2023

Degradation and Modeling of Large-Format Commercial Lithium-Ion Cells as a Function of Chemistry, Design, and Aging Conditions

Demand for large-format (>10 Ah) lithium-ion batteries has increased substantially in recent years, due to the growth of both electric vehicle and stationary energy storage markets. The economics of these applications is sensitive to the lifetime of the batteries, and end-of-life can either be due to energy or power limitations. Despite this, there is little information from cell manufacturers on the sensitivity of cell degradation to environmental conditions or battery use. This work reports accelerated aging test data from four commercial large-format lithium-ion batteries from three manufacturers, with varying design (thickness, casings, ...), chemistry (lithium-iron-phosphate (LFP) or lithium-nickel-manganese-cobalt-oxide positive electrodes (NMC), with graphite (Gr) negative electrodes), and capacity (50 to 250 Amp hours). The tested LFP|Gr cell is found to be relatively insensitive to cycling conditions like temperature or voltage window, while NMC|Gr cells have varying sensitivity. Degradation trends are further investigated by training predictive models: simple polynomial trend lines, a semi-empirical reduced-order model, and an empirical reduced-order model identified using machine-learning based on symbolic regression. Calendar and cycle life are simulated over a variety of conditions to directly compare the various batteries. Cell size and thickness are found to substantially impact sensitivity to temperature during cycle aging, while electrode chemistry impacts depth-of-discharge sensitivity. Real-world battery lifetime is evaluated by simulating residential energy storage and commercial frequency containment reserve systems in several U.S. climate regions. Predicted lifetime across cell types varies from 7 years to 20+ years, though all cells are predicted to have at least 10 year life in certain conditions.

battery lifetime↗