Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Energy transfer”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles

Interactions between gold metallic nanoparticles and molecular dyes have been well described by the nanometal surface energy transfer (NSET) mechanism. However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. In this study, the NSET formula was slightly modified in the size-dependent dampening constant and skin depth terms to allow for modeling of different metals as well as testing the quenching effects created by variously sized gold, silver, copper, and platinum nanoparticles. Overall, the metal nanoparticles followed more closely the NSET prediction than for Förster resonance energy transfer, though scattering effects began to occur at 20 nm in the nanoparticle diameter. To further improve the NSET theoretical equation, an attempt was made to set a best-fit line of the NSET theoretical equation curve onto the Au and Ag data points. An exhaustive grid search optimizer was applied in the ranges for two variables, 0.1≤C≤2.0 and 0≤α≤4, representing the metal dampening constant and the orientation of donor to the metal surface, respectively. Three different grid searches, starting from coarse (entire range) to finer (narrower range), resulted in more than one million total calculations with values C=2.0 and α=0.0736. The results improved the calculation, but further analysis needed to be conducted in order to find any additional missing physics. With that motivation, two artificial intelligence/machine learning (AI/ML) algorithms, multilayer perception and least absolute shrinkage and selection operator regression, gave a correlation coefficient, R2, greater than 0.97, indicating that the small dataset was not overfitting and was method-independent. This analysis indicates that an investigation is warranted to focus on deeper physics informed machine learning for the NSET equations.

Demers, Steven M. E. (ORCID:0000000192213246)↗
NASA NTRS2002

Total-body irradiation with high-LET particles: acute and chronic effects on the immune system

Although the immune system is highly susceptible to radiation-induced damage, consequences of high linear energy transfer (LET) radiation remain unclear. This study evaluated the effects of 0.1 gray (Gy), 0.5 Gy, and 2.0 Gy iron ion (56Fe(26)) radiation on lymphoid cells and organs of C57BL/6 mice on days 4 and 113 after whole body exposure; a group irradiated with 2.0 Gy silicon ions (28Si) was euthanized on day 113. On day 4 after 56Fe irradiation, dose-dependent decreases were noted in spleen and thymus masses and all major leukocyte populations in blood and spleen. The CD19(+) B lymphocytes were most radiosensitive and NK1.1(+) natural killer (NK) cells were most resistant. CD3(+) T cells were moderately radiosensitive and a greater loss of CD3(+)/CD8(+) T(C) cells than CD3(+)/CD4(+) T(H) cells was noted. Basal DNA synthesis was elevated on day 4, but response to mitogens and secretion of interleukin-2 and tumor necrosis factor-alpha were unaffected. Signs of anemia were noted. By day 113, high B cell numbers and low T(C) cell and monocyte percents were found in the 2.0 Gy 56Fe group; the 2.0 Gy 2)Si mice had low NK cells, decreased basal DNA synthesis, and a somewhat increased response to two mitogens. Collectively, the data show that lymphoid cells and tissues are markedly affected by high linear energy transfer (LET) radiation at relatively low doses, that some aberrations persist long after exposure, and that different consequences may be induced by various densely ionizing particles. Thus simultaneous exposure to multiple radiation sources could lead to a broader spectrum of immune dysfunction than currently anticipated.

NASA Discipline Radiation Health↗
NASA NTRS1974

CO2 photodissociation and vibrational excitation in the planetary atmospheres

The principal subjects of investigation were the determination of the CO2 photodissociation quantum yields at the wavelengths from 1200 A to 1500 A, and the efficiency of electronic-to-vibrational energy transfer in the systems 0(1D) + CO, N2, CO2 yields 0(3P) + CO N2, CO2 vibrational energies. Measurements on the photodissociation quantum yield of CO2 in the 1200-1500 A region show that it is wavelength dependent, and for the six atomic line sources used, the quantum yield varied from 0.2 to 0.8. The data appear to fit the interpretation of stable CO2 bound states mixed with repulsive or predissociating states, since the low quantum yields coincide with the maximum structure in the CO2 absorption spectrum. The first reliable measurements were made on the efficiency of electronic-to-vibrational energy transfer in the systems 0(1D)-CO and 0(1D)-N2, using a uv resonance fluorescence technique. The 0(1D)-CO2 interaction was investigated by infrared techniques.

Slanger, T. G.↗
DOE OSTI2020

Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control

District heating and cooling (DHC) is considered one of the most sustainable technologies to meet the heating and cooling demands of buildings in urban areas. The fifth-generation district heating and cooling (5GDHC) concept, often referred to as ambient loops, is a novel solution emerging in Europe and has become a widely discussed topic in current energy system research. 5GDHC systems operate at a temperature close to the ground and include electrically driven heat pumps and associated thermal energy storage in a building-sited energy transfer station (ETS) to satisfy user comfort. This work presents new strategies for improving the operation of these energy transfer stations by means of a model predictive control (MPC) method based on recurrent artificial neural networks. The results show that, under simple time-of-use utility rates, the advanced controller outperforms a rule-based controller for smart charging of the domestic hot water (DHW) thermal energy storage under specific boundary conditions. By exploiting the available thermal energy storage capacity, the MPC controller is capable of shifting up to 14% of the electricity consumption of the ETS from on-peak to off-peak hours. Therefore, the advanced control implemented in 5GDHC networks promotes coupling between the thermal and the electric sector, producing flexibility on the electric grid.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1992

Modeling of turbulent shear flows

The current progress is documented in the research and development of modeling techniques for turbulent shear flows. These include a two-scale model for compressible turbulent flows and a new energy transfer model. The former represents the status of the efforts to identify compressibility effects in turbulence. The energy transfer model refines a weakly nonlinear wave model developed earlier, which models directly the turbulent large structures. The objective of these activities is to develop second-order closures for compressible turbulent flows.

Liou, William W.↗
NASA NTRS1984

Plasmon device design: Conversion from surface to junction plasmons with grating-couplers

Scaling calculations and numerical studies are used to show that grating couplers provide effective energy transfer between surface plasmons and slower modes localized in the tunnel diodes. Within first order perturbation theory in grating amplitude, 90% efficiency energy transfer occurs within micrometers for realistic structures and materials parameters. Scaling laws are derived. Seventy to 90% of the electromagnetic field energy is concentrated in the oxide layer of an MOM diode after the energy is distributed by longer range modes that have less than 0.1% overlap with the tunneling region. The mode conversion allows the requirements separation for energy transport and power production by inelastic tunneling.

Anderson, L. M.↗
DOE OSTI2021

An Ab Initio Multiple Cloning Method for Non-Adiabatic Excited-State Molecular Dynamics in NWChem

The recently developed ab-initio multiple cloning (AIMC) approach based on the multicongurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to non-adiabatic dynamics with a particular strength in the proper description of decoherence effects due to branching of vibrational wavepackets at a level crossing. In this work, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-eld theory to determine the equations of motion for classical trajectories. The multi-dimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based non-adiabatic coupling approach within the AIMC method, all observable are calculated on-the-y in the non-adiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level non-adiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Frequency-Domain Spectroscopic Study of the Photosystem I Supercomplexes, Isolated IsiA Monomers, and the Intact IsiA Ring

The PSI 3 -IsiA 18 supercomplex is one of the largest and most complicated assemblies in photosynthesis. The IsiA ring, composed of 18 IsiA monomers (IsiA 18 ) surrounding the PSI trimer (PSI 3 ), forms under iron-deficient condition in cyanobacteria and acts as a peripheral antenna. Based on the supercomplex structure recently determined via cryo-EM imaging, we model various optical spectra of the IsiA monomers and IsiA 18 ring. Comparison of the absorption and emission spectra of the isolated IsiA monomers and the full ring reveals that about 2.7 chlorophylls (Chls) are lost in the isolated IsiA monomers. The best fits for isolated monomers spectra are obtained assuming the absence of Chl 508, Chl 517 and 70% loss of Chl 511. The best model describing all three hexamers and the entire ring suggests that the lowest energy pigments are Chls 511, 514 and 517. Based on the modeling results presented in this work we conclude that there are most likely three entry points for EET from the IsiA6 hexamer to the PSI core monomer, with two of these entry points likely being located next to each other (i.e. nine entry points from IsiA 18 to the PSI 3 trimer). Lastly, we show that excitation energy transfer inside individual monomers is fast (< 2 ps at T = 5 K) and at least 20 times faster than inter-monomer energy transfer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rate coefficients for rotational state-to-state transitions in H 2 O + H 2 O collisions for cometary and planetary applications, as predicted by mixed quantum-classical theory

We present new calculations of collision cross sections for state-to-state transitions between the rotational states in an H 2 O + H 2 O system, which are used to generate a new database of collisional rate coefficients for cometary and planetary applications. Calculations were carried out using a mixed quantum-classical theory approach that is implemented in the code MQCT. The large basis set of rotational states used in these calculations permits us to predict thermally averaged cross sections for 441 transitions in para- and ortho-H 2 O in a broad range of temperatures. It is found that all state-to-state transitions in the H 2 O + H 2 O system split into two well-defined groups, one with higher cross-section values and lower energy transfer, which corresponds to the dipole-dipole driven processes. The other group has smaller cross sections and higher energy transfer, driven by higher-order interaction terms. We present a detailed analysis of the theoretical error bars, and we symmetrized the state-to-state transition matrixes to ensure that excitation and quenching processes for each transition satisfy the principle of microscopic reversibility. We also compare our results with other data available from the literature for H 2 O + H 2 O collisions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

A near-wall turbulence model and its application to fully developed turbulent channel and pipe flows

A near wall turbulence model and its incorporation into a multiple-time-scale turbulence model are presented. In the method, the conservation of mass, momentum, and the turbulent kinetic energy equations are integrated up to the wall; and the energy transfer rate and the dissipation rate inside the near wall layer are obtained from algebraic equations. The algebraic equations for the energy transfer rate and the dissipation rate inside the near wall layer were obtained from a k-equation turbulence model and the near wall analysis. A fully developed turbulent channel flow and fully developed turbulent pipe flows were solved using a finite element method to test the predictive capability of the turbulence model. The computational results compared favorably with experimental data. It is also shown that the present turbulence model could resolve the over shoot phenomena of the turbulent kinetic energy and the dissipation rate in the region very close to the wall.

Kim, S.-W.↗
DOE OSTI2024

Localizing Low-Grade Heat Using Hybrid Photonic-Phononic Materials

Creating next-generation devices capable of transducing waste heat into useful work will require building blocks designed to direct low-grade thermal energy at length scales well below the diffraction limit. Characterizing thermally induced energy transfer at the nanoscale, however, is a formidable task due to the simultaneous demand of high spatial and spectral resolution at infrared energies. Leveraging recent advancements in electron energy loss (EEL) and gain (EEG) spectroscopy, we reveal that individual nanostructures can concentrate energy by the resonant thermal excitation of their photonic Fabry–Pérot modes. Specifically, we show that the spatially localized gain signal increases upon in situ heating. Finally, theoretical modeling elucidates the mechanism for these observations by showing that a Purcell enhancement in the local photonic density of states drives the increased rate of infrared energy transfer from the ambient environment to each nanostructure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of polymer structure and material properties on mechanochemical reaction environments for polymer recycling

Plastic waste accumulation necessitates innovative recycling approaches to achieve sustainability goals. Mechanochemical depolymerization offers a solvent-free, energy-efficient route to convert polymers into valuable monomers. In addition to their chemical properties, the way that polymers absorb kinetic energy is a key parameter of any mechanochemical process. This perspective explores the principles underpinning mechanochemical recycling, emphasizing how deformation and localized transient heating mediate energy transfer between impacts and localized excitations. Key factors such as polymer crystallinity, molecular weight, viscoelasticity, and thermal effects are analyzed to elucidate their role in energy transfer mechanisms during ball milling. This work establishes a foundational framework for the design and optimization of mechanochemical recycling by connecting polymer response to mechanical energy with the intention to improve depolymerization efficiency. Future research opportunities are outlined to advance the integration of polymer science and mechanochemistry for scalable, sustainable plastic upcycling.

ball mill↗
DOE OSTI2020

An extended methodology for automated calculations of non-Boltzmann kinetic sequences: H + C 2 H 2 + X and combustion impact

It is generally assumed in phenomenological kinetic models that bimolecular reactions only occur between species whose rovibrational energy follows a Boltzmann (thermal) distribution. That is, any complexes initially formed in non-Boltzmann distributions are assumed to be thermalized by energy-transferring collisions prior to bimolecular reactions. Given the high mole fractions of reactive species, X, in combustion environments, reactive collisions of the complexes with X often occur on the same timescale as energy-transferring collisions – yielding sequences proceeding through non-Boltzmann intermediates across multiple potential energy surfaces. Recent studies have shown that such non-Boltzmann kinetic sequences can have substantial impact on the global reactivity in combustion systems. Simulations of these non-Boltzmann reaction sequences, which can be described in phenomenological kinetic models via chemically termolecular reactions, require that rovibrational excitation from one potential energy surface be carried over to the next. Here this paper presents an extended theoretical and computational methodology that couples multiple master equations and derives rate constants for phenomenological reactions describing the conversion of thermal reactants to thermal products for use in phenomenological kinetic schemes. The methodology is then implemented using in-house scripts for non-Boltzmann sequences involving C2H$^*_3$ + X (with X = O 2 , H, and OH) where C 2 H$^*_3$ is formed via H + C 2 H 2 association – which were identified as having strong potential for influencing combustion predictions in a recent study. The results reveal that non-Boltzmann reaction sequences for X = O 2 (the primary focus of this paper) significantly alters the total conversion rate from H + C 2 H 2 to products and product branching fractions from those of thermal sequential pathways. Furthermore, the present results demonstrate that non-Boltzmann reaction sequences have significant impact – as high as an order of magnitude – on predicted ignition delay times. Similarly, they yield significantly different dependence of ignition delay times with temperature and O 2 mole fraction – yielding signatures that are likely observable experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Biomimetic Light Harvesting Complexes Based on Self-Assembled Dye-DNA Nanostructures (Final Technical Report)

A fundamental limitation in the development of artificial molecular light harvesting structures is that generally if one places pigment molecules close enough to achieve very high energy transfer efficiency and absorbance cross section, the dyes interact in such a way that self-quenching occurs. This limits both the optical cross section and the overall efficiency of light capture in such systems. Nature overcomes this problem and achieves efficient energy transfer without self-quenching by controlling the environment, vibration characteristics, orientation and dynamics of the pigments involved in light harvesting. Natural light harvesting systems have evolved highly intricate chromophore architectures of protein-bound organic molecules that absorb and funnel solar energy with high efficiency and fast transfer rates using elegant excitonic circuitries. Nature achieves this precise control over the properties of pigment complexes by using specific proteins as templates to guide the formation of very well-defined pigment aggregates, groups of pigment molecules that are in close enough contact to undergo excitonic interactions resulting in new electronic properties that were not present in the monomer. In synthetic systems, pigment aggregates are well known, and J-aggregates and H-aggregates have been long studied for their unique properties. In Nature, the chlorosomes of green bacteria form what appear to be classical J-aggregates and the light harvesting complexes of purple nonsulfur bacteria form ring structures that have many of the properties of J-aggregates such as a red-shifted absorbance spectrum and excited states that are delocalized over multiple pigment molecules. These photosynthetic systems leverage the spectral and enhanced transport properties of J-like aggregates to achieve fast exciton transport within the antenna and thus high light-harvesting efficiency. The close interaction of the pigments results in substantial electronic coupling that lifts the degeneracy of excitonic states and therefore modifies the absorption and emission spectra of the monomer. In the case of J-aggregation, lower energy excitonic states acquire significant oscillator strength, resulting in a characteristic bathochromic shift of the absorption and fluorescence and often superradiant delocalized exciton states.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Optimization of transformer ratio and beam loading in a plasma wakefield accelerator with a structure-exploiting algorithm

Plasma-based acceleration has emerged as a promising candidate as an accelerator technology for a future linear collider or a next-generation light source. We consider the plasma wakefield accelerator (PWFA) concept where a plasma wave wake is excited by a particle beam and a trailing beam surfs on the wake. For a linear collider, the energy transfer efficiency from the drive beam to the wake and from the wake to the trailing beam must be large, while the emittance and energy spread of the trailing bunch must be preserved. One way to simultaneously achieve this when accelerating electrons is to use longitudinally shaped bunches and nonlinear wakes. In the linear regime, there is an analytical formalism to obtain the optimal shapes. In the nonlinear regime, however, the optimal shape of the driver to maximize the energy transfer efficiency cannot be precisely obtained because currently no theory describes the wake structure and excitation process for all degrees of nonlinearity. In addition, the ion channel radius is not well defined at the front of the wake where the plasma electrons are not fully blown out by the drive beam. We present results using a novel optimization method to effectively determine a current profile for the drive and trailing beam in PWFA that provides low energy spread, low emittance, and high acceleration efficiency. We parameterize the longitudinal beam current profile as a piecewise-linear function and define optimization objectives. For the trailing beam, the algorithm converges quickly to a nearly inverse trapezoidal trailing beam current profile similar to that predicted by the ultrarelativistic limit of the nonlinear wakefield theory. For the drive beam, the beam profile found by the optimization in the nonlinear regime that maximizes the transformer ratio also resembles that predicted by linear theory. Furthermore, the current profiles found from the optimization method provide higher transformer ratios compared with the linear ramp predicted by the relativistic limit of the nonlinear theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗