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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of subsurface transport processes of delayed gas signatures applicable to underground nuclear explosions

Radioactive gas signatures from underground nuclear explosions (UNEs) result from gas-migration processes occurring in the subsurface. The processes considered in this study either drive or retard upward migration of gases from the detonation cavity. The relative importance of these processes is evaluated by simulating subsurface transport in a dual-permeability medium for the multi-tracer Noble Gas Migration Experiment (NGME) originally intended to study some aspects of transport from a UNE. For this experiment, relevant driving processes include weak two-phase convection driven by the geothermal gradient, over pressuring of the detonation cavity, and barometric pumping while gas sorption, dissolution, radioactive decay, and usually diffusion represent retarding processes. From deterministic simulations we found that over-pressuring of the post-detonation chimney coupled with barometric pumping produced a synergistic effect amplifying the tracer-gas reaching the surface. Bounding simulations indicated that the sorption and dissolution of gases, tending to retard transport, were much smaller than anticipated by earlier laboratory studies. The NGME observations themselves show that differences in gas diffusivity have a larger effect on influencing upward transport than do the combined effects of tracer-gas sorption and dissolution, which is consistent with a Sobol’ sensitivity analysis. Both deterministic simulations and those considering parametric uncertainties of transport-related properties predict that the excess in concentration of SF 6 compared to 127 Xe as might be captured in small volumetric samples should be much smaller than the order-of-magnitude contrast found in the large-volume gas samples taken at the site. While extraction of large-volume subsurface gas samples is shown to be capable of distorting in situ gas compositions, the highly variable injection rate of SF 6 into the detonation cavity relative to that of 127 Xe at the start of the field experiment is the most likely explanation for the large difference in observed concentrations.

58 GEOSCIENCES↗
DOE OSTI2025

Multi-stage heat pump with two-phase injection for cold climate applications implementing natural refrigerants

Heat pump adoption in cold climates is limited by various technical challenges, including heat capacity degradation, compressor deterioration, and frost accumulation on the outdoor heat exchanger. Furthermore, wide-spread adoption of heat pumps with high global warming potential presents a possible environmental concern. Thus, we present a heat pump concept termed the “saturation cycle,” which uses numerous compression stages to improve energy efficiency and injects two-phase refrigerant between compression stages to dramatically reduce compressor discharge temperatures. Given the growing interest in heat pumps, there is a need for a straightforward framework for parametric evaluation of natural refrigerants in high-efficiency heat pump cycle architectures, like the saturation cycle, in adverse climates. This work develops a thermodynamic modeling framework and focuses on the application of natural refrigerants to explore the performance trends at extremely cold climates down to −25 °C. This study shows that a two-stage saturation cycle and four-stage saturation cycle can reduce the compressor discharge superheating by up to 51–57 % or 73–80 %, respectively, depending on the refrigerant. Furthermore, at −25 °C, a two-stage R-290 saturation cycle heat pump theoretically can use 25 % less power than a single-stage heat pump or can provide up to 59 % more heating capacity when using the same compressor power as the baseline single-stage heat pump. The exergetic parametric analyses show that two-phase refrigerant injection fundamentally improves the thermodynamic performance of the heat pump, reducing overall exergy destruction by 10 % compared to a vapor-injection heat pump, compared at −25 °C. Thus, the saturation cycle is a promising heat pump cycle architecture for cold climate applications due to its superior energy savings (or capacity improvement) and substantial de-superheating capabilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Simulation of 12-bed vacuum pressure-swing adsorption for hydrogen separation from methanol-steam reforming off-gas

This study focuses on analysis of a 12-bed vacuum pressure-swing adsorption (VPSA) process capable of purifying hydrogen from a ternary mixture (H 2 /CO 2 /CO 75/24/1 mol%) derived from methanol-steam reforming. The process produces 9 kmol H 2 /h with less than 2 ppm and 0.2 ppm of CO2 and CO, respectively, to supply a polymer electrolyte membrane fuel cell. The process model is developed in Aspen Adsorption® using the “uni-bed” approach. A parametric study of H 2 purity and recovery with respect to adsorption pressure, adsorbent height, activated carbon:zeolite ratio, feed composition, and number of beds is performed. Results show 12-bed VPSA can meet the H 2 purity goals, with H 2 recovery as high as 75.75%. Adsorption occurs at 7 bar, the column height is 1.2 m, and the adsorbent ratio is 70%:30%. Furthermore, a 4-bed VPSA can achieve the same purity goals as the 12-bed process, but H 2 recovery decreases to 61.34%.

03 NATURAL GAS↗
DOE OSTI2023

Improving the Accuracy of Variational Quantum Eigensolvers with Fewer Qubits Using Orbital Optimization

Near-term quantum computers will be limited in the number of qubits on which they can process information as well as the depth of the circuits that they can coherently carry out. To date, experimental demonstrations of algorithms such as the Variational Quantum Eigensolver (VQE) have been limited to small molecules using minimal basis sets for this reason. In this work we propose incorporating an orbital optimization scheme into quantum eigensolvers wherein a parametrized partial unitary transformation is applied to the basis functions set in order to reduce the number of qubits required for a given problem. The optimal transformation is found by minimizing the ground state energy with respect to this partial unitary matrix. Through numerical simulations of small molecules up to 16 spin orbitals, we demonstrate that this method has the ability to greatly extend the capabilities of near-term quantum computers with regard to the electronic structure problem. Finally, we find that VQE paired with orbital optimization consistently achieves lower ground state energies than traditional VQE when using the same number of qubits and even frequently achieves lower ground state energies than VQE methods using more qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

From disorganized data to emergent dynamic models: Questionnaires to partial differential equations

Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate the data-driven derivation of parameter dependent, evolutionary partial differential equation (PDE) models capable of generating the data. This tensor type of data is reminiscent of shuffled (multidimensional) puzzle tiles. The independent variables for the evolution equations (their “space” and “time”) as well as their effective parameters are all emergent , i.e. determined in a data-driven way from our disorganized observations of behavior in them. We use a diffusion map based questionnaire approach to build a smooth parametrization of our emergent space/time/parameter space for the data. This approach iteratively processes the data by successively observing them on the “space,” the “time” and the “parameter” axes of a tensor. Once the data become organized, we use machine learning (here, neural networks) to approximate the operators governing the evolution equations in this emergent space. Our illustrative examples are based (i) on a simple advection–diffusion model; (ii) on a previously developed vertex-plus-signaling model of Drosophila embryonic development; and (iii) on two complex dynamic network models (one neuronal and one coupled oscillator model) for which no obvious smooth embedding geometry is known a priori. This allows us to discuss features of the process like symmetry breaking, translational invariance, and autonomousness of the emergent PDE model, as well as its interpretability.

generative models↗
DOE OSTI2026

A Parametric Reduced-Order Model for Inverter Short-Circuit Response in Protection Studies

This paper presents a reduced-order model (ROM) for grid-following (GFL) inverters that reproduces inverter fault current trajectories, including sub transients, transient, and steady-state phases, across a range of fault types, locations, and pre-fault operating points. . The proposed model is developed by: Constructing the positive- and negative-sequence current with parameterization fitted by large data training and fitting Validating using EMT simulation against EMT full model and demonstrating the ROM's capability to capture fault current magnitude, phase angle, and oscillatory transients. Building a standard EMT simulation platform library component for easy configuration and application.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Parametric study of solid-solid translucent phase change materials in building windows

Thermal energy storage and solar radiation management are crucial to improve the sustainability and energy efficiency of buildings. Compared with the implementation of phase change materials (PCMs) in opaque components, the energy saving potential of incorporating PCMs in transparent glazing windows is much less studied and not well understood. Here we present a comprehensive parametric study of novel PCM windows for building energy saving with a focus on optimizing and quantitatively distinguishing the contributions from the optical and thermal properties of the PCM, which is particularly useful for the design of solid-solid PCM windows. We investigate a reference commercial office building using EnergyPlus by developing an equivalent model of our PCM window that is compatible with EnergyPlus's modeling capabilities. Compared with a clear-clear double-pane window, the integration of 3 mm solid-solid PCMs with optimal properties in warm, mixed, and cold climates can respectively save up to 17.2%, 14.0%, and 5.8% energy for the HVAC (heating, ventilation, and air conditioning) system, and 9.4%, 6.7%, and 3.2% energy for the whole building. We also demonstrate that these energy savings are most sensitive to the solar absorptance of PCMs for all three climates. The optimal transition temperature varies with climate and is related to the climate and solar radiation heat gain. Other issues are also briefly discussed, such as hysteresis, window orientations, and the effect of interior lighting. Finally, although the optimal PCM windows show energy saving performance comparable with low-emissivity windows, the PCM windows provide a unique advantage in terms of shifting HVAC loads which can provide benefits to the electrical grid.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A Comparison

The replacement of classical force fields (FFs) with novel neural-network-based frameworks is an emergent topic in molecular dynamics (MD) simulations. In contrast to classical FFs, which have proven their capability to provide insights into complex soft matter systems at an atomistic resolution, the machine learning (ML) potentials have yet to demonstrate their applicability for soft materials. However, the underlying philosophy, which is learning the energy of an atom in its surrounding chemical environment, makes this approach a promising tool. In particular for the exploration of novel chemical compounds, which have not been considered in the original parametrization of classical FFs. In this article, we study the performance of the ANI-2x ML model and compare the results with those of two classical FFs, namely, CHARMM27 and the GROMOS96 43a1 FF. We explore the performance of these FFs for bulk water and two model peptides, trialanine and a 9-mer of the α-aminoisobutyric acid, in vacuum and water. The results for water describe a highly ordered water structure, with a structure similar to those using ab initio molecular dynamics simulations. The energy landscape of the peptides described by Ramachandran maps show secondary structure basins similar to those of the classical FFs but differ in the position and relative stability of the basins. Details of the sampled structures show a divergent performance of the different models, which can be related either to the short-ranged nature of the ML potentials or to shortcomings of the underlying data set used for training. These findings highlight the current state of the applicability of ANI-2x ML potential for MD simulations of soft matter systems. Simultaneously, they provide insights for future improvements of current ML potentials.

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

Amplification of mid-IR continuum for broadband 2D IR spectroscopy

We report the generation and characterization of microjoule level, broad bandwidth femtosecond pulses in the mid-infrared (MIR) using optical parametric amplification of continuum MIR seed pulses in GaSe. The signal (3 μm) and idler (6 μm) pulses have energies of 6 μJ and 3 μJ with bandwidths of ∼950 cm −1 and 650 cm −1 FWHM and pulse lengths of 34 fs and 80 fs. Broadband 2D IR spectra of O-H and N-H transitions are acquired with the signal beam demonstrating the capabilities of this source for cross peak and line shape measurements.

Optics↗
DOE OSTI2026

Predicted third-order sweet spots for phi-junction Josephson parametric amplifiers

Hybrid superconductor-semiconductor nanowire Josephson junctions exhibit skewed and phi-shifted current phase relations when an in-plane magnetic field is applied along the weak link's spin-orbit effective field direction. These junctions can have an asymmetric Josephson potential with odd-order nonlinearities. A dominant third-order nonlinearity can be achieved by tuning the magnetic field to a sweet spot. Sweet spots persist when higher order Josephson harmonics are included. This makes it possible to have a single Josephson junction dipole element with three-wave mixing capability, which is favorable for pump-efficient amplification. Electrostatic gate tunability of the semiconductor weak link can make it operable within an extended range of working frequencies, and the inclusion of micromagnets can facilitate near-zero magnetic field operation.

Reza, Tasnum [Univ. of Pittsburgh, PA (United Stat↗
DOE OSTI2020

Modeling of fluid injection-induced fault reactivation using coupled fluid flow and mechanical interface model

The present study is aimed at developing a numerical model to reproduce coupled hydro-mechanical processes associated with fault reactivation by fluid injection in low permeability rock, as part of the DECOVALEX-2019 project Task B. We proposed a modeling approach for simulating the processes using the TOUGH-FLAC simulator, and modeled a fault reactivation experiment conducted at Mont Terri Rock Laboratory in Switzerland. The first step of the study involved benchmark calculations considering a simplified fault plane and geometry. Fluid flow along a fault was modeled using elements of aperture-sized thickness on the basis of Darcy's law and the cubic law in TOUGH2, whereas the mechanical behavior of a single fault was represented by zero-thickness interface elements in FLAC3D upon which a slip and/or separation is allowed. A methodology to connect a TOUGH2 volume element to a FLAC3D interface element was developed for handling the hydro-mechanical interactions on the fault during fluid injection. Two different fault models for describing the evolutions of hydraulic aperture by elastic fracture opening and failure-induced aperture increase were considered in the benchmark calculations. In the coupling process, the changes in geometrical features and hydrological properties induced by mechanical deformation were continuously updated. The transient responses of the fault and host rock to stepwise pressurization were examined during the simulation. The hydro-mechanical behavior, including the injection flow rate, pressure distribution around the borehole, stress conditions, and displacements in normal and shear directions were monitored in the surrounding rock and along the fault. The results of benchmark calculations suggest that the developed model reasonably represents the hydro-mechanical behavior of a fault and the surrounding rock. This modeling approach was applied to the fault reactivation experiment of the Mont Terri Rock Laboratory. In this interpretive modeling, a parametric study was conducted to examine the effects of input parameters regarding in situ stress and fault properties on the hydro-mechanical responses of the fault to water injection. Then, an optimal parameter set to reproduce the field experiment results was chosen by trial-and-error. The injection flow rate and pressure response during fault reactivation closely matched those obtained at the site, which indicates the capability of the model to appropriately capture the progressive pathway evolution during fault reactivation tests at the site. Finally, the anchor displacements were overestimated by the model, but a fair agreement was obtained in terms of the order of magnitude and the variation tendency.

58 GEOSCIENCES↗
DOE OSTI2024

SPH Modeling of Biomass Granular Flow: Engineering Application in Hoppers and Augers

Numerical modeling of granular biomass material flow in handling operations is indispensable to decipher flow upsets, commonly manifested as clogging and jamming in hoppers and augers. With a computational tool developed based on smoothed particle hydrodynamics (SPH), we simulated the hopper flow and auger feeding of six granular biomass materials. The good agreement between the experimental and numerical flow rates demonstrated the capability of the developed SPH solver in modeling the complicated flow of granular biomass materials. Further, the impact of physical and numerical parameters is investigated, and the major results show that the hopper flow pattern is controlled by shear band evolution; hopper clogging is collectively influenced by the opening size, wall friction, and material packing, and the impact of material compressibility on the auger feed rate is minimal. These parametric studies validate the solver’s robustness in simulating biomass flow in handling equipment and demonstrate that the SPH computational tool can provide insights about granular flow mechanics to facilitate handling equipment design and optimize handling operations.

09 BIOMASS FUELS↗
DOE OSTI2023

Coupled magnetostructural continuum model for multiferroic BiFeO 3

Here, a continuum approach to study magnetoelectric multiferroic BiFeO 3 (BFO) is proposed. Our modeling effort marries the ferroelectric (FE) phase field method and micromagnetic simulations to describe the entire multiferroic order parameter sector (polarization, oxygen antiphase tilts, strain, and magnetism) self-consistently on the same time- and length scale. In this paper, we discuss our choice of FE and magnetic energy terms and demonstrate benchmarks against known behavior. We parametrize the lowest order couplings of the structural distortions against previous predictions from density functional theory calculations giving access to simulations of the FE domain wall (DW) topology. This allows us to estimate the energetic hierarchy and thicknesses of the numerous structural DWs. We then extend the model to the canted antiferromagnetic order and demonstrate how the FE domain boundaries influence the resulting magnetic DWs. We also highlight some capabilities of this model by providing two examples relevant for applications. We demonstrate spin-wave transmission through the multiferroic domain boundaries which identify rectification in qualitative agreement with recent experimental observations. As a second example of application, we model fully dynamical magnetoelectric switching, where we find a sensitivity on the Gilbert damping with respect to switching pathways. We envision that this modeling effort will set the basis for further work on properties of arbitrary 3D nanostructures of BFO (and related multiferroics) at the mesoscale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Many-Body Physics in the NISQ Era: Quantum Programming a Discrete Time Crystal

Recent progress in the realm of noisy intermediate-scale quantum (NISQ) devices represents an exciting opportunity for many-body physics by introducing new laboratory platforms with unprecedented control and measurement capabilities. We explore the implications of NISQ platforms for many-body physics in a practical sense: we ask which physical phenomena, in the domain of quantum statistical mechanics, they may realize more readily than traditional experimental platforms. While a universal quantum computer can simulate any system, the eponymous noise inherent to NISQ devices practically favors certain simulation tasks over others in the near term. As a particularly well-suited target, we identify discrete time crystals (DTCs), novel nonequilibrium states of matter that break time translation symmetry. These can only be realized in the intrinsically out-of-equilibrium setting of periodically driven quantum systems stabilized by disorder-induced many-body localization. While promising precursors of the DTC have been observed across a variety of experimental platforms—ranging from trapped ions to nitrogen-vacancy centers to NMR crystals—none have all the necessary ingredients for realizing a fully fledged incarnation of this phase, and for detecting its signature long-range spatiotemporal order. We show that a new generation of quantum simulators can be programmed to realize the DTC phase and to experimentally detect its dynamical properties, a task requiring extensive capabilities for programmability, initialization, and readout. Specifically, the architecture of Google’s Sycamore processor is a remarkably close match for the task at hand. We also discuss the effects of environmental decoherence, and how they can be distinguished from ‘internal’ decoherence coming from closed-system thermalization dynamics. Already with existing technology and noise levels, we find that DTC spatiotemporal order would be observable over hundreds of periods, with parametric improvements to come as the hardware advances.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Optimal Power Sharing Speed Compensation in On-road Wireless EV Charging Systems

Dynamic wireless charging of electric vehicles (EV) is an emerging technology with the potential to address range anxiety and reduce the size of batteries or provide charge-sustaining operation. Charging demand for dynamic wireless charging systems (DWCS) varies greatly in response to location-specific traffic behaviors including the number and speed of vehicles. This paper highlights the potential reduction of load variation with speed compensation and simulates opportunities to maximize the number of cars charged concurrently through “power sharing” or altering power output to slower cars while maintaining a maximum delivered energy. An improved sub-minute model for synthetic traffic is proposed to effectively model DWCS load on high speed roadways and a power electronics model is created based on an existing prototype developed by ORNL to investigate the potential for power sharing. Reductions in the average speed of traffic can greatly increase instantaneous DWCS load by as much as 26%, complicating capacity sizing. Parametric studies with a LCC-S power electronics model shows feasible power reduction of more than 20%, while maintaining a maximum achievable efficiency greater than 90%. Speed compensation on a roadway with large speed variation can reduce average power expected by 21% and increase the maximum number of cars charged simultaneously by 30%. The application of power sharing may significantly reduce load variability due to speed, allow for increased car hosting capability, and guarantee a maximum energy delivered.

Lewis, Donovin D.↗
DOE OSTI2022

Random quasi-phase-matching for pulse characterization from the near to the long wavelength infrared

Experiments requiring ultrafast laser pulses require a full characterization of the electric field to glean meaning from the experimental data. Such characterization typically requires a separate parametric optical process. As the central wavelength range of new sources continues to increase so too does the need for nonlinear crystals suited for characterizing these wavelengths. Here we report on the use of poly-crystalline zinc selenide as a universal nonlinear crystal in the frequency resolved optical gating characterization technique from the near to long-wavelength infrared. Due to its property of random quasi-phase-matching it’s capable of phase matching second-harmonic and sum-frequency generation of ultra-broadband pulses in the near and long wavelength infrared, while being crystal orientation independent. With the majority of ultra-fast laser sources being in this span of wavelengths, this work demonstrates a greatly simplified approach towards ultra-fast pulse characterization spanning from the near to the long-wavelength infrared. To our knowledge there is no single optical technique capable of such flexible capabilities.

Davis, Brandin (ORCID:0000000166964548)↗
DOE OSTI2023

Genomic materials design: CALculation of PHAse Dynamics

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. Here, as first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new “materials concurrency” integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-repetition rate, CEP-stable shortwave infrared source with two-cycle pulses for field-resolved spectroscopy

We report on a passively carrier-envelope phase (CEP)-stable optical parametric amplifier generating two-cycle pulses at 2060 nm with energies of up to 2.25 µJ operating at a repetition rate of 400 kHz, specifically designed for applications in field-resolved spectroscopy. The measured pulse duration is 13.6 fs, resulting in two cycles of the carrier wave. Due to the robust CEP-stable front-end design, we achieve an open-loop CEP stability of 250 mrad (rms) and the capability for fast CEP modulation.

47 OTHER INSTRUMENTATION↗