Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “statistical thermodynamics”

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 163 records · Page 9

Time-reversal symmetry breaking in two-dimensional nonequilibrium viscous fluids

In this work, we study the rheological signatures of departure from equilibrium in two-dimensional viscous fluids with and without internal spin. Under the assumption of isotropy, we provide the most general linear constitutive relations for stress and couple stress in terms of the velocity and spin fields. Invoking Onsager's regression hypothesis for fluctuations about steady states, we derive the Green-Kubo formulas relating the transport coefficients to time-correlation functions of the fluctuating stress. In doing so, we show that one of the nonequilibrium transport coefficients, the odd viscosity, requires time-reversal symmetry breaking in the case of systems without internal spin. However, the Green-Kubo relations for systems with internal spin also show that there is a possibility for nonvanishing odd viscosity even when time-reversal symmetry is preserved. Furthermore, we find that breakdown of equipartition in nonequilibrium steady states results in the decoupling of the two rotational viscosities relating the vorticity and the internal spin.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Approximate 𝑡-Designs in Generic Circuit Architectures

Unitary 𝑡-designs are distributions on the unitary group whose first 𝑡 moments appear maximally random. Previous work has established several upper bounds on the depths at which certain specific random quantum circuit ensembles approximate 𝑡-designs. Here we show that these bounds can be extended to any fixed architecture of Haar-random two-site gates. This is accomplished by relating the spectral gaps of such architectures to those of one-dimensional brickwork architectures. Our bound depends on the details of the architecture only via the typical number of layers needed for a block of the circuit to form a connected graph over the sites. When this quantity is bounded, the circuit forms an approximate 𝑡-design in at most linear depth. We give numerical evidence for a stronger bound that depends only on the number of connected blocks into which the architecture can be divided. We also give an implicit bound for nondeterministic architectures in terms of properties of the corresponding distribution over fixed architectures.

information scrambling↗

Light element ($$Z=1,2$$) production from spontaneous ternary fission of $$^{252}$$Cf

Abstract The yields of light elements ( $$Z=1,2$$ Z = 1 , 2 ) obtained from spontaneous ternary fission of $$^{252}$$ 252 Cf are treated within a nonequilibrium approach, and the contribution of unstable nuclei and excited bound states is taken into account. These light cluster yields may be used to probe dense matter, and to infer in-medium corrections such as Pauli blocking which is determined by the nucleon density. Continuum correlations are calculated from scattering phase shifts using the Beth-Uhlenbeck formula, and the effect of medium modification is estimated. The relevant distribution is reconstructed from the measured yields of isotopes. This describes the state of the nucleon system at scission and cluster formation, using only three Lagrange parameters which are the nonequilibrium counterparts of the temperature and chemical potentials, as defined in thermodynamic equilibrium. We concluded that a simple nuclear statistical equilibrium model neglecting continuum correlations and medium effects is not able to describe the measured distribution of H and He isotopes. Moreover, the freeze-out concept may serve as an important ingredient to the nonequilibrium approach using the relevant statistical operator concept.

Röpke, G.↗

Entanglement features of random neural network quantum states

Restricted Boltzmann machines (RBMs) are a class of neural networks that have been successfully employed as a variational ansatz for quantum many-body wave functions. Here, we develop an analytic method to study quantum many-body spin states encoded by random RBMs with independent and identically distributed complex Gaussian weights. By mapping the computation of ensemble-averaged quantities to statistical mechanics models, we are able to investigate the parameter space of the RBM ensemble in the thermodynamic limit. We discover qualitatively distinct wave functions by varying RBM parameters, which correspond to distinct phases in the equivalent statistical mechanics model. Notably, there is a regime in which the typical RBM states have near-maximal entanglement entropy in the thermodynamic limit, similar to that of Haar-random states. However, these states generically exhibit nonergodic behavior in the Ising basis, and do not form quantum state designs, making them distinguishable from Haar-random states.

36 MATERIALS SCIENCE↗

Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine

Here, we analyze a steady-state thermoelectric engine, whose working substance consists of two capacitively coupled quantum dots. One dot is tunnel-coupled to a hot reservoir serving as a heat source, the other one to two electrically biased reservoirs at a colder temperature, such that work is extracted under the form of a steady-state current against the bias. In single realizations of the dynamics of this steady-state engine autonomous, four-stroke cycles can be identified. The cycles are purely stochastic, in contrast to mechanical autonomous engines which exhibit self-oscillations. In particular, these cycles fluctuate in direction and duration and occur in competition with other spurious cycles. Using a stochastic thermodynamic approach, we quantify the cycle fluctuations and relate them to the entropy produced during individual cycles. We identify the cycle mainly responsible for the engine performance and quantify its statistics with tools from graph theory. We show that such stochastic cycles are made possible because the work extraction mechanism is itself stochastic instead of the periodic time dependence in the working-substance Hamiltonian which can be found in conventional mechanical engines. Our investigation brings new perspectives about the connection between cyclic and steady-state engines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development and Validation of Physics-Based Sub-Models of High-Pressure Supercritical Fuel Injection at Diesel Conditions Insert

The project sought to develop and validate accurate, physics-based, numerical submodels and implement them in computational fluid dynamics (CFD) software codes to enable accurate predictions of diesel sprays at pressures higher than the current systems. The combined experimental-computational effort has four main objectives: (1) acquire spatially and temporally resolved scalar measurements of fuel-oxidizer mixing in the near field of the fuel jet, (2) develop software modules to calculate thermo-physical properties of diesel surrogates and their mixtures with oxidizer of interest in real-gas operating regime, (3) integrate the real-fluid model into a commercial and an open-source CFD code to simulate fuel-air mixing in high-pressure diesel sprays, and (4) assess the robustness, accuracy, and uncertainty of the integrated CFD solvers in computing diesel sprays. Project accomplishments are consistent with the original goals of the project. Although we acquired spatially and temporally resolved scalar measurements, they were limited to refractive index difference and not to thermodynamic properties such as temperature and equivalence ratio. However, we successfully developed the theoretical background needed to acquire such measurements at diesel conditions and demonstrated the capability of the RSD for scalar measurements in a canonical turbulent jet flow replicating features of the diesel jet. Additional work will be needed to implement these procedures at high-pressure, high-temperature engine-like conditions of the CPFR. Mainly, we did not anticipate the need to find the liquid boundary and its statistical features or the state relationships between refractive index and thermodynamic properties, assuming the widely known Dale-Gladstone equation would suffice. Still, efforts devoted to these tasks were essential to fulfil the goals of the project and serves as the foundation on which many of the conclusions and key contributions of this project are based. Further assessment and application of the developed CFD codes is recommended to fully realize the benefits of this research.

33 ADVANCED PROPULSION SYSTEMS↗

A collision operator for describing dissipation in noncanonical phase space

The phase space of a noncanonical Hamiltonian system is partially inaccessible due to dynamical constraints (Casimir invariants) arising from the kernel of the Poisson tensor. When an ensemble of noncanonical Hamiltonian systems is allowed to interact, dissipative processes eventually break the phase space constraints, resulting in a thermodynamic equilibrium described by a Maxwell–Boltzmann distribution. However, the time scale required to reach Maxwell–Boltzmann statistics is often much longer than the time scale over which a given system achieves a state of thermal equilibrium. Examples include diffusion in rigid mechanical systems, as well as collisionless relaxation in magnetized plasmas and stellar systems, where the interval between binary Coulomb or gravitational collisions can be longer than the time scale over which stable structures are self-organized. Here, we focus on self-organizing phenomena over spacetime scales such that particle interactions respect the noncanonical Hamiltonian structure, but yet act to create a state of thermodynamic equilibrium. We derive a collision operator for general noncanonical Hamiltonian systems, applicable to fast, localized interactions. This collision operator depends on the interaction exchanged by colliding particles and on the Poisson tensor encoding the noncanonical phase space structure, is consistent with entropy growth and conservation of particle number and energy, preserves the interior Casimir invariants, reduces to the Landau collision operator in the limit of grazing binary Coulomb collisions in canonical phase space, and exhibits a metriplectic structure. We further show how thermodynamic equilibria depart from Maxwell–Boltzmann statistics due to the noncanonical phase space structure, and how self-organization and collisionless relaxation in magnetized plasmas and stellar systems can be described through the derived collision operator.

Boltzmann equation↗

Unified bulk semiclassical theory for intrinsic thermal transport and magnetization currents

In this work, we reveal the unexpected role of the material inhomogeneity in unifying the formulation of intrinsic thermal and thermoelectric transport as well as magnetization currents. The smooth inhomogeneity leads to the position dependent local band dispersion and phase-space Berry curvature, enabling a general and rapid access to transport and magnetization currents displaying the momentum-space Berry curvature physics. Our theory does not invoke the boundary current, the thermodynamic approach to magnetization or any mechanical counterpart of statistical forces. By introducing a fictitious inhomogeneity, it applies to homogeneous samples as well, promoting the inhomogeneity to be a basic trick in semiclassical transport theories. Such a trick works regardless of the driving force of transport, e.g., temperature gradient, in contrast to the trick of fictitious gravitational field in quantum transport theories. We thus include more general mechanical driving forces and establish the Mott relation between the resulting transport thermal and electric currents, whereas this relation for these two currents was previously only known when an electric field is the driving force.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nonlinear Topological Photonics: Capturing Nonlinear Dynamics and Optical Thermodynamics

Combining multiple optical resonators or engineering dispersion of complex media has provided an effective method for demonstrating topological physics controlling photons in unprecedented ways such as unidirectional light propagation and spatially localized modes between an interface or on a corner. Further, adding nonlinear responses to those topological photonic systems has enabled achieving diverse phases of photons in both space and time, allowing for more functionalities in photonic devices that provide a new playground for studying dynamic features of nonlinear topological systems. However, most methods for describing nonlinear topological photonic systems rely on linear topological theories, making it challenging to accurately characterize the topology of nonlinear systems. Thus, substantial efforts have focused on rigorously describing nonlinear topological phases and developing effective tools to analyze nonlinear topological effects. Meanwhile, coupled multimode optical waveguides with nonlinear dynamic responses provide an excellent platform for the statistical description of photons, opening a new paradigm called “optical thermodynamics”. This review will introduce the basic concepts of nonlinear topological photonics and the recent development of theoretical approaches focusing on data-driven approaches for creating phase diagrams as well as the spectral localizer framework and the pseudospectrum method for understanding optical nonlinearities in topological systems. In addition, the new concept of optical thermodynamics will be introduced with some recent theoretical works.

Topological photonics↗

The statistical mechanics of near-BPS black holes

Due to the failure of thermodynamics for low temperature near-extremal black holes, it has long been conjectured that a 'thermodynamic mass gap' exists between an extremal black hole and the lightest near-extremal state. For non-supersymmetric near-extremal black holes in Einstein gravity with an AdS2 throat, no such gap was found. Rather, at that energy scale, the spectrum exhibits a continuum of states, up to non-perturbative corrections. In this paper, we compute the partition function of near-BPS black holes in supergravity where the emergent, broken, symmetry is PSU(1, 1|2). To reliably compute this partition function, we show that the gravitational path integral can be reduced to that of a $\mathcal{N}=4$ supersymmetric extension of the Schwarzian theory, which we define and exactly quantize. In contrast to the non-supersymmetric case, we find that black holes in supergravity have a mass gap and a large extremal black hole degeneracy consistent with the Bekenstein–Hawking area. Furthermore, our results verify a plethora of string theory conjectures, concerning the scale of the mass gap and the counting of extremal micro-states.

79 ASTRONOMY AND ASTROPHYSICS↗

Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degrees of freedom

The emergence of scanning probe and electron beam imaging techniques has allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic descriptors, in turn, can be associated with local symmetry breaking phenomena, representing the stochastic manifestation of the underpinning generative physical model. In this work, we explore the reconstruction of exchange integrals in the Hamiltonian for a lattice model with two competing interactions from observations of microscopic degrees of freedom and establish the uncertainties and reliability of such analysis in a broad parameter-temperature space. In contrast to other approaches, we specifically specify a loss function inherent to thermodynamic systems and utilize it to estimate uncertainty in simulated realizations of different models. As an ancillary task, we develop a machine learning approach based on histogram clustering to predict phase diagrams efficiently using a reduced descriptor space. We further demonstrate that reconstruction is possible well above the phase transition and in the regions of parameter space when the macroscopic ground state of the system is poorly defined due to frustrated interactions. This suggests that this approach can be applied to the traditionally complex problems of condensed matter physics such as ferroelectric relaxors and morphotropic phase boundary systems, spin and cluster glasses, and quantum systems once the local descriptors linked to the relevant physical behaviors are known.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Atomic-scale mechanism of carbon nucleation from a deep crustal fluid by replica exchange reactive molecular dynamics simulation

Here we present a mechanistic model of carbon nucleation and growth from a fluid at elevated temperature (T) and pressure conditions, typical of those found in the shallow Earth’s lithosphere. Our model uses a replica exchange reactive molecular dynamics framework in which molecular configurations are swapped between adjacent T replica at regular intervals according to underlying statistical mechanics. This framework allows predicting complex molecular structures and thermodynamics while remaining computationally efficient. Here we simulate the reactivity of an unstable mixture of CO 2 and CH 4 at 1000 K and 1 GPa. We find that the path to thermodynamic equilibrium is initially entropy-driven, producing a diversity of short-lived species, including various alcohols with intermediate carbon oxidation states. Cyclic and polycyclic radicals that are sometimes resonance-stabilized form next and set the stage for carbon nucleation. The carbon exsolution process releases abundant water, is exothermic and starts with the nucleation of a large aggregate of hydrogenated graphene flakes from covalently bonded polycyclic units. The carbon backbone of this nucleus subsequently grows into a hydrogen-depleted fullerene-like structure, before evolving toward a partially bilayered graphene layer. Overall, our results show that the mechanism of graphitic C formation is certainly not bimolecular, and that it may involve a combination of key condensation and radical chain reactions. This will help understand the isotopic, and reactive characteristics of carbon-bearing fluids during their upward transit through the Earth’s mantle and crust. Moreover, the mechanistic insights outlined here present intriguing similarities with the process of soot and interstellar dust formation, which suggests that the widespread distribution of abiotic polyaromatic and graphitic material on Earth and beyond may reflect the prevalence of a fundamental chemical pathway.

58 GEOSCIENCES↗

Free-energy estimates from nonequilibrium trajectories under varying-temperature protocols

The Jarzynski equality allows the calculation of free-energy differences using values of work measured from nonequilibrium trajectories. The number of trajectories required to accurately estimate free-energy differences in this way grows sharply with the size of work fluctuations, motivating the search for protocols that perform desired transformations with minimum work. However, protocols of this nature can involve varying temperature, to which the Jarzynski equality does not apply. Here, we derive a variant of the Jarzynski equality that applies to varying-temperature protocols, and show that it can have better convergence properties than the standard version of the equality. We derive this modified equality and the associated fluctuation relation within the framework of Markovian stochastic dynamics, complementing related derivations done within the framework of Hamiltonian dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗

Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning

Calculating thermodynamic potentials and observables efficiently and accurately is key for the application of statistical mechanics simulations to materials science. However, naive Monte Carlo approaches, on which such calculations are often dependent, struggle to scale to complex materials in many state-of-the-art disciplines such as the design of high entropy alloys or multi-component catalysts. To address this issue, we adapt sampling tools built upon machine learning-based generative modeling to the materials space by transforming them into the semi-grand canonical ensemble. Furthermore, we show that the resulting models are transferable across wide ranges of thermodynamic conditions and can be implemented with any internal energy model U, allowing integration into many existing materials workflows. We demonstrate the applicability of this approach to the simulation of benchmark systems (AgPd, CuAu) that exhibit diverse thermodynamic behavior in their phase diagrams. Finally, we discuss remaining challenges in model development and promising research directions for future improvements.

36 MATERIALS SCIENCE↗

Determination of a most representative cycle from cylinder pressure ensembles via statistical method using distribution skewness

In internal combustion engine research, cylinder pressure measurements provide valuable information about the underlying thermodynamic and combustion processes, and are typically collected in ensembles of several 100 traces. Although in some particular fields of combustion research all traces are analyzed, in most cases only one trace is studied because analyzing all the traces is impractical due to the large number of collected samples. Instead, an ensemble-averaged pressure trace is commonly calculated and used for analysis. However, this pressure trace is highly smoothed and dynamic information is lost during the averaging process. With the average trace, pressure rise rates are lower and pressure oscillations such as the ones resulting from combustion knock are lost. In this work, a statistical method was developed to determine the “most representative cycle,” which is the cycle from the ensemble that has the pressure trace most representative of the engine operating condition. Eleven characteristic parameters are computed from each pressure trace and probabilistic distributions are obtained for each of the parameters using all the traces in the ensemble. Finally, the most representative cycle is selected by means of a cost function minimization. The benefits of this method are illustrated using experimental data from four very different engine platforms, under four different combustion modes and over a range of operating conditions.

42 ENGINEERING↗

Thermal transport exceeding bulk heat conduction due to nonthermal micro/nanoscale phonon populations

While classical size effects usually lead to a reduced effective thermal conductivity, we report here that nonthermal phonon populations produced by a micro/nanoscale heat source can lead to enhanced heat conduction, exceeding the prediction from Fourier's law. We study nondiffusive thermal transport by phonons at small distances within the framework of the Boltzmann transport equation (BTE) and demonstrate that the transport is significantly affected by the distribution of phonons emitted by the source. We discuss analytical solutions of the steady-state BTE for a source with a sinusoidal spatial profile, as well as for a three-dimensional Gaussian “hot spot,” and provide numerical results for single crystal silicon at room temperature. If a micro/nanoscale heat source produces a thermal phonon distribution, it gets hotter than that predicted by the heat diffusion equation; however, if the source predominantly produces low-frequency acoustic phonons with long mean free paths, it may get significantly cooler than that predicted by the heat equation, yielding an enhanced heat transport beyond bulk heat conduction.

42 ENGINEERING↗