Thermodynamic State Research Articles

Nonideal Compressible Fluid Dynamics of Dense Vapors and Supercritical Fluids

The gas dynamics of single-phase nonreacting fluids whose thermodynamic states are close to vapor-liquid saturation, close to the vapor-liquid critical point, or in supercritical conditions differs quantitatively and qualitatively from the textbook gas dynamics of dilute, ideal gases. Due to nonideal fluid thermodynamic properties, unconventional gas dynamic effects are possible, including nonclassical rarefaction shock waves and the nonmonotonic variation of the Mach number along steady isentropic expansions. This review provides a comprehensive theoretical framework of the fundamentals of nonideal compressible fluid dynamics (NICFD). The relation between nonideal gas dynamics and the complexity of the fluid molecules is clarified. The theoretical, numerical, and experimental tools currently employed to investigate NICFD flows and related applications are reviewed, followed by an overview of industrial processes involving NICFD, ranging from organic Rankine and supercritical CO2 cycle power systems to supercritical processes. The future challenges facing researchers in the field are briefly outlined.

Experimental and numerical investigations on the microstructural features and mechanical properties of explosively welded aluminum/titanium/steel trimetallic plate

In this paper, 3A21Al/TA1/CCSB composite plate was fabricated successfully by explosive welding to improve the bond strength. The microstructure characteristics of aluminum/titanium and titanium/steel bonding interfaces were systematically investigated by two-step numerical simulation and SEM/EBSD characterizations. Firstly, the SPH (Smoothed Particle Hydrodynamics) and Lagrange methodology were used to simulate and calculate the collision velocity and collision angle, establishing an accurate impact condition. Secondly, the SPH model was used to simulate the high-speed oblique impact welding process. The simulation results reproduce the formation of wavy interface, vortex zone and jet, which are consistent with the experimental results. Combined with SEM, EBSD, and EDS analysis, continuous and uniform wavy structures were found at different interfaces of the composite plate, showing significantly different wave lengths and amplitudes. Dynamic recovery and recrystallization took place at the bonding interfaces which showed refined grain with different preferred orientations. The observed structural characteristics and the thermodynamic state predicted by SPH simulation inferred the evolutions of microstructures (including morphologies, micro defects, grain structures). The tensile strength and fracture elongation of the trimetallic plate reach 448.2 MPa and 14.15%, respectively. In addition, the shear strengths of each interface far exceed the corresponding acceptable standard values.

Influence of the Type of Biocompatible Polymer in the Shell of Magnetite Nanoparticles on Their Interaction with DPPC in Two-Component Langmuir Monolayers.

Magnetite nanoparticles (MNPs) are attractive nanomaterials for applications in magnetic resonance imaging, targeted drug delivery, and anticancer therapy due to their unique properties such as nontoxicity, wide chemical affinity, and intrinsic superparamagnetism. Their functionalization with polymers such as chitosan or poly(vinyl alcohol) (PVA) can not only improve their biocompatibility and biodegradability but it also plays an important role in their interactions with biological cells. In this work, the effect of the functionalization of MNPs with chitosan, PVA, and their blend on model cell membranes formed from 1,2-dipalmitoyl-sn-glycerol-3-phosphocholine (DPPC) using a Langmuir technique was studied. The studies performed showed that the type of biocompatible polymer in the MNP shell plays a crucial role in the effectiveness of its adsorption process into the model cell membrane. Modification of MNPs with chitosan facilitates significantly more effective adsorption than coating them with PVA or with a chitosan and PVA blend. The presence of all the investigated MNPs in the DPPC monolayer at low concentrations does not affect its thermodynamic state, fluidity, or morphology, which is promising in terms of their biocompatibility. On the other hand, their high concentration (molar fraction above ≈0.05) exerts a disruptive effect on the model cell membrane and results in their aggregation, leading probably to the loss of their superparamagnetic properties essential for nanomedicine.

Coupling transport equations to mechanics in the material point method using an approximate full capacity matrix inverse

Coupling solutions of one or more transport equations to mechanics modeling in the material point method (MPM), extends MPM to a platform for solving multi-physics problems. Unfortunately, the standard MPM approach to transport equations using a lumped transport capacity matrix is prone to large oscillations in particle values especially near interfaces, cracks, or rapid changes in transport value. Switching from lumped capacity matrix methods to an approximate full capacity matrix approach can eliminate those oscillations. Although this switch can cause unwanted numerical diffusion, that problem can be suppressed using periodic or blending options. Several examples illustrate the new methods for heat conduction, solvent transport, poroelasticity, and phase field fracture simulations. In thermal calculations, the new methods improve accuracy for tracking thermodynamics state functions.

Numerical investigation on turbulent flame jet characteristics of a pre-chamber fueled with CH4/O2 and CH4/NH3/O2 mixture under different initial pressures

Ammonia is a very potential carbon-free alternative fuel with extremely low reactivity. The application of ammonia in internal combustion engines faces the risks of ignition failure, low burning rate, and poor combustion stability. Pre-chamber turbulent jet ignition (TJI), which can provide much more ignition energy, is a promising method to ignite ammonia fuel. However, the transient propagation process of pre-chamber jet flame has not been fully investigated yet. In this paper, the propagation characteristic of methane jet flame was numerically studied based on a constant volume combustion system. The supersonic jet flame propagation and Mach disk phenomenon were further analyzed with numerical methods. And the propagation characteristic of methane/ammonia mixed jet flame was investigated. According to the results, the formation and propagation process of methane jet flame has different characteristics at different stages. In High-speed development stage (Stage II) and Low-speed oscillation development stage (Stage III), the penetration distance of flame jet tip is almost proportional to the penetration time. However, the penetration speed of the two stages is significantly different. The change trend of the jet velocity at the outlet of orifice hole can also be divided into four stages: slow increasing, rapid increasing, gradual decreasing, and periodic oscillation. The periodic oscillation of the jet tip velocity and the jet velocity at the outlet of orifice hole is caused by the effect of forward and reverse shock waves. The calculation results of CH4/NH3/O2 mixture jet flame show that the addition of ammonia has significant effects on the flame propagation process in PC, the thermodynamic state of PC, and the propagation characteristics of jet flame. With the increase of ammonia proportion, the maximum pressure of PC gradually decreases and the pressure rise rate slows down. Meanwhile, the two-stage (the high-speed development stage and the low-speed development stage) characteristic of jet propagation process gradually disappears. And the addition of ammonia is more likely to destroy the two-stage characteristic under low initial pressure.

Application of absorption-line blackbody distribution functions for H2O-CO2 mixtures for the spectral integration of the radiative transfer equation with the SLW model

This study presents the generation and evaluation of absorption-line blackbody distribution functions for mixtures (ALBDF-M) of CO2 and H2O. These functions are employed in the spectral integration of the radiative transfer equation in the framework of the spectral line-based weighted-sum-of-gray-gases (SLW) model. The proposed approach avoids the need to model the mixture of gases when dealing with ALBDFs obtained for pure H2O and CO2 species, which is the methodology currently adopted in the SLW literature. The ALBDF-M can be used with any development of the SLW model to manage local variations of the thermodynamic state conditions. In the present study, both the rank (RC-) and the locally correlated (LC-) SLW methodologies are employed with the ALBDF-M for an uncouple solution of an axisymmetric field that is representative of the combustion of ethylene diluted with H2O. Comparisons with line-by-line (LBL) solutions show that using the ALBDF-M provides an improvement in the accuracy when compared to the standard methodology to combine the ALBDFs generated for CO2 and H2O individually.

Consistent Coupling of Compressibility Effects in Manifold-Based Models for Supersonic Combustion

Manifold-based models are an efficient modeling framework for turbulent combustion but, in their basic formulation, do not account for the compressibility effects of high-speed flows. To include the effects of compressibility, ad hoc corrections have been proposed but result in an inconsistent thermodynamic state between the manifold and flow simulation. In this work, an iterative algorithm to consistently incorporate compressibility effects into manifold-based models is developed. The manifold inputs (fuel and oxidizer temperatures and pressure) are determined iteratively to reflect the nonnegligible variations in thermodynamic state (expressed in terms of density and internal energy in flow simulations) that are characteristic of supersonic combustion. The algorithm is demonstrated on data from simulations of high-speed reacting mixing layers and is significantly more accurate than established approaches that only partially couple the manifold in compressible flow simulations. The proposed approach eliminates partial coupling approximation errors in excess of 10 and 20% for temperature and water source term.

Learning thermodynamically constrained equations of state with uncertainty

Numerical simulations of high energy-density experiments require equation of state (EOS) models that relate a material’s thermodynamic state variables—specifically pressure, volume/density, energy, and temperature. EOS models are typically constructed using a semi-empirical parametric methodology, which assumes a physics-informed functional form with many tunable parameters calibrated using experimental/simulation data. Since there are inherent uncertainties in the calibration data (parametric uncertainty) and the assumed functional EOS form (model uncertainty), it is essential to perform uncertainty quantification (UQ) to improve confidence in EOS predictions. Model uncertainty is challenging for UQ studies since it requires exploring the space of all possible physically consistent functional forms. Thus, it is often neglected in favor of parametric uncertainty, which is easier to quantify without violating thermodynamic laws. This work presents a data-driven machine learning approach to constructing EOS models that naturally captures model uncertainty while satisfying the necessary thermodynamic consistency and stability constraints. We propose a novel framework based on physics-informed Gaussian process regression (GPR) that automatically captures total uncertainty in the EOS and can be jointly trained on both simulation and experimental data sources. A GPR model for the shock Hugoniot is derived, and its uncertainties are quantified using the proposed framework. We apply the proposed model to learn the EOS for the diamond solid state of carbon using both density functional theory data and experimental shock Hugoniot data to train the model and show that the prediction uncertainty is reduced by considering thermodynamic constraints.

Toward constraint of ionization-potential depression models in a convergent geometry

We demonstrate the value of inner-shell X-ray absorption spectroscopy for dense-plasma atomic physics and explore the coupling between constraint of the thermodynamic state and constraint of ionization-potential depression models. Synthetic K-shell absorption spectra are generated along a radius from a point-like core and analyzed using different ionization-potential depression models. Within this synthetic analysis framework, we identify plasma conditions (Te=400 eV, ρ=40 g/cm3) accessible by spherical implosions where K-shell absorption spectra discriminate between models if the material temperature is measured to a precision of 20%. The analysis is extensible to a finite-sized core and can be used to guide future studies of ionization-potential depression, informing material and radiative properties of matter in fusion plasmas and stellar interiors.

Statistics of detonation confinement: 1D, 2D and 3D simulations in hydrogen–oxygen

Statistical analysis of one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) detonation simulations is performed to understand the role of confinement on detonation frontal velocity and thermodynamic states. Simulations considered include a 2D wide channel (5 detonation cells across), a 2D narrow channel (1.5 cells across), a 3D square channel (10 cells around perimeter), and a 3D round tube (6 cells around perimeter), with identical mixture conditions of stoichiometric hydrogen–oxygen with 3000 parts per million by volume (PPMv) ozone at 300 K and 15 kPa. 1D and 2D simulations with the same mixture without ozone are also considered. All simulations solve the compressible Navier–Stokes equations with detailed chemistry and exhibit good agreement with macroscopic characteristics of experiments (e.g., cell size). Results show that the frontal velocity in 3D simulations is more irregular as compared to the 2D simulations, which are more irregular compared to the 1D simulations. The irregularity in frontal velocity leads to broader distributions of shock velocities and shock decay behavior. The 3D simulations also exhibit a wider and more extreme set of thermodynamic states as compared to the 2D simulations immediately behind the shock wave, within the induction zone, and throughout the rest of the domain. Increasing relative boundary losses leads to quantitative differences in both thermodynamic state and frontal velocity, consistent with 1D steady models of detonation with losses. The conclusions drawn in this work are not sensitive to numerical grid resolution.

Investigation of non-ideal effects in compressible boundary layers of dense vapors through direct numerical simulations

In this work, we present an investigation about the sources of dissipation in adiabatic boundary layers of non-ideal compressible fluid flows. Direct numerical simulations (DNS) of transitional, zero-pressure gradient boundary layer flows are performed for two fluids characterized by different complexity of the fluid molecules, namely, “air” and siloxane MM. Different sets of thermodynamic free-stream boundary conditions are selected to evaluate the influence of the fluid state on both the frictional loss and the dissipation mechanisms. The thermophysical properties of siloxane MM are calculated with a state-of-the-art equation of state. Results show that the dissipation due to both time-mean strain field, irreversible heat transfer, and turbulent dissipation differs significantly depending on both the molecular complexity of the fluid and its thermodynamic state. The dissipation coefficient calculated from the DNS results is then compared against the one obtained using a reduced-order model (ROM), which solves the two-dimensional boundary layer flow equations for an arbitrary fluid [M. Pini and C. De Servi, “Entropy generation in laminar boundary layers of non-ideal fluid flows,” in 2nd International Seminar on Non-Ideal Compressible Fluid Dynamics for Propulsion and Power (Springer, 2020), pp. 104–117]. Results from both the DNS and the ROM show that low values of the overall dissipation are observed in the case of fluids made of simple molecules, e.g., air, and if the fluid is at a thermodynamic state in the proximity of that of the vapor–liquid critical point.

Impact of the chimney junction radius on the air-flow characteristics inside a solar Chimney Power Plant

The chimney junction of solar chimney power plant was the main element coupled the solar collector to the chimney. It presents an important impact on the SCPP design, which is change the air-flow direction. The numerical code ANSYS Fluent was used in this study to investigate how the chimney Junction radius affected the local air-flow characteristics and the turbine site. Using test results from an experimental prototype constructed in Sfax, Tunisia, the numerical method was validated and verified. For four set-ups with various chimney connection radii, thermodynamic variables such as distributions of the total pressure, static temperature, static pressure, and magnitude velocity were examined. Also, the influence of these parameters on the air turbulence was analyzed through the transition zone. The results showed that the local air-flow characteristics and therefore, the SCPP efficiency were significantly impacted by changes in junction radius. Besides, the maximum velocity inside the chimney was varied and changes its location when the junction radius changed. These facts affect directly the overall turbine expenditure, which represented in terms of structure and power capacity.

Unravelling denaturation, temperature and cosolvent-driven chiroptical switching in peptide self-assembly with switchable piezoelectric responses.

Herein, we explore the intricate pathway complexity, focusing on the dynamic interplay between kinetic and thermodynamic states, during the supramolecular self-assembly of peptides. We uncover a multiresponsive chiroptical switching phenomenon influenced by temperature, denaturation and content of cosolvent in peptide self-assembly through pathway complexity (kinetic vs. thermodynamic state). Particularly noteworthy is the observation of chiroptical switching during the denaturation process, marking an unprecedented phenomenon in the literature. Furthermore, the variation in cosolvent contents produces notable chiroptical switching effects, emphasizing their infrequent incidence. Such chiroptical switching yields switchable piezoresponsive peptide-based nanomaterials, demonstrating the potential for dynamic control over material properties. In essence, our work pioneers the ability to control piezoresponsive behavior by transforming nanostructures from kinetic to thermodynamic states through pathway complexity. This approach provides new insights and opportunities for tailoring material properties in self-assembled systems.

Quantitative Mapping of Transient Thermodynamic States in Ultrafast Laser Nanostructuring of Quartz

Understanding material structural reaction to light is of utmost importance to advance processing resolution in ultrafast laser volume structuring into the nanoscale. Selective thermodynamic pathways are required to quench energy transport in the most rapid manner and to confine the process to nanometer lengths, bypassing optical resolution. Quantifying material dynamics under confinement, with in situ access to transient local temperature and density parameters, thus becomes key in understanding the process. We report in situ reconstruction of thermodynamic states over the entire matter relaxation path in bulk α -quartz irradiated by ultrafast nondiffractive laser beams using time-resolved qualitative and quantitative optical phase microscopy. Thermooptic dynamics indicate rapid spatially confined crystalline-to-amorphous transition to a hot dense fused silica form. Densification exceeds 20% and the matrix temperature rises to more than 2,000 K in the first nanosecond. This structural state relaxes in hundreds of nanoseconds. The dispersion and time design of the optical beam to picosecond durations increases the spatial confinement and triggers an extreme nanostructuring process based on nanocavitation that occurs within the amorphizing material, where the low-viscosity phase lowers the mechanical requirements for the process. Processing feature scales of less than a tenth of the optical wavelength are obtained in the volume. This allows for structural and morphological nanoscale material features under 3D confinement that can engineer optical materials.

Detecting Cold Pool Family Trees in Convection Resolving Simulations

AbstractRecent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short of reliably identifying the active gust front. The current cold pool (CP) detection and tracking algorithm (CoolDeTA), aims to identify cold pools and follow them in time, thereby distinguishing their active gust fronts and the “offspring” rain cells generated nearby. To accomplish these tasks, CoolDeTA utilizes a combination of thermodynamic and dynamical variables and examines the spatial and temporal relationships between cold pools and rain events. We demonstrate that CoolDeTA can reconstruct CP family trees. Using CoolDeTA we can contrast radiative convective equilibrium (RCE) and diurnal cycle CP dynamics, as well as cases with vertical wind shear and without. We show that the results obtained are consistent with a conceptual model where CP triggering of children rain cells follows a simple birth rate, proportional to a CP's gust front length. The proportionality factor depends on the ambient atmospheric stability and is lower for RCE, in line with marginal stability as traditionally ascribed to the moist adiabat. In the diurnal case, where ambient stability is lower, the birth rate thus becomes substantially higher, in line with periodic insolation forcing—resulting in essentially run‐away mesoscale excitations generated by a single parent rain cell and its CP.

Development of Micro-mechanical Constitutive Model for Alumina at High Strain Rates Using Unified Mechanics Theory

Ceramic materials used in mechanical applications show variations in their properties due to the presence of cracks. Micro-cracks within the material (size, orientation and density) affect the ceramic material’s strength and other mechanical properties. This study developed a micro-mechanics-based model that accounts for the original orientation of micro-cracks and their propagation as wing cracks. Unlike other micromechanics-based models, the current model defines failure based on entropy associated with crack propagation within the material. Entropy is calculated from energy dissipation from crack propagation from the pre-existing flaws in the ceramic. The Unified Mechanics Theory (UMT) is used to define entropy-based damage in the ceramic material, in which a parameter called thermodynamic state index (TSI) is employed to describe the state of the material. A representative volume element (RVE) with a pre-existing flaw is used to calculate the energy dissipated during the wing crack propagation. The effect of various crack lengths and orientations is incorporated with a probability density function. The strain rate effects are implemented using dynamic crack growth law. The stress-strain curve at strain rate from quasi-static to high strain rate (10-3-106) is plotted for Alumina under dynamic compression.

ЭНЕРГЕТИЧЕСКИЙ АНАЛИЗ В СИСТЕМЕ ЗАЩИТНЫХ МЕРОПРИЯТИЙ ПРЕДПРИЯТИЙ АГРАРНОГО СЕКТОРА

This article discusses the issue of the system of protective measures at enterprises of the agricultural sector. Energy plays a key role in farming. The cultivation of crops is based on the conversion of solar energy into biomass. Energy flows are located between two worlds: although energy is a strategic component of the economy, it is also a thermodynamic state variable for describing ecosystems. This situation once again highlights the need to analyze energy flows in agricultural systems. There is a wide variety of approaches used to calculate farm-scale energy flows. This analysis highlights the lack of clear definition of system boundaries in farm-scale research. In addition, most of the research is mainly devoted to socio-economic flows in the sectoral context. However, internal biomass flows, which play a role in maintaining the functionality of the agroecosystem, can also be considered in accordance with a circular/systemic perspective. Thus, some recommendations are given for conducting an exhaustive energy assessment of farming systems, as well as for future research directions. An attempt has been made to conceptualize the implementation of energy expertise in the system of protective measures of the agro-industrial complex enterprise against pests (insects, rodents, birds). The separation of energy in the working part into calculated consumption and losses is proposed, with the transfer of this division to energy consumption and energy intensity of products. Thus, using this method gives a figure of the real value of energy efficiency. This eliminates the uncertainty of the traditional calculation of the energy intensity of products. It also allows for energy expertise of design and technological solutions and to obtain correct information about energy needs. Material products made from raw materials acquire, through the influence of energy, those properties that determine their need in the market. These properties and qualities are given to raw materials in a process called energy technology. There are basically two formulations of the technological process. According to the first, the technological process is a sequence and a set of operations, according to the second, more capacious and arising from the content of the term itself, technology is the science of ways to influence the material, allowing to optimize this effect. The first definition refers more to the organization and structure of production.

Effect of the linking bridge type on the self-assembly behaviour of 2',3'-difluoroterphenyl derivatives.

The self-assembly behaviour and the crystallization kinetics of two liquid crystal compounds containing 2',3'-difluorosubstituted terphenyl as the mesogenic core have been described. Calorimetric studies show that the linking bridge type affects the polymorphism of smectic phases. The CH2O.3 compound with the -CH2O- linking bridge connected with a longer methylene spacer possesses the chiral smectic phase with antiferroelectric properties (SmCA* phase), while the COO.6 liquid crystal with the -COO- linking bridge connected with a shorter alkyl chain forms the chiral smectic phase with ferroelectric properties (SmC* phase). Both compounds crystallize upon slow cooling, while fast cooling causes the vitrification of the conformationally disordered crystal phase. Dielectric measurements reveal the complex relaxation dynamics in the identified thermodynamic states. DFT calculations allow us to estimate the nature of relaxation processes.

Physics-informed machine learning of the correlation functions in bulk fluids

The Ornstein–Zernike (OZ) equation is the fundamental equation for pair correlation function computations in the modern integral equation theory for liquids. In this work, machine learning models, notably physics-informed neural networks and physics-informed neural operator networks, are explored to solve the OZ equation. The physics-informed machine learning models demonstrate great accuracy and high efficiency in solving the forward and inverse OZ problems of various bulk fluids. The results highlight the significant potential of physics-informed machine learning for applications in thermodynamic state theory.

Theoretical study of CDW phases for bulk NbX2 (X = S and Se).

In most two-dimensional transition metal chalcogenides, the superconducting phase coexists with the charge density wave (CDW) phase. There exists at least one case, i.e. bulk 2H-NbS2, that does not conform to this picture. Scientists have shown great interest in trying to experimentally find the CDW phase of bulk NbS2 since 1975. Is there any theoretically more stable thermodynamic state than its higher-temperature metal phase, especially in the case of charge injection? Theoretically more stable CDW bulk configurations (TC for 2H-NbS2 and TTs for 2H-NbSe2) with partial pseudo energy gaps were predicted through the harmonic phonon softening theory and first-principles calculations. The ratios of larger to smaller pseudo gaps around K-H segment in the Brillouin zone for CDW phases are basically equal to those of superconductivity phases for bulk 2H-NbX2 (X = S and Se). The CDW phase should coexist with its superconductor state below the critical temperature rather than the metal phase for bulk 2H-NbS2. The presence of CDW phase should be more easily observed experimentally when the injected charge reaches 0.5e/Nb18S36 for bulk 2H-NbS2. Our calculations of density of state (DOS) indicated that, during Nb atoms contracting to form the CDW phases with symmetry breaking in the in-plane direction, dominant conductive carriers are always of p-type for bulk 2H-NbS2 while the alternation of carrier type from p-type to n-type occurs for bulk 2H-NbSe2. The Fermi level continuously drops and then the M-L segment of the out-of-plane energy band emerges from the Fermi surface, which corresponds to the reversal of p-n type sign. Lifshitz transition of pocket-vanishing types occurs in the out-of-plane direction without symmetry breaking during the geometrical structural phase transition for bulk 2H-NbSe2. Our calculations have theoretically addressed the long-standing coexistence issue of CDW and superconducting phases.