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Results for “engineering 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.
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On the operational characteristics and economic value of pumped thermal energy storage
Pumped thermal energy storage (PTES) systems use an electrically-driven heat pump to store electricity in the form of thermal energy, and subsequently dispatch the stored thermal energy to generate electricity using a thermodynamic heat engine. Optimal day-ahead operational scheduling and annual value of a PTES system based on Joule-Brayton thermodynamic cycles and two-tank molten salt hot thermal storage is evaluated in this work. Production cost models, which simultaneously optimize commitment and dispatch schedules for an entire set of generators to minimize the cost of satisfying electricity demand, are employed to determine system-optimal operation and day-ahead energy value of the PTES system within each of six hypothetical near-future grid scenarios intended to approximately represent the U.S. Western Interconnection or the Texas Interconnection. Sensitivity to grid scenario (including the contribution of variable renewable energy sources), thermal storage capacity, relative heat pump and heat engine capacities, and startup/shutdown cycling costs are evaluated. PTES energy value and heat engine annual capacity factor increase strongly as the contribution of variable renewable resources increases, heat pump capacity increases relative to heat engine capacity, or PTES cycling costs decrease. Grid scenarios in which the contribution of variable renewable energy is dominated by solar photovoltaics (PV) vs. wind produce inherently different PTES operational patterns. Annual PTES energy value within PV-dominated scenarios increased with storage capacity only up to approximately seven hours of full-load discharge capacity, whereas that within wind-dominated scenarios exhibited a continual increase with storage duration up to at least 16 hours.
Titanium and Iron in the Cassiopeia A Supernova Remnant
Mixing above the proto-neutron star is believed to play an important role in the supernova engine, and this mixing results in a supernova explosion with asymmetries. Elements produced in the innermost ejecta, e.g., 56 Ni and 44 Ti, provide a clean probe of this engine. The production of 44Ti is particularly sensitive to the exact production pathway and, by understanding the available pathways, we can use 44 Ti to probe the supernova engine. Using thermodynamic trajectories from a three-dimensional supernova explosion model, we review the production of these elements and the structures expected to form under the "convective-engine" paradigm behind supernovae. Overall, we compare our results to recent X-ray and γ-ray observations of the Cassiopeia A supernova remnant.
Summary of Thermodynamic Data Integration (M4SF-23LL010301052)
This progress report (Level 4 Milestone Number M4SF-23LL010301052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Activity Number M4SF-23LL010301052. SUPCRTNE is being developed as the primary engine for thermodynamic database development in support of geologic disposal of high-level nuclear waste. As used here, “SUPCRT” refers to both a computer program and its supporting database. Additional letters or numbers refer to specific variants (SUPCRT92, Johnson et al., 1992; SUPCRTBL, Zimmer et al., 2016; and SUPCRTNE). A SUPCRT database contains the data required to calculate the thermodynamic properties of solid, gas, and aqueous species over a wide range of temperature and pressure. Normally SUPCRT is used to create a higher-level data base that directly supports modeling and simulation codes such as EQ3/6, GWB, PHREEQC, and PFLOTRAN.
Temperature-dependent spectral emittance of bauxite and silica particle beds
Bauxite and silica particles are candidate materials for solar thermal energy storage at high temperatures. The temperature-dependent emittance of packed beds with bauxite and silica particles was measured using a newly upgraded emissometer at wavelengths 2 μm ≤ λ ≤ 16 μm and temperatures up to ~730 K. The room-temperature emittance was obtained from the measured directional-hemispherical reflectance. A fused silica disc was used to test the emissometer by comparing the measured spectral emittance with the calculated emittance from a fitted Lorentz oscillator model. For the polycrystalline silica particles and the fused silica disc, the measured emittance increases with temperature in the mid-infrared region. The underlying mechanism is interpreted as the temperature-dependent damping coefficient in the Lorentz oscillator model. Two types of bauxite particles with different compositions and sizes were investigated. For λ > 10 μm, the measured emittance at elevated temperatures is higher than that at room temperature. In the region 2 μm < λ < 6 μm, the temperature dependence varies for different types of particles. The total emittance of bauxite particle beds was calculated by spectral integration using Planck’s distribution at the prescribed temperature. As a result, the calculated total emittance is between 0.89 and 0.96, but it does not change monotonically with temperature.
A cosine-based correlation information entropy approach for building automatic fault detection baseline construction
Building automatic fault detection and diagnosis (AFDD) technologies have shown great potential for energy savings. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Existing research using physics-based knowledge and models for AFDD has mainly taken a trial-and-error approach to determine if a given baseline is sufficient via empirical experiments. A mechanism to support decisions such as how many samples and what samples should be included in the baseline is currently lacking. In this study, a data-driven method for AFDD baseline construction based on information entropy is developed. The entropy is derived based on cosine similarity among typical building automation system measurements in conjunction with outdoor weather information. The performance of the proposed method is evaluated using real building data. Evaluation results indicate that the fault detection strategy adopting the proposed method has similar or better accuracy in detecting faults compared to the same fault detection strategy using the baseline construction method from the literature. Additionally, the use of entropy enables the proposed method to automatically construct and assess the baseline consisting of information-rich samples.
Numerical simulation of a methane-oxygen rotating detonation rocket engine
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Survey of Data and Models for Refrigerant Mixtures Containing Halogenated Olefins
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Thermodynamic re-modeling of the Yb-Sb system aided by first-principles calculations
Here, the thermodynamic description of the Yb-Sb binary system is developed by means of the CALculations of PHAse Diagrams (CALPHAD) method by combining experimental data in the literature and predictions from first-principles calculations based on density functional theory (DFT) in the literature and the present work. Two pseudopotentials of Yb are compared in the present DFT-based calculations with 14 and 13 f-electrons frozen in the core, i.e., 5p 6 6s 2 and 5p 6 6s 2 5 d 1 electrons as valence electrons, termed Yb_2 and Yb_3, respectively. It is shown that the phonon spectrum of the YbSb phase calculated using the Yb_3 pseudopotential does not have imaginary phonon modes and is subsequently used to predict its temperature dependent thermodynamic properties by the DFT-based quasiharmonic phonon calculations. The present thermodynamic database includes the Yb 16 Sb 11 phase in addition to five intermetallic phases that were considered in previous modeling studies, i.e., YbSb 2 , YbSb, Yb 11 Sb 10 , Yb 4 Sb 3 , and Yb 5 Sb 3 . The high temperature orthorhombic structure of the Yb 5 Sb 3 phase is not considered in the present work as it was stabilized by hydrogen. The associate solution model is used to describe the short-range ordering behavior in the liquid phase. The calculations from the present thermodynamic model show good agreement with thermochemical and phase equilibrium data from both the present work and the literature.
Computational thermodynamics and its applications
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.
Dry cooler contribution to LCOE in a sCO 2 power cycle for CSP
In order to maintain viability as a future power-generating technology, concentrating solar power (CSP) must reduce its levelized cost of electricity (LCOE). One component of solving this problem is reducing the cost of the power block while simultaneously increasing the efficiency of the thermodynamic cycle. One disruptive technology that has the promise to accomplish this is supercritical CO 2 (sCO 2 ) based power cycles. Here, these cycles are conceptually similar to steam cycles; however, they have substantially smaller turbomachinery at equivalent power while also delivering more efficiency at turbine inlet temperatures of 500-700 °C.
Bubble Point Measurements of Three Binary Mixtures of Refrigerants: R-32/1234yf, R-32/1234ze(E), and R-1132a/1234yf
In this article, bubble point pressures of three binary mixtures at two compositions each have been measured utilizing a static method. The mixtures studied were difluoromethane + 2,3,3,3-tetrafluoroprop-1-ene (R-32/1234yf), difluoromethane + (E)-1,3,3,3-tetrafluoroprop-1-ene (R-32/1234ze(E)), and 1,1-difluoroethene + 2,3,3,3-tetrafluoroprop-1-ene (R-1132a/1234yf). For all of the mixtures, the minimum temperature measured was 270 K. The maximum temperatures measured for the R-32/1234ze(E), R-32/1234yf, and R-1132a/1234yf mixtures were 360, 345, and 325 K, respectively. A total of 100 bubble point pressures are reported and compared to available literature data relative to the REFPROP database. Lemmon, E. W. [ NIST Standard Reference Database 23: Reference Fluid Thermodynamic and Transport Properties-REFPROP, 10.0; National Institute of Standards and Technology, Standard Reference Data Program: Gaithersburg, 2018]. Additionally, the bubble point pressures obtained in this study are modeled using the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state. The PC-SAFT model parameters, as well as deviations of this work and literature data from the model, are reported.
Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Furthermore, those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.
Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model
We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.