Search NASA⌕ Search

SEARCH · Search NASA

Results for “Yield function”

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 1,351 records · Page 75

Semi-automated Design of Artificial Intelligence Earth Systems Models

Prediction and observation of water cycles at various scales involve not only patterns isolated in space and time, but also modeling of complex spatio-temporal relationships across multiple domains. For instance, evapotranspiration (ET) and leaf area indexes (LAI) are two parameters that are needed to accurately model and understand land-atmosphere processes. Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFTs), which fail to capture fine-scale variations because of changes in vegetation type across the globe. Similarly LAI estimates have typically been derived from vegetation indices at global scales or estimated locally using physical models, both of which suffer from a range of uncertainties that impact model sensitivity. The new era of AI model development for Earth systems (ES) calls for data-driven methods that provide domain scientists with uncertainty-aware estimations of biophysical parameters such as ET and LAI in a generalizable, interpretable, and discoverable manner.

54 ENVIRONMENTAL SCIENCES↗

Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform

The goal of the Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform project is to derisk the manufacturing scalability for a high chip count heterogeneous smart lighting platform, with the potential to enable significant energy savings through dynamic directional light control and custom. Specifically, the project derisks the scalability of a disruptive new computer controlled microassembly fabrication process SRI International is developing, to address fundamental cost barriers to mass production of high chip count systems. This is key for enabling mass adoption and thus maximum societal energy savings impact. The LED light sheet technology is a smart illumination platform that can be applied to lighting, signage, and display. It has features and a form factor similar to bendable or conformal OLED light sheets but uses more efficient LEDs with a remote phosphor layer that is very close to the LED to deliver a luminous efficacy that exceeds 125 lumen/Watt and enable > 50% Lighting Application Efficiency (LAE) energy savings. During Budget Period 1 (BP1), all of the BP1 milestones were successfully completed: (M2.0.1) Design demonstrator details that will meet the final project goals, (M6.1.1) Show lighting output model can predict illuminance, spatial, spectral distribution for specific light-sheet designs and use case, (M3.2.1) Automated loading supports 200 chip arrays, and (M3.3.1) Finish first interconnect process run for 200 chip array. The BP1 Go/No-Go Decision Point (G/NG 1) 200 chip demonstrator sample was in the process of final assembly and test at the end of BP1 on December 31, 2023. The objective was successfully achieved on January 16, 2024, when a wired 200-chip sample underwent confirmation testing that demonstrated a 93.75% first pass electrical yield that successfully exceeded the 75% first-pass electrical yield BP1 G/NG requirement. In addition, all 93.75% of the sample devices lit up, further demonstrating the ability to assemble and transfer small LED chips without damaging their functionality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Measuring the Properties of Dark Energy with Photometrically Classified Pan-STARRS Supernovae. I. Systematic Uncertainty from Core-collapse Supernova Contamination

The Pan-STARRS (PS1) Medium Deep Survey discovered over 5000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3147 of these likely SNe and estimate that ∼1000 are Type Ia SNe (SNe Ia) with light-curve quality sufficient for a cosmological analysis. We use these data with simulations to determine the impact of core-collapse SN (CC SN) contamination on measurements of the dark energy equation of state parameter, w. Using the method of Bayesian Estimation Applied to Multiple Species (BEAMS), distances to SNe Ia and the contaminating CC SN distribution are simultaneously determined. We test light-curve-based SN classification priors for BEAMS as well as a new classification method that relies upon host galaxy spectra and the association of SN type with host type. By testing several SN classification methods and CC SN parameterizations on large SN simulations, we estimate that CC SN contamination gives a systematic error on w (σ{sub w}{sup CC}) of 0.014, 29% of the statistical uncertainty. Our best method gives σ{sub w}{sup CC}=0.004, just 8% of the statistical uncertainty, but could be affected by incomplete knowledge of the CC SN distribution. This method determines the SALT2 color and shape coefficients, α and β, with ∼3% bias. However, we find that some variants require α and β to be fixed to known values for BEAMS to yield accurate measurements of w. Finally, the inferred abundance of bright CC SNe in our sample is greater than expected based on measured CC SN rates and luminosity functions.

79 ASTRONOMY AND ASTROPHYSICS↗

In-situ ionothermal synthesis of nanoporous carbon/oxide composites: A new key to functional separators for stable lithium-sulfur batteries

Lithium-sulfur batteries (LSBs) with high energy density are promising for energy storage. However, conventional polypropylene-based separator cannot avoid polysulfides shuttling which impedes the practical application of LSBs. Herein, an in-situ ionothermal synthesis strategy that concurrently applies ionic liquid as the solvent, template and high-yield carbon source is proposed for the facile preparation of nanoporous carbon/oxide composite separator modifiers. The composites exhibit features of high polarity, self doping, oxygen vacancy, heteroatom doping, abundant defects and high electronic conductivity. Theoretical and experimental studies suggest that the composites can efficiently trap and convert polysulfides for high-performance LSBs. Indeed, in the composite-modified LSBs with next-generation roll-to-roll dry-processed high-loading sulfur cathodes, enhanced performance is achieved, revealing the effectiveness of the composites as functional materials towards separator modification. Therefore, the proposed strategy and its delivered nanoporous composites exhibit excellent versatility and practicality for high-performance LSBs.

25 ENERGY STORAGE↗

High-throughput exploration of the WMoVTaNbAl refractory multi-principal-element alloys under multiple-property constraints

Development of next-generation gas turbines requires the design and fabrication of novel high-temperature structural materials capable of operating beyond 1300°C. Here, we propose a high-throughput alloy design framework under multiple-property constraints to discover new refractory multi-principal element alloys (MPEAs) for high-temperature applications. The framework treats the development of MPEAs as a composition-agnostic constraint satisfaction problem, i.e., no prescriptions are made concerning the design space before performing investigatory calculations. We target alloys in the WMoVTaNbAl chemistry space that are predicted to meet constraints on the following properties simultaneously: single-phase stability, density, solidus temperature, yield strength at 1300°C, and ductile-to-brittle-transition temperature. These properties are relevant to both applications in gas turbines and manufacturability. A set of 214 MoNbV-rich alloys meet these relevant constraints. These feasible alloys are investigated with density functional theory (DFT) to provide a fundamental electronic basis for their superior properties. Three compositionally representative alloys from the feasible design space (Mo 45 Nb 35 Ta 5 V 15 , Mo 25 Nb 50 V 20 W 5 , and Mo 30 Nb 35 Ta 5 V 25 W 5 ) are selected with a k-medoids-based design scheme for detailed DFT analysis and experimental characterization. The DFT analysis predicted a single-phase BCC at high temperatures with a high yield strength for all three MPEAs, in agreement with CALPHAD (CALculation of PHAse Diagrams) and experiments, respectively. These three alloys are benchmarked against a public database of 1546 MPEAs. Concerning the aforementioned constraints, the Mo 30 Nb 35 Ta 5 V 25 W 5 alloy outperforms these 1546 MPEAs. The present work demonstrates the ability of the proposed design methodology to identify candidate alloys for a given application under multiple property constraints in a combinatorically vast design space.

36 MATERIALS SCIENCE↗

Advanced stationary and nonstationary kernel designs for domain-aware Gaussian processes

Gaussian process regression is a widely-applied method for function approximation and uncertainty quantification. The technique has gained popularity recently in the machine learning community due to its robustness and interpretability. The mathematical methods we discuss in this paper are an extension of the Gaussian-process framework. We are proposing advanced kernel designs that only allow for functions with certain desirable characteristics to be elements of the reproducing kernel Hilbert space (RKHS) that underlies all kernel methods and serves as the sample space for Gaussian process regression. These desirable characteristics reflect the underlying physics; two obvious examples are symmetry and periodicity constraints. In addition, non-stationary kernel designs can be defined in the same framework to yield flexible multi-task Gaussian processes. We will show the impact of advanced kernel designs on Gaussian processes using several synthetic and two scientific data sets. The results of our research show that including domain knowledge, communicated through advanced kernel designs, has a significant impact on the accuracy and relevance of the function approximation.

97 MATHEMATICS AND COMPUTING↗

Exploring and enhancing the accuracy of interior-scaled Perdew–Zunger self-interaction correction

The Perdew–Zunger self-interaction correction (PZ-SIC) improves the performance of density functional approximations for the properties that involve significant self-interaction error (SIE), as in stretched bond situations, but overcorrects for equilibrium properties where SIE is insignificant. This overcorrection is often reduced by local scaling self-interaction correction (LSIC) of the PZ-SIC to the local spin density approximation (LSDA). Here, we propose a new scaling factor to use in an LSIC-like approach that satisfies an additional important constraint: the correct coefficient of the atomic number Z in the asymptotic expansion of the exchange–correlation (xc) energy for atoms. LSIC and LSIC+ are scaled by functions of the iso-orbital indicator z σ , which distinguishes one-electron regions from many-electron regions. LSIC+ applied to the LSDA works better for many equilibrium properties than LSDA-LSIC and the Perdew, Burke, and Ernzerhof generalized gradient approximation (GGA), and almost close to the strongly constrained and appropriately normed (SCAN) meta-GGA. LSDA-LSIC and LSDA-LSIC+, however, fail to predict interaction energies involving weaker bonds, in sharp contrast to their earlier successes. It is found that more than one set of localized SIC orbitals can yield a nearly degenerate energetic description of the same multiple covalent bond, suggesting that a consistent chemical interpretation of the localized orbitals requires a new way to choose their Fermi orbital descriptors. To make a locally scaled down SIC to functionals beyond the LSDA requires a gauge transformation of the functional’s energy density. Here, the resulting SCAN-sdSIC, evaluated on SCAN-SIC total and localized orbital densities, leads to an acceptable description of many equilibrium properties including the dissociation energies of weak bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energetic Basis and Design of Enzyme Function Demonstrated Using GFP, an Excited-State Enzyme

We report the past decades have witnessed an explosion of de novo protein designs with a remarkable range of scaffolds. It remains challenging, however, to design catalytic functions that are competitive with naturally occurring counterparts as well as biomimetic or nonbiological catalysts. Although directed evolution often offers efficient solutions, the fitness landscape remains opaque. Green fluorescent protein (GFP), which has revolutionized biological imaging and assays, is one of the most redesigned proteins. While not an enzyme in the conventional sense, GFPs feature competing excited-state decay pathways with the same steric and electrostatic origins as conventional ground-state catalysts, and they exert exquisite control over multiple reaction outcomes through the same principles. Thus, GFP is an “excited-state enzyme”. Herein we show that rationally designed mutants and hybrids that contain environmental mutations and substituted chromophores provide the basis for a quantitative model and prediction that describes the influence of sterics and electrostatics on excited-state catalysis of GFPs. As both perturbations can selectively bias photoisomerization pathways, GFPs with fluorescence quantum yields (FQYs) and photoswitching characteristics tailored for specific applications could be predicted and then demonstrated. The underlying energetic landscape, readily accessible via spectroscopy for GFPs, offers an important missing link in the design of protein function that is generalizable to catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous Aerosol and Plasma Co‐Jet Printing of Metallic Devices at Ambient Temperature

Abstract Additive manufacturing of metallic materials holds the potential to revolutionize the fabrication of functional devices unattainable via traditional methods. Despite recent advancements, printing metallic materials typically requires thermal processing at elevated temperatures to form dense structures with desired properties, which presents a major challenge for direct printing and integration with temperature‐sensitive materials. Herein, a unique co‐jet printing (CJP) method is reported integrating an aerosol jet and a non‐thermal, atmospheric pressure plasma jet to enable concurrent aerosol deposition of metal nanoparticle inks and in situ sintering at ambient temperature. A machine learning algorithm is integrated with the CJP to perform real‐time defect detection and autonomous correction, enhancing the yield of printed films with high electrical conductivity from 44% to 94%. Concurrent printing and sintering eliminate the need for post‐printing processing, reducing the overall manufacturing time by multiple folds depending on product size. CJP enables direct printing of functional devices on a variety of temperature‐sensitive materials including biological materials. Direct printing of hydration sensors on living plant leaves is demonstrated for long‐duration monitoring of hydration level in the plant. The versatile CJP method opens tremendous opportunities to harmoniously integrate abiotic and biotic materials for emerging applications in wearable/implantable devices and biohybrid systems.

Du, Yipu [Department of Aerospace and Mechanical E↗

Programming interfacial energetic offsets and charge transfer in β-Pb 0.33 V 2 O 5 /quantum-dot heterostructures: Tuning valence-band edges to overlap with midgap states

Here, semiconductor heterostructures for solar energy conversion interface light-harvesting semiconductor nanoparticles with wide-band-gap semiconductors that serve as charge acceptors. In such heterostructures, the kinetics of charge separation depend on the thermodynamic driving force, which is dictated by energetic offsets across the interface. A recently developed promising platform interfaces semiconductor quantum dots (QDs) with ternary vanadium oxides that have characteristic midgap states situated between the valence and conduction bands. In this work, we have prepared CdS/β-Pb 0.33 V 2 O 5 heterostructures by both linker-assisted assembly and surface precipitation and contrasted these materials with CdSe/β-Pb 0.33 V 2 O 5 heterostructures prepared by the same methods. Increased valence-band (VB) edge onsets in X-ray photoelectron spectra for CdS/β-Pb 0.33 V 2 O 5 heterostructures relative to CdSe/β-Pb 0.33 V 2 O 5 heterostructures suggest a positive shift in the VB edge potential and, therefore, an increased driving force for the photoinduced transfer of holes to the midgap state of β-Pb 0.33 V 2 O 5 . This approach facilitates a ca. 0.40 eV decrease in the thermodynamic barrier for hole injection from the VB edge of QDs suggesting an important design parameter. Transient absorption spectroscopy experiments provide direct evidence of hole transfer from photoexcited CdS QDs to the midgap states of β-Pb 0.33 V 2 O 5 NWs, along with electron transfer into the conduction band of the β-Pb 0.33 V 2 O 5 NWs. Hole transfer is substantially faster and occurs at <1-ps time scales, whereas completion of electron transfer requires 5—30 ps depending on the nature of the interface. The differentiated time scales of electron and hole transfer, which are furthermore tunable as a function of the mode of attachment of QDs to NWs, provide a vital design tool for designing architectures for solar energy conversion. More generally, the approach developed here suggests that interfacing semiconductor QDs with transition-metal oxide NWs exhibiting intercalative midgap states yields a versatile platform wherein the thermodynamics and kinetics of charge transfer can be systematically modulated to improve the efficiency of charge separation across interfaces.

36 MATERIALS SCIENCE↗

Aligning the Induced Anisotropy of Isotropic Nanoparticles with Liquid Crystals

Thermotropic liquid crystals (LCs) present opportunities for synergistic interactions with ligand-functionalized nanoparticles (NPs). Understanding the dynamics and structures of ligand-coated NPs in an anisotropic LC environment allows for better design and control of versatile LC-NP hybrid materials. Here, simulations and experiments yield direct evidence that cyanobiphenyl LCs induce anisotropy in the biphenylalkyl ligand shells of spherical NPs. The ellipsoidal NP aligns with the LC director. Magnetic fields can dictate the directional ordering of mesogens and consequently allow control of the orientation of the nonmagnetic NPs. Further, controlling the alignment and deformation advances the design and engineering of these hybrid nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulating Electron Dynamics of Complex Molecules with Time-Dependent Complete Active Space Configuration Interaction

In this paper, time-dependent electronic structure methods are growing in popularity as tools for modeling ultrafast and/or nonlinear processes, for computing spectra, and as the electronic structure component of mean-field molecular dynamics simulations. Time-dependent configuration interaction (TD-CI) offers several advantages over the widely used real-time time-dependent density functional theory: namely, that it correctly models Rabi oscillations; it offers a spin-pure description of open-shell systems; and a hierarchy of TD-CI methods can be defined that systematically approach the exact solution of the time-dependent Schrodinger equation (TDSE). In this work, we present a novel TD-CI approach that extends TD-CI to large complete active-space configuration expansions. Such extension is enabled by use of a direct configuration interaction approach that eliminates the need to explicitly build, store, or diagonalize the Hamiltonian matrix. Graphics processing unit (GPU) acceleration enables fast solution of the TDSE even for large active spaces—up to 12 electrons in 12 orbitals (853776 determinants) in this work. A symplectic split operator propagator yields long-time norm conservation. We demonstrate the applicability of our approach by computing the response of a large molecule with a strongly correlated ground state, decacene (C 42 H 24 ), to various pulses (δ-function, transform limited, chirped). Our simulations predict that chirped pulses can be used to induce dipole-forbidden transitions. Simulations of decacene using the 6-31G(d) basis set and a 12 electrons/12 orbitals active space took 20.1 h to propagate for 100 fs with a 1 attosecond time step on a single NVIDIA K40 GPU. Convergence with respect to time step is found to depend on the property being computed and the chosen active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A new neutron time-of-flight detector for yield and ion-temperature measurements at the OMEGA Laser Facility

A new neutron time-of-flight (nTOF) detector for deuterium–deuterium (DD)-fusion yield and ion-temperature measurements was designed, installed, and calibrated for the OMEGA Laser Facility. This detector provides an additional line of sight for DD neutron yield and ion-temperature measurements for yields exceeding 1 × 10 10 with higher precision than existing detectors. The nTOF detector consists of a 90-mm-diam, 20-mm-thick BC-422 scintillator and a gated Photek photomultiplier tube (PMT240). The PMT collects scintillating light through the 20-mm side of the scintillator without the use of a light guide. There is no lead shielding from hard x rays in order to allow the x-ray instrument response function of the detector to be measured easily. Instead, hard x-ray signals generated in implosion experiments are gated out by the PMT. The design provides a place for glass neutral-density filters between the scintillator and the PMT to avoid PMT saturation at high yields. The nTOF detector is installed in the OMEGA Target Bay along the P8A sub-port line of sight at a distance of 5.3 m from the target chamber center. In addition to DD measurements, the same detector can be used to measure the neutron yield and ion temperature from deuterium–tritium (DT) implosion targets in the 5 × 10 10 to 2 × 10 12 yield range. Here, the design details and the calibration results of this nTOF detector for both D 2 and DT implosions on OMEGA will be presented.

47 OTHER INSTRUMENTATION↗

The effect of temperature on photosystem II efficiency across plant functional types and climate

Modeling terrestrial gross primary productivity (GPP) is central to predicting the global carbon cycle. Much interest has been focused on the environmentally induced dynamics of photosystem energy partitioning and how improvements in the description of such dynamics assist the prediction of light reactions of photosynthesis and therefore GPP. The maximum quantum yield of photosystem II (Φ PSIImax ) is a key parameter of the light reactions that influence the electron transport rate needed for supporting the biochemical reactions of photosynthesis. Φ PSIImax is generally treated as a constant in biochemical photosynthetic models even though a constant Φ PSIImax is expected only for non-stressed plants. We synthesized reported Φ PSIImax values from pulse-amplitude-modulated fluorometry measurements in response to variable temperatures across the globe. We found that Φ PSIImax is strongly affected by prevailing temperature regimes with declined values in both hot and cold conditions. To understand the spatiotemporal variability in Φ PSIImax , we analyzed the temperature effect on Φ PSIImax across plant functional type (PFT) and habitat climatology. The analysis showed that temperature's impact on Φ PSIImax is shaped more by climate than by PFT for plants with broad latitudinal distributions or in regions with extreme temperature variability. There is a trade-off between the temperature range within which Φ PSIImax remains maximal and the overall rate of decline of Φ PSIImax outside the temperature range such that species cannot be simultaneously tolerant and resilient to extreme temperatures. Our study points to a quantitative approach for improving electron transport and photosynthetic productivity modeling under changing climates at regional and global scales.

54 ENVIRONMENTAL SCIENCES↗

Achieving Ultra-High Selectivity to Hydrogen Production from Formic Acid on Pd–Ag Alloys

Palladium-silver based alloy catalysts have a great potential for CO-free hydrogen production from formic acid for fuel cell applications. However, the structural factors affecting the selectivity of formic acid decomposition is still debated. Herein, the decomposition pathways of formic acid on Pd-Ag alloys with different atomic configurations have been investigated to identify the alloy structures yielding high H 2 selectively. Several Pd x Ag 1-x surface alloys with various compositions were generated on a Pd(111) single crystal; their atomic distribution and electronic structure were determined by a combination of infrared reflection absorption spectroscopy (IRAS), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT). It was established that the Ag atoms with Pd neighbors are electronically altered, and the degree of alteration correlates with the number of nearest Pd. Temperature programmed reaction spectroscopy (TPRS) and DFT demonstrated that the electronically altered Ag domains create a new reaction pathway that selectively dehydrogenates formic acid. In contrast, Pd monomers surrounded by Ag are demonstrated to have a similar reactivity compared to pristine Pd(111), yielding CO and H 2 O in addition to the dehydrogenation products. Furthermore, they bind to the produced CO weaker than pristine Pd, demonstrating an enhancement in resistance to CO poisoning. This work therefore shows that surface Ag domains modified by interaction with subsurface Pd are the key active sites for selective decomposition of formic acid, while surface Pd atoms are detrimental for selectivity. Hence the decomposition pathways can be tailored for CO-free H 2 production on Pd-Ag alloy systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coherent Transport of Electron Excitations in Organic Solar Cells

The mechanisms of formation and coherent transport of free and bound electron excited states in organic solar cells are considered. In the model of a photocell (one-dimensional chain of photosensitive molecules in a uniform electric field of the p–n junction), the energy eigenvalues and the eigenfunctions of molecular excitons, charge-transfer excitons (CTE), and electron–hole pairs are determined. It is assumed that processes of transport between adjacent sites dominate in the case of the Coulomb interaction between the electron and the hole constituting a CTE. With decreasing Coulomb coupling energy, the CTE wavefunctions become superpositions of localized functions of the increasing number of sites. The decay time determined by independent transitions of the electron and the hole in this case becomes shorter than the transport time of the CTE as a whole. It is shown that autoionization of molecular excitons and small-radius CTEs in a strong electric field of a nanosize chain induces the mixing of states of these excitons as well as of electron–hole pairs, which substantially increases the quantum yield of the photoeffect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On the analysis of signal peaks in pulse-height spectra

The estimation of the signal location and intensity of a peak in a pulse height spectrum is important for X- ray and γ-ray spectroscopy, charged-particle spectrometry, liquid chromatography, and many other subfields. However, both the ‘‘centroid’’ and ‘‘signal intensity’’ of a peak in a pulse-height spectrum are ill-defined quantities and different methods of analysis will yield different numerical results. Here, we apply three methods of analysis. Method A is based on simple count summation and is likely the technique most frequently applied in practice. The analysis is straightforward and fast, and does not involve any statistical modeling. We find that it provides reliable results only for high signal-to-noise data, but has severe limitations in all other cases. Method B employs a Bayesian model to extract signal counts and centroid from the measured total and background counts. The resulting values are derived from the respective posteriors and, therefore, have a rigorous statistical meaning. The method makes no assumptions about the peak shape. It yields reliable and relatively small centroid uncertainties. However, it provides relatively large signal count uncertainties. Method C makes a strong assumption regarding the peak shape by fitting a Gaussian function to the data. Furthermore, the fit is based again on a Bayesian model. Although Method C requires careful consideration of the Gaussian width (usually given by the detector resolution) used in the fitting, it provides reliable values and relatively small uncertainties both for the signal counts and the centroid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Close-contact melting on an isothermal surface with the inclusion of non-Newtonian effects

The present study deals with a theoretical investigation of a close-contact melting (CCM) process involving a vertical cylinder on a horizontal isothermal surface, where the liquid phase is a non-Newtonian viscoplastic fluid that behaves according to the Bingham model. Accordingly, a new approach is formulated based on the thin layer approximation and different quasi-steady process assumptions. By analytical derivation, an algebraic equation that relates the molten layer thickness and the solid bulk height is developed. The problem is then solved numerically, coupled with another equation for the melting rate. The new model shows that as the yield stress increases the melting rate decreases and the molten layer thickness increases. It is found that under certain conditions, the model can be reduced to a form that allows an analytical solution. The approximate model predicts an exponential dependence of both the melt fraction and the molten layer thickness. Comparison between the numerical and analytical solutions shows that the analytical approximation provides an excellent estimation for sufficiently large values of the yield stress. Dimensional analysis, which is supported by the analytical model results, reveals the dimensionless groups that govern the problem. For the general case, the melt fraction is a function of two dimensionless groups. For the analytical approximation, it is shown that the melt fraction is governed by a single dimensionless group and that the molten layer thickness is governed by two dimensionless groups.

Mechanics↗