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At least 379 records · Page 21

On the capillary pressure function in porous media based on relative permeabilities of two immiscible fluids: Application of capillary bundle models and validation using experimental data

The objective of this paper is to extend the theoretical approach and an analytical solution, which was proposed by Babchin and Faybishenko (2014), for the evaluation of a capillary pressure (P c ) curve in porous media based on the apparent specific surface area, using an explicit combination of the relative permeability functions for the wetting and nonwetting phases. Specifically, in the current paper, the authors extended this approach by the application of two types of capillary bundle models with different formulations of effective capillary radius formulae. The application of the new models allowed the authors to improve the results of calculations of the effective average contact angle given in the paper by Babchin and Faybishenko (2014). The validation of the new models for calculations of the P c curve is also given in this paper using the results of a specifically designed core experiment, which was originally conducted by Ayub and Bentsen (2001).

58 GEOSCIENCES↗

Process Model-Based Validation of the Intensification of Biomass Fast Pyrolysis in a Fluidized Bed via Autothermal Operation

A model for the fluidized-bed pyrolysis of biomass is extended to enable the simulation of intensified autothermal operation. In this system, partial oxidation of char and pyrolysate species replaces an external heat source to supply the enthalpy of pyrolysis, greatly increasing the throughput of a given fast pyrolysis reactor. Oxidation reactions are compiled from CRECK and other literature sources and extended to cover the species found in pyrolysis products, including a derivation of the catalytic effect of ash on char combustion from experimental studies at Iowa State University (ISU). Results indicate a roughly 3-fold increase in biomass throughput for a given reactor volume at the pilot scale with minimal loss of valuable products, in agreement with published data from the 3 × 10 -2 m 3 reactor operated by ISU. Additionally, a proposal for a 250 ton/day commercial-scale biomass pyrolysis reactor is analyzed, showing that the same size reactor operated by heating the fluidizing gas externally would have only one-tenth the capacity; if operated by heating the sand externally, the sand would need to circulate at an impractical 0.7 bed volume per minute rate to maintain a 250 ton/day biomass throughput.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical calibration and validation framework of bench-scale computational fluid dynamics simulations for solvent-based carbon capture. Part 2: Chemical absorption across a wetted wall column: Original Research Article: Hierarchical calibration and validation framework of bench-scale computational fluid dynamics simulations

Part 1 of this paper presents a numerical model for non-reactive physical mass transfer across a wetted wall column (WWC). In Part 2, we improved the existing computational fluid dynamics (CFD) model to simulate chemical absorption occurring in a WWC as a bench-scale study of solvent-based carbon dioxide (CO 2 ) capture. In this study, to generate data for WWC model validation, CO 2 mass transfer across a monoethanolamine (MEA) solvent was first measured on a WWC experimental apparatus. The numerical model developed in this work can account for both chemical absorption and desorption of CO 2 in MEA. In addition, the overall mass transfer coefficient predicted using traditional/empirical correlations is conducted and compared with CFD prediction results for both steady and wavy falling films. A Bayesian statistical calibration algorithm is adopted to calibrate the reaction rate constants in chemical absorption/desorption of CO 2 across a falling film of MEA. The posterior distributions of the two transport properties, i.e., Henry's constant and gas diffusivity in the non-reacting nitrous oxide (N 2 O)/MEA system obtained from Part 1 of this study, serves as priors for the calibration of CO 2 reaction rate constants after using the N 2 O/CO 2 analogy method. Finally, the calibrated model can be used to predict the CO 2 mass transfer in a WWC for a wider range of operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

36 MATERIALS SCIENCE↗

Vacuum-assisted carbon molecular sieve membrane reactor for non-oxidative ethane dehydrogenation

Non-oxidative ethane dehydrogenation (EDH) is equilibrium-limited and endothermic. Selective hydrogen removal using a gas-permeable membrane within the EDH reaction zone can overcome the thermodynamic equilibrium, enabling higher ethane conversions. Employing vacuum as the permeation driving force, rather than a sweep gas, enhances the industrial viability of membrane reactors by eliminating additional post-reaction separation units. This study presents a membrane reactor that integrates H 2 -permeable carbon molecular sieve (CMS) hollow fiber membranes embedded in a fixed bed of cobalt in a dealuminated beta zeolite (Co@DeAl-BEA) catalyst, utilizing a vacuum to remove hydrogen efficiently. The CMS membrane exhibits high hydrogen permeance and an excellent H 2 /C 2 H 6 separation factor. The membrane reactor significantly enhanced the ethane conversion under reaction conditions comparable to those reported in the literature. A Langmuir-Hinshelwood kinetic rate expression was developed and incorporated into a one-dimensional steady-state reactor model. The experimentally validated model indicates that increasing the number of hollow fibers improves ethane conversion, although ethane loss to the permeate limits the benefit. The contact area between the catalyst and the membrane limits the reactor performance more than the catalytic throughput. Furthermore, we find that the location of the catalyst packing relative to the hollow fiber membranes influences ethane loss and conversion. Higher reactor pressures and inlet ethane flow rates improve space-time yield at the expense of lower ethane conversion. Increasing reactor temperature or packing length promotes both performance metrics. The EDH membrane reactor demonstrated durability over 200 h of continuous operation, maintaining record-low deactivation rates and high ethylene selectivity. Protocols for catalyst regeneration were developed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Analysis of contact conditions and microstructure evolution in shear assisted processing and extrusion using smoothed particle hydrodynamics method

Shear assisted processing and extrusion (ShAPE) is a solid-phase processing technique that adds an additional shear force as compared with a conventional extrusion approach. Recently, ShAPE has demonstrated the capability of extruding high-performance aluminum alloy 7075 (AA7075) tubes at speeds up to 12.2 m/min without surface tearing. However, the relationship among the ShAPE processing parameters, thermomechanical conditions, contact conditions, heat generation, and microstructure evolution remains primarily empirical because an insightful understanding of the associated physics is still lacking. To help elucidate these relationships, this work proposes a thermomechanical meshfree model for the first time for ShAPE processing of AA7075 using the smoothed particle hydrodynamics (SPH) method. The meshfree model is first validated thoroughly by experimental data in terms of material flow, die face temperature, and extrusion force with various processing parameters. The validated model is then used to analyze the steady-state contact conditions and heat generation rates during ShAPE processing. Distributions of the average grain size of AA7075 being extruded are calculated using the SPH model output. The meshfree model results reveal that extrusions conducted at lower temperatures and higher strain rates yield more refined grains and possibly higher material strength, which is also consistent with the experimental observations.

36 MATERIALS SCIENCE↗

Machine Learning Force Field Parameters from Ab Initio Data

Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. Our results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.

97 MATHEMATICS AND COMPUTING↗

Challenges and Opportunities in Magnetospheric Space Weather Prediction

Abstract Space Weather is the study of the dynamics of the coupled Solar‐Terrestrial environment, as these dynamics impact technological systems and human activity. This paper reviews a selection of the advances, challenges, and new opportunities for magnetospheric space weather, and while the focus is on specific phenomena, many other aspects of space weather will have similar challenges and needs. As a scientific field with direct applications, the field of space weather is partly driven by imperatives from both policy and operations. We provide an introduction to some of the context in which the field exists and discuss how this might shape future developments and norms within the space weather enterprise. We briefly examine benchmarking, as a policy and operationally driven activity, as it provides immediate societal relevance and an opportunity to stretch scientific understanding. As numerical space weather prediction now becomes routine, and exascale computing is in the near future, we identify challenges relating to computational expense and big data, capturing and accounting for uncertainties, and specification of boundary conditions. Here, as with the observations supporting numerical space weather prediction, the key challenge lies in extending the lead time of predictions. We also discuss the role of data, particularly in regard to model validation and empirical modeling. Due to the growing societal impact of space weather, we also examine the relationships between space weather and its terrestrial counterpart and look at the importance of continuous evaluation, monitoring progress in predictive capability, and communication with researchers, forecasters, and end users.

79 ASTRONOMY AND ASTROPHYSICS↗

Quench protection studies of the 11-T Nb 3 Sn dipole for the LHC upgrade

The planned upgrade of the LHC collimation system foresees additional collimators to be installed in the dispersion suppressor areas. Fermilab and CERN are developing an 11 T Nb 3 Sn dipole to replace some 8.33 T-15-m-long Nb-Ti LHC main dipoles providing longitudinal space for the collimators. In case of a quench, the large stored energy and the low copper stabilizer fraction make the protection of the 11 T Nb 3 Sn dipoles challenging. This paper presents the results of quench protection analysis, including quench protection heater design and efficiency, quench propagation and coil heating. The numerical results are compared with the experimental data from the 2-m-long Nb 3 Sn dipole models. Here, the validated model is used to predict the current decay and hot spot temperature under operating conditions in the LHC and the presently foreseen magnet protection scheme is discussed.

43 PARTICLE ACCELERATORS↗

Direct Utilization of Coal Syngas in High Temperature Fuel Cells

This EPSCoR project had two primary goals: (i) to build infrastructure and work force at WVU to support long-term research in the area of fuel cells and related sciences; (ii) study effects of various impurities found in coal-syngas on performance of Solid Oxide Fuel Cells (SOFC). As detailed in this report the WVU research team has made significant accomplishments in both of these areas. What follows is a brief summary of these accomplishments: State-of-the-art test facilities and diagnostic tools have been built and put into use. These include cell manufacturing, half-cell and full-cell test benches, XPS, XRD, TEM, Raman, EDAX, SEM, EIS, and ESEM equipment, unique in-situ measurement techniques and test benches (Environmental EM, Transient Mass-Spectrometer-MS, and IR Optical Temperature measurements). In addition, computational capabilities have been developed culminating in a multi-scale multi-physics fuel cell simulation code, DREAM-SOFC, as well as a Beowulf cluster with 64 CPU units. We have trained 16 graduate students, 10 postdoctoral fellows, and recruited 4 new young faculty members who have actively participated in the EPSCoR project. All four of these faculty members have already been promoted to the tenured associate professor level. With the help of these faculty and students, we were able to secure 14 research awards/contracts amounting to a total of circa $5.0 Million external funding in closely related areas of research. Using the facilities mentioned above, the effects of PH3, HCl, Cl2, and H2S on cell performance have been studied in detail, mechanisms have been identified, and also remedies have been proposed and demonstrated in the laboratory. For example, it has been determined that PH3 reacts rapidly with Ni to from secondary compounds which may become softer or even melt at high temperature and then induce Ni migration to the surface of the cell changing the material and micro-structural properties of the cell drastically. It is found that the extent of steam and current load accelerate the degradation caused by PH3. A unique filtering technique has been proposed to reduce the effect of PH3. In addition, various cell materials have been proposed to reduce the rate of degradation caused by H2S. Furthermore, a three-dimensional, transient multi-physics model has been formulated to describe primary transport processes and electro-chemical reactions occurring within the cell. This model has been validated using data gathered from accelerated tests. The validated model then has been used to study the degradation rates under a range of operating conditions and impurity levels. This has resulted in a procedure that uses both experiments and simulations to predict the life-time of a cell operating with syngas with known concentration of trace impurities. Finally all the experience and knowledge gained has been disseminated via 39 journal papers and 43 presentations/posters/conference papers.

01 COAL, LIGNITE, AND PEAT↗

Development and Validation of Accident Models for FeCrAl Cladding

The purpose of this milestone report is to present the work completed in regards to material model development for FeCrAl cladding and highlight the results of applying these models to Loss of Coolant Accidents (LOCA) and Station Blackouts (SBO). With the limited experimental data available (essentially only the data used to create the models) true validation is not possible. In the absence of another alternative, qualitative comparisons during postulated accident scenarios between FeCrAl and Zircaloy-4 cladded rods have been completed demonstrating the superior performance of FeCrAl.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and Validation of Accident Models for U 3 Si 2

The purpose of this milestone report is to present the work completed in regards to material model development for U 3 Si 2 fuel and highlight the results of applying these models to Reactivity Initiated Accidents (RIA), Loss of Coolant Accidents (LOCA), and Station Blackouts (SBO). With the limited experimental data available (essentially only the data used to create the models) true validation is not possible. In the absence of another alternative, code-to-code comparisons have been completed. Qualitative comparisons during postulated accident scenarios between U 3 Si 2 and UO 2 fueled rods have also been completed demonstrating the superior performance of U 3 Si 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SCM-Forcing Data

Single-Column Model (SCM) Forcing Data are derived from the ARM facility observational data using the constrained variational analysis approach (Zhang and Lin 1997 and Zhang et al., 2001). The resulting products include both the large-scale forcing terms and the evaluation fields, which can be used for driving the SCMs and Cloud Resolving Models (CRMs) and validating model simulations.

54 ENVIRONMENTAL SCIENCES↗

Bifacial Vertical Testbed and Ground Irradiance Data in Golden, Colorado

This data was collected for Tonita et al., “Vertical bifacial photovoltaic system model validation: study with field data, various orientations, and latitudes,” for validation of optical models for vertically-oriented photovoltaics under high albedo. Ground irradiance data for vertical PV arrays modeling in agrivoltaics is also provided. The dataset is provided for further use or study as open source. For any questions on the dataset, email silvana.ovaitt@nlr.gov.

14 SOLAR ENERGY↗

Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses

Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. The validated models will be used to optimize performance of the Stillwater hybrid plant and explore next-generation hybrid plant design concepts. A preliminary effort to improve performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error. Subsequent analyses of the optical characterization results indicate that the solar field is currently operating at approximately 90% of the manufacturer’s performance specifications. Control system and hardware modifications expected to improve solar array performance by XX% have been identified.

14 SOLAR ENERGY↗

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present paper, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to develop significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modeling and Validation of Irradiation Damage in Ni-based Alloys for Long-Term LWR Applications (Final Report)

As light water reactor (LWR) plant lives are extended, the need for predictive modeling tools for materials degradation increase in order to ensure safe operation and plan for component replacements. The Grizzly code, which is built on the MOOSE multi-physics simulation environment, is being developed for exactly this purpose. To extend Grizzly to include capabilities for modeling Ni-based alloys, we propose a US/UK integrated program to address thermal and irradiation-induced transformations mechanisms of Alloys 690 and 625. Alloy 690 is widely used in existing LWR plants due to its superior stress corrosion cracking (SCC) resistance compared to Alloy 600. Alloy 625 is used in more limited applications but offers the benefits of both high strength (in the aged condition) and corrosion/SCC resistance. Research has shown that both alloys can undergo phase changes due to thermal or irradiation exposure. In the precipitation-hardened condition, Alloy 625 “softens” during neutron irradiation as the strengthening precipitates decompose and metastable precipitates form. However, the nature and rates of these transformations as a function of exposure conditions are not well understood. Similarly, the effects of these thermal and irradiation-induced microstructural changes on mechanical properties require evaluation. The proposed program combines thermal and irradiation experiments, mechanical testing, microstructural characterization using state-of-the art analytical techniques, atomistic modeling, micro-and macro-scale modeling via Grizzly. This multi-pronged approach yields several benefits: 1) atomistic scale models capture the physics of the mechanisms of phase transformations, which can be generalized to other systems, 2) the modeling results (from atomistic to continuum) will be validated experimentally to ensure the predictive aspect, 3) the microstructure/property relationships captured with mechanical testing provides information at the engineering scale that is needed to validate the integration of the proposed new capability into Grizzly

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗