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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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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Calibration of a mesoscale tritium transport model for ceramic breeder materials in TMAP8 using experimental data

Due to the scarcity of the long-term external tritium supply, lithium-containing breeder materials are used in the blanket of fusion reactors to produce tritium faster than the deuterium-tritium fusion reaction consumes it. A cellular breeder is a promising material with higher lithium density and thermal conductivity than conventional ceramic pebbles and enhanced tritium extraction with interconnected pores. Although several experimental and modeling efforts have improved our understanding of tritium transport, the exact mechanisms governing tritium release from breeder materials are still unknown. As a result, current models cannot reliably assess the tritium breeding capabilities of cellular breeder materials. This work presents a tritium transport multiphysics model and calibrates it using experimental data of deuterium absorption and desorption from cellular breeder materials at different temperatures and pressures. This model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. After calibrating the model and performing sensitivity analysis, we discuss pre-dominant mechanisms governing tritium release from cellular breeder materials. The model is part of the Tritium Migration Analysis Program [TMAP8], a multiscale, multiphysics framework for tritium transport based on the finite element multiphysics framework MOOSE. This study demonstrates some of TMAP8’s capabilities and provides insight into the mechanisms governing tritium transport in cellular ceramic breeder materials.

08 HYDROGEN↗
DOE OSTI2015

Enhancing performance assessments using the ASCEM tool-set - 15222

The Office of Soil and Groundwater Remediation within the U.S. Department of Energy's Office of Environmental Management (EM) is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. ASCEM integrates modeling tools into a common work-flow that facilitates integrated approaches to modeling and site characterization, and enables robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project includes collaboration with end users engaged in performance assessments and subsurface simulation. Two working groups are engaged in performance assessment activities at the Hanford Site and Savannah River Site (SRS). The Hanford Site working group is focused on evaluating an alternative conceptual model that includes fine-scale heterogeneities. The baseline conceptual model for the performance assessment includes the large-scale stratigraphy at the site. The working group is applying the ASCEM tool-set to develop and evaluate alternative conceptual models and evaluate the effect of heterogeneities on long-term transport under rainfall-driven conditions. Because the heterogeneous models require long compute times due to increased model complexity, the simulations are implemented on a high-performance computing platform to reduce simulation times. The ASCEM Akuna work-flow enables efficient organization, simulation execution, and processing and visualization of results. Current performance assessments for waste tank closure at the SRS are limited to two-dimensional axi-symmetric representations. The SRS working group is collaborating with the site contractor to address technical review issues by resolving fine-scale tank features and simulating three-dimensional flow with Richards equation for selected closure scenarios using the ASCEM simulator, Amanzi. The Akuna tool-set is being applied to support model setup, sensitivity analysis, uncertainty quantification, and visualization. Both of the ASCEM working groups are addressing issues that cannot readily be evaluated with the existing tools. In these efforts, ASCEM is being used to provide technical underpinnings for ongoing performance assessments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

High pressure shock tube ignition delay time measurements during oxy-methane combustion with high levels of CO 2 dilution

For this study, ignition delay times and methane species time-histories were measured for methane/O 2 mixtures in a high CO 2 diluted environment using shock tube and laser absorption spectroscopy. The experiments were performed between 1300 K and 2000 K at pressures between 6 and 31 atm. The test mixtures were at an equivalence ratio of 1 with CH 4 mole fractions ranging from 3.5% -5% and up to 85% CO 2 with a bath of argon gas as necessary. The ignition delay times and methane time histories were measured using pressure, emission, and laser diagnostics. Predictive ability of two literature kinetic mechanisms (GRI 3.0 and ARAMCO Mech 1.3) was tested against current data. In general, both mechanisms performed reasonably well against measured ignition delay time data. The methane time-histories showed good agreement with the mechanisms for most of the conditions measured. A correlation for ignition delay time was created taking into the different parameters showing that the ignition activation energy for the fuel to be 49.64 kcal/mol. Through a sensitivity analysis, CO 2 is shown to slow the overall reaction rate and increase the ignition delay time. To the best of our knowledge, we present the first shock tube data during ignition of methane/CO 2 /O 2 under these conditions. In conclusion, current data provides crucial validation data needed for development of future kinetic mechanisms.

42 ENGINEERING↗
NASA NTRSDate not supplied

Elastic-Poroelastic Simulation of Locally Resonant Ultrasound for Aging Li-Metal Batteries

An elastic-poroelastic simulation of ultrasound inspection for lithium-metal batteries is presented and compared to empirical reflection spectra measured during battery cycling. Simulated reflection spectra were obtained using a two-dimensional (2D) plane strain model, comprised of dozens of individual microns-thick layers within a Li-metal pouch cell. The simulated reflection spectra were then compared to ultrasonic reflection spectra measurements taken intermittently during cell cycling. A sensitivity analysis and parameter calibration were performed for the pristine pouch cell simulation prior to cycling, providing a baseline to account for difficult to measure poroelastic material parameters. Then, the reduction in solid Li anode thickness and corresponding growth into a mossy lithium layer was modeled to represent aging conditions. Results from both simulations and empirical inspections show similar trends in through-thickness resonance frequencies due to cell aging.

Battery↗
DOE OSTI2015

Integrated gasification and plasma cleaning for waste treatment: A life cycle perspective

Highlights: • A life cycle assessment of an advanced two-stage process is undertaken. • A comparison of the impacts of the process when fed with 7 feedstock is presented. • Sensitivity analysis on the system is performed. • The treatment of RDF shows the lowest impact in terms of both GWP and AP. • The plasma shows a small contribution to the overall impact of the plant. - Abstract: In the past, almost all residual municipal waste in the UK was landfilled without treatment. Recent European waste management directives have promoted the uptake of more sustainable treatment technologies, especially for biodegradable waste. Local authorities have started considering other options for dealing with residual waste. In this study, a life cycle assessment of a future 20 MWe plant using an advanced two-stage gasification and plasma technology is undertaken. This plant can thermally treat waste feedstocks with different composition and heating value to produce electricity, steam and a vitrified product. The objective of the study is to analyse the environmental impacts of the process when fed with seven different feedstocks (including municipal solid waste, solid refuse fuel, reuse-derived fuel, wood biomass and commercial & industrial waste) and identify the process steps which contribute more to the environmental burden. A scenario analysis on key processes, such as oxygen production technology, metal recovery and the appropriate choice for the secondary market aggregate material, is performed. The influence of accounting for the biogenic carbon content in the waste from the calculations of the global warming potential is also shown. Results show that the treatment of the refuse-derived fuel has the lowest impact in terms of both global warming potential and acidification potential because of its high heating value. For all the other impact categories analysed, the two-stage gasification and plasma process shows a negative impact for all the waste streams considered, mainly due to the avoided burdens associated with the production of electricity from the plant. The plasma convertor, key characteristic of the thermal process investigated, although utilising electricity shows a relatively small contribution to the overall environmental impact of the plant. The results do not significantly vary in the scenario analysis. Accounting for biogenic carbon enhanced the performance of biomass and refuse-derived fuel in terms of global warming potential. The main analysis of this study has been performed from a waste management perspective, using 1 ton of waste as functional unit. A comparison of the results when 1 kWhe of electricity produced is used as functional unit shows similar trends for the environmental impact categories considered.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Realistic Geochemical Parameter Uncertainty for Performance Assessment Modeling - 17066

Performance assessments (PAs) include uncertain geochemical parameters that affect the fate and transport of contaminants in environmental media, such as partitioning coefficients for water/rock (K{sub d}) and water/air (K{sub H}), diffusion coefficients, and aqueous solubilities. A statistical approach to realistic, as opposed to 'conservative,' stochastic distribution development for geochemical parameters is presented here. For contaminants not identified as focus elements during screening, broad generic distributions are developed. If any parameter is flagged in the subsequent model sensitivity analysis (SA), it becomes a focus element for further research during the next round of distribution development. This iterative approach is efficient and technically defensible at each stage. Data are collected in databases and may be appropriately weighted or filtered. In the relatively few cases where data exist from local or analogous rocks, those data may be prioritized. Once established, the databases can be used for future PAs or other environmental models and can be expanded as needed based on model SA results, additional screening, and as additional relevant data become available. The iterative method is demonstrated for K{sub d} and K{sub H} in a PA model for a radioactive waste disposal facility. An SA was performed based on preliminary geochemical parameter distributions that showed certain model endpoints are sensitive to K{sub d} and K{sub H} values for some contaminants. This underscores the importance of including realistic uncertainty in these geochemical parameters. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Kriging-Based Inverse Uncertainty Quantification of BISON Fission Gas Release Model

Nuclear reactor fuel performance analysis studies the thermo-mechanical behavior of fuel rods and verify their compliance with safety criteria under both normal operation and accidental conditions. One of the major concerns in fuel performance analysis is the behavior of the fission gases xenon and krypton in uranium dioxide fuel, which significantly affect the thermo-mechanical performance of the nuclear fuel rods employed in current LWRs. Previously, the modeling of fission gas release (FGR) in nuclear fuel performance codes have been relying on empirical models which are not applicable beyond their range of calibration. Recently a more efficient and flexible physics-based FGR and swelling model that can describe a wider range of reactor operation conditions have been implemented in fuel performance code BISON. In this work, we performed Bayesian calibration to inversely quantify the uncertainties associated with the 5 tuning parameters in BISON FGR model, based on the time-dependent FGR measurement data from Riso-AN3 benchmark. It takes around 1 hour and 40 minutes for BISON to simulate the Riso-AN3 benchmark with a moderate mesh size using 32 processors. As hundreds of thousands of BISON simulations are needed during Markov Chain Monte Carlo (MCMC) sampling, running BISON directly is not a viable solution. Therefore we propose to use Kriging-based metamodels to replace BISON during MCMC sampling. Surrogate model is an approximation of the input/output relation of a computer code/model. It is also called metamodel, response surface, emulator. Surrogate models usually take much less computational time than the original model (like BISON) while maintaining the input/output relation of the original model to a desirable accuracy. Constructing the metamodels normally requires small number of executions of the original model. Once validated, metamodels can be used to perform uncertainty and sensitivity analysis, Bayesian calibration, optimization, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Effect of Reaction Kinetics on Graphene-Edge Morphology and Composition

New simulations of graphene growth in flame environments are presented. The simulations employed a kinetic Monte Carlo (KMC) algorithm coupled to molecular mechanics (MM) geometry optimization to track individual graphenic species as they evolve. Focus was given to incorporation of five-member rings and resulting curvature and edge defects. The model code was re-written to be more computationally efficient enabling a larger set of simulations to be run, decreasing stochastic fluctuations in the averaged results. The model also included updated rate coefficients for graphene edge reactions recently published in the literature. Sensitivity analysis, enabled by the more efficient coding, confirmed the importance of the updated rates as well as providing further insight on key reactions controlling layer growth and morphology. The new KMC code was applied to simulate graphene-layer growth in the environments of laminar premixed flames. Finally, in these flame simulations, C-H ratios of evolving structures were computed and compared to those from experiment and from an alternate model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Modeling of stagnation-line nonequilibrium flows by means of quantum based collisional models

The stagnation-line flow over re-entry bodies is analyzed by means of a quantum based collisional model which accounts for dissociation and energy transfer in N{sub 2}-N interactions. The physical model is based on a kinetic database developed at NASA Ames Research Center. The reduction of the kinetic mechanism is achieved by lumping the rovibrational energy levels of the N{sub 2} molecule in energy bins. The energy bins are treated as separate species, thus allowing for non-Boltzmann distributions of their populations. The governing equations are discretized in space by means of the Finite Volume method. A fully implicit time-integration is used to obtain steady-state solutions. The results show that the population of the energy bins strongly deviate from a Boltzmann distribution close to the shock wave and across the boundary layer. The sensitivity analysis to the number of energy bins reveals that accurate estimation of flow quantities (such as chemical composition and wall heat flux) can be obtained by using only 10 energy bins. A comparison with the predictions obtained by means of conventional multi-temperature models indicates that the former can lead to an overestimation of the wall heat flux, due to an inaccurate modeling of recombination in the boundary layer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Inferring Atmospheric Release Characteristics in a Large Computer Experiment using Bayesian Adaptive Splines

An atmospheric release of hazardous material, whether accidental or intentional, can be catastrophic for those in the path of the plume. Predicting the path of a plume based on characteristics of the release (location, amount and duration) and meteorological conditions is an active research area highly relevant for emergency and long-term response to these releases. As a result, researchers have developed particle dispersion simulators to provide plume path predictions that incorporate release characteristics and meteorological conditions. However, since release characteristics and meteorological conditions are often unknown, the inverse problem is of great interest, that is, based on all the observations of the plume so far, what can be inferred about the release characteristics? This is the question we seek to answer using plume observations from a controlled release at the Diablo Canyon Nuclear Power Plant in Central California. With access to a large number of evaluations of a computationally expensive particle dispersion simulator that includes continuous and categorical inputs and spatio-temporal output, building a fast statistical surrogate model (or emulator) presents many statistical challenges, but is an essential tool for inverse modeling and sensitivity analysis. We achieve accurate emulation using Bayesian adaptive splines to model weights on empirical orthogonal functions. Here, we use this emulator as well as appropriately identifiable simulator discrepancy and observational error models to calibrate the simulator, thus finding a posterior distribution of characteristics of the release. Since the release was controlled, these characteristics are known, making it possible to compare our findings to the truth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Impact of Rock Wettability and Mineralization on CO 2 Storage Efficiency in Basalt Reservoirs

Basalt formations have emerged as highly promising targets for geological CO 2 storage due to their abundance of reactive silicate minerals that can rapidly convert dissolved CO 2 into stable carbonate minerals. The efficiency of CO 2 trapping in basalts, however, depends not only on their geochemical reactivity but also on reservoir wettability, which governs how CO 2 partitions among structural, residual, solubility, and mineral trapping mechanisms. However, wettability and mineral kinetics have largely been examined separately, wettability for plume migration and kinetics in terms of mineralization, leaving their coupled impact unquantified. Here, we systematically integrate th ese processes in a reservoir-scale reactive transport model to quantify the impact of three distinct wettability conditions (water-wet, mixed-wet, and CO 2 -wet) on plume migration, mineral precipitation, pore-scale blockage, and long-term immobilization. Results show that under ideal conditions (no mineralization), water-wet systems exhibited plume aspect ratios up to 28% higher than CO 2 -wet systems and promoted at least 60% greater residual trapping. When mineralization was incorporated, mineral trapping accounted for 57%, 53%, and 46% of the total immobilized CO 2 in water-wet, mixed-wet, and CO 2 -wet systems, respectively. Dissolved CO 2 contributed 43-46%, while residual trapping remained below 5%, and mobile CO 2 was substantially reduced due to mineralization, demonstrating that as the system becomes more water-wet, CO 2 is more effectively converted into stable carbonate minerals, although extensive mineral precipitation may lead to pore clogging. A global Sobol-Morris sensitivity analysis further reveals that the kinetic parameters of reactive minerals are the most influential factor, followed by wettability, while salinity has only a minor influence. Furthermore, these findings highlight that wettability is not merely a flow property but a fundamental control on CO 2 mineralization in basalts, with direct implications for site selection for storage projects.

Basalts↗
DOE OSTI2016

Sequential experimental design based generalised ANOVA

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

NMDQi Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST)

The Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST) is developed to support the thermal-hydraulic aspects for the design of optimal irradiation vehicles for the Nuclear Materials Discovery and Qualification initiative (NMDQi). TOAST is currently a MATLAB-based tool that utilizes a simplified steady-state analytical model where a radial thermal resistance circuit is utilized to account for conduction through up to 2 capsules, a gas gap, a thermal bond, a sample cladding, and a sample, as well as the convection from a water coolant outside the capsules. The geometry is discretized axially along the user-defined height of a basket with a user-defined number of points/nodes, essentially turning TOAST into a semi-2D heat transfer analysis utility for cylindrical irradiation vehicles with practically any configuration, solving for temperatures radially at multiple axial locations. TOAST utilizes a Graphical User Interface (GUI) in-which a user can define the geometrical layout, the materials utilized for each component, the coolant characteristics, and the required solution. The user can define the geometry by inputting the diameters, thicknesses, and heights for each component, whereas the materials are defined via the user-provided constant or variable thermal conductivities. The user can select the coolant's inlet temperature, pressure, and the pressure drop across the height of the problem (which is used to calculate the velocity of the flow). Finally, the user can choose to solve for a sample heat generation rate limit by inputting temperature limits for the sample and capsules or can choose to purely solve for the axial temperature distributions of each component by inputting a pre-selected heat generation rate. Either way, TOAST provides the user with axial temperature distributions of all the components including the coolant, and the heat generation rate limit as well as the maximum outlet coolant temperature. The user can also choose to do one of 6 sensitivity analyses in TOAST. The sensitivity analyses yield plots of the sensitivity of the heat generation rate limit, the maximum coolant temperature, and the pressure limit for the annular components due to perturbations in 1-2 unknown variables based on the selected sensitivity analysis. Benchmarks between computations in TOAST and equivalent 2D axis symmetric ABAQUS models are presented, showing that TOAST results are within less than 3% of ABAQUS results in most cases, and a maximum of 8% difference in some cases. The benchmarks also revealed that this uncertainty is tied to the selection of an appropriate Nusselt number correlation and appropriate thermal conductivities, which the user can do from the GUI. Regardless, TOAST is demonstrated as a computationally efficient, highly accessible, and accurate utility for optimization and scoping s of studies different irradiation vehicles.

42 ENGINEERING↗
DOE OSTI2024

Ignition Delay Times and Chemical Kinetic Model Validation for Hydrogen and Ammonia Blending With Natural Gas at Gas Turbine Relevant Conditions

Ignition delay times from undiluted mixtures of natural gas (NG)/H 2 /Air and NG/NH 3 /Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000 and 1500 K near a constant pressure of 25 bar. As mentioned, mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data are compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H 2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH 3 fuel addition made no noticeable difference in ignition time. NG/NH 3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis. Here, the reaction CH 3 + O 2 = CH 3 O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Modular evaluation method for subsurface activities (MEMSA). A novel approach for integrating social acceptance in a permit decision-making process for subsurface activities

We investigate how the decision support system ‘Modular Evaluation Method Subsurface Activities’ (MEMSA) can help facilitate an informed decision-making process for permit applications of subsurface activities. To this end, we analyze the extent the MEMSA approach allows for a dialogue between stakeholders in a transparent manner. We use the exploration permit for the underground gas storage facility at the Pieterburen salt dome (Netherlands) as a case study. The results suggest that the MEMSA approach is flexible enough to adjust to changing conditions. Furthermore, MEMSA provides a novel way for identifying structural problems and possible solutions in permit decision-making processes for subsurface activities, on the basis of the sensitivity analysis of intermediate rankings. We suggest that the planned size of an activity should already be specified in the exploration phase, because this would allow for a more efficient use of the subsurface as a whole. We conclude that the host community should be involved to a greater extent and in an early phase of the permit decision-making process, for example, already during the initial analysis of the project area of a subsurface activity. We suggest that strategic national policy goals are to be re-evaluated on a regular basis, in the form of a strategic vision for the subsurface, to account for timing discrepancies between the realization of activities and policy deadlines, because this discrepancy can have a large impact on the necessity and therefore acceptance of a subsurface activity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Process-informed adsorbent design guidelines for direct air capture

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the development of new adsorbents. However, there is a discord between the adsorbent design and process performance. Many materials scientists focus on maximising metrics such as the CO 2 capacity of their adsorbent. Here, we combine detailed process modelling, machine learning, and extensive global sensitivity analysis, which entails varying all of the model parameters together, on a direct air capture process to show that the dry CO 2 adsorption capacity does not influence process performance for an amine-functionalised adsorbent operating in a temperature vacuum swing adsorption (TVSA) process, while it is important in a steam-assisted TVSA (S-TVSA) process. In fact, adsorption kinetics, density, and thermal conductivity are all critical attributes to obtaining a low energy penalty and reduced costs. The analysis also highlights the importance of heat transfer, directing process engineers to (alternative) adsorber designs that maximise this. By an in-depth evaluation of how process performance indicators are affected by materials properties and process operating parameters, this work provides guidance to both material scientists and process engineers towards the design of a “unicorn adsorbent” and intensified DAC processes. This will improve the performance of solid adsorbent direct air capture and help drive down the costs of this vital technology to avert the worst impacts of climate change.

42 ENGINEERING↗
DOE OSTI2019

Development of control quality factor for HVAC control loop performance assessment I—Methodology (ASHRAE RP-1587)

This article is the second paper from the ASHRAE research project RP-1587, focusing on the methodology of obtaining a control quality factor (CQF). This article presents a development of two CQFs for assessing the heating, ventilation, and air-conditioning (HVAC) control loop performance. Both CQFs are able to detect whether the control loop is able to maintain the setpoint and identify the loop's ability to handle disturbances. In addition, the reversal behaviors are assessed as well. The first CQF (CQF-Harris) is proposed based on the normalized Harris index using the recursive least squares method. This recursive least squares method is selected because of its computational efficiency compared with the maximum likelihood estimation method. The second CQF (CQF-EWMA) is based on the exponentially weighted moving average of the error ratio. The assessment scale of excellent, good, fair, bad, and failed, which indicates the quality of the HVAC control loops, is established as well. The sensitivity analysis for both CQFs is also conducted, and it provides insights on choosing the appropriate parameters to compute such CQFs. Such parameters include the sampling frequency, the length of the moving window, and the variance of the unmeasured disturbance. The field evaluations and tests of the proposed CQFs for simulated control loops and real control loops can be found in the companion paper with the title 'Development of Control Quality Factor for HVAC Control Loop Performance Assessment - III: Field Testing and Results (ASHRAE RP-1587).'

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Assessment of model parameters in MFiX particle-in-cell approach

The limitations in numerical treatment of solids-phase in conventional methods like Discrete Element Model and Two-Fluid Model have facilitated the development of alternative techniques such as Particle-In-Cell (PIC). However, a number of parameters are involved in PIC due to its empiricism. In this work, global sensitivity analysis of PIC model parameters is performed under three distinct operating regimes common in chemical engineering applications, viz. settling bed, bubbling fluidized bed and circulating fluidized bed. Simulations were performed using the PIC method in Multiphase Flow with Interphase eXchanges (MFiX) developed by National Energy Technology Laboratory (NETL). A non-intrusive uncertainty quantification (UQ) based approach is applied using Nodeworks to first construct an adequate surrogate model and then identify the most influential parameters in each case. This knowledge will aid in developing an effective design of experiments and determine optimal parameters through techniques such as deterministic or statistical calibration.

01 COAL, LIGNITE, AND PEAT↗