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At least 1,351 records · Page 75

Preliminary Nuclear Containment Vessel Modeling for Multi-Hazard Probabilistic Risk Assessment under Seismic Hazards and Concrete Degradation

The current practice for natural phenomena hazards (NPH) risk assessment of nuclear facilities is to compute the risk for each hazard independently and then compound the total risk as a combination of single hazard risks. This state of practice does not consider correlations between hazards and the cascading impacts to structures, systems, and components (SSCs), and could thus underestimate the NPH risk or overestimate the nuclear facility safety. Events such as the Fukushima Daiichi accident have highlighted the importance of multi-hazard risk considerations to nuclear power plants (NPPs) that quantify the cascading damage effects to SSCs in the risk models. Moreover, the current fleet of NPPs in the United States is aging; these NPPs are now expected to operate well beyond their initially planned design life. Aging-related deterioration can potentially decrease the capacity of critical structures such as containment vessels to withstand NPH. Such aging considerations may not be adequately accounted for by the current NPH risk assessment guidelines. This paper presents a preliminary modeling and simulation of a representative reinforced concrete containment vessel subjected to seismic mainshock and aftershock considering concrete degradation due to alkali silica reaction. The broader aim is to develop multi-hazard time-dependent fragility functions that could be subsequently used in the probabilistic risk assessment (PRA) model. The multi-hazard component comes into play due to the consideration of damage to the containment vessel under seismic loads and concrete degradation. Consideration of concrete degradation also brings into play the time-dependent nature of the containment vessel response. The response of the containment vessel under varying degrees of concrete degradation to seismic loads is investigated. The results presented are simulated using the Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) software for seismic analysis and the Blackbear software for concrete degradation and damage modeling. Both software are open source and developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE).

42 ENGINEERING↗

Full-System Linearization for Floating Offshore Wind Turbines in OpenFAST: Preprint

The wind engineering community relies on multiphysics engineering software to run nonlinear time-domain simulations, e.g. for design-standards-based loads analysis. Although most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear system equations is often advantageous to understand the system properties and exploit well-established methods and tools for analyzing linear systems. This paper presents the development of the new linearization functionality of the open-source engineering tool OpenFAST for floating offshore wind turbines (FOWTs), as well as the concepts and mathematical background needed to understand and apply it correctly.

17 WIND ENERGY↗

New Developments and Verification of the Fusion Blanket Simulation Capabilities in the MOOSE Framework

This poster contains new developments and updates in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework related to fusion modeling and simulation, and forms the basis for an on-going effort in modeling whole fusion devices at Idaho National Laboratory using MOOSE. In this work, a slice of the midplane of a proposed ceramic breeder blanket design for the Fusion Nuclear Science Facility is simulated using a combination of neutronics, 1D system level thermal hydraulics for helium, 3D heat conduction, and tritium transport. Previous work focused on the engineering scale full assembly of a blanket sector, but the simulations here form the basis for software quality and verification efforts to increase confidence as the large scale simulations continue. This poster was presented at the Idaho National Laboratory Intern Poster Session 2023.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Online simulation powered learning modules for materials science

Simulation tools are playing a significant role in materials science and engineering and beyond their well established importance in research and development, these tools have a vital pedagogical potential. We describe a set of online simulation tools and learning modules designed to help students explore important concepts in materials science where hands-on activities with high-fidelity simulations can provide insight not easily acquired otherwise. The online tools, which involve density functional theory and molecular dynamics simulations, have been designed with non-expert end-users in mind and only a few clicks are required to perform most simulations, yet they are powered by research-grade codes and expert users can access advanced options. All tools and modules are available for online simulation in nanoHUB.org and access is open and free of charge. Importantly, instructors and students do not need to download or install any software. The learning modules cover a range of topics from electronic structure of crystals and doping, plastic deformation in metals, and physical properties of polymers. These modules have been utilized in several core undergraduate courses at Purdue’s School of Materials Engineering, they are self contained, and are easy to incorporate into existing classes.

36 MATERIALS SCIENCE↗

Combined crystal plasticity and grain boundary modeling of creep in ferritic-martensitic steels: II. The effect of stress and temperature on engineering and microstructural properties

This paper describes a series of physically-based crystal plasticity finite element method (CPFEM) simulations of long-term creep and creep rupture of Grade 91 steel. It is Part 2 of a two part series of papers. Part 1 describes the simulation framework; this part focuses on specific simulations and on how the predicted long-term creep properties of Grade 91 compare to the assumptions used in current high temperature design practices. This work extends the model developed in Part 1 to look at creep properties at different temperatures, principal stresses, and multiaxial stress states. The simulations show that empirically extrapolating creep rupture stresses from short-term experimental data may substantially over predict the actual long-term creep properties of Grade 91. Additionally, the CPFEM calculations predict a transition from notch strengthening creep behavior for high values of maximum principal stress and moderate notch severity to notch weakening behavior for low principal stresses and more severe notches. The latter regime better categorizes conditions in engineering components designed for long term elevated temperature use, which implies Grade 91 may be a notch weakening material in actual service. This would have a significant impact on high temperature design practices, though confirmatory test data on long-life, low stress notched specimens is difficult to obtain. Finally, one advantage of the physically-based modeling approach adopted here is that the simulation results also elucidate the microstructural mechanisms causing the macroscopic trends in engineering properties predicted by the simulations. This paper shows that the detailed micromechanical mechanisms predicted by the CPFEM simulations can be abstracted with a simple micromechanical model that can be used to both explain the detailed results and make improved predictions of engineering properties from experimental data.

36 MATERIALS SCIENCE↗

Trilinos Developers SQE Guide: ASC Software Quality Engineering Practices Version 3.0

The Trilinos Project is an effort to develop algorithms and enabling technologies within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. A new software capability is introduced into Trilinos as a package. A Trilinos package is an integral unit and, although there are exceptions such as utility packages, each package is typically developed by a small team of experts in a particular algorithms area such as algebraic preconditioners, nonlinear solvers, etc. The Trilinos Developers SQE Guide is a resource for Trilinos package developers who are working under Advanced Simulation and Computing (ASC) and are therefore subject to the ASC Software Quality Engineering Practices as described in the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan: ASC Software Quality Engineering Practices Version 3.0 document. The Trilinos Developer Policies webpage contains a lot of detailed information that is essential for all Trilinos developers. The Trilinos Software Lifecycle Model defines the default lifecycle model for Trilinos packages and provides a context for many of the practices listed in this document.

Willenbring, James Michael↗

New Automotive Air Conditioning System Simulation Tool Developed in MATLAB/Simulink

Further improvements in vehicle fuel efficiency require accurate evaluation of the vehicle's transient total power requirement. When operated, the air conditioning (A/C) system is the largest auxiliary load on a vehicle; therefore, accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation software, such as 'Autonomie,' has been used by OEMs to evaluate vehicles' energy performance. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software Matlab/Simulink was used to develop new and more efficient vehicle energy system controls. The various modeling methods used for the new simulation tool are described in detail. Comparison with measured data is provided to demonstrate the validity of the model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effect of Split-Injection Strategies on Engine Performance and Emissions under Cold-Start Operation

The recently concluded partnership for advancing combustion engines (PACE) was a US Department of Energy consortium involving multiple national laboratories focused on addressing key efficiency and emission barriers in light-duty engines. Generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior was a major pillar in this program. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon, and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster three-way catalyst light-off, and engine out emissions during that period. In this study, engine performance, emissions, and catalyst warmup potential were monitored while the engine was operated using a single direct injection (baseline case) as well as a two-way-equal-split direct injection strategy. These injection strategies were analyzed at a range of cold-start-operation relevant retarded spark timings of up to 25 degrees after top dead center of firing (dATDCf). A stoichiometric 2-bar NIMEP steady-state condition was used for all cases to simulate cold-start operation. Significant improvement in engine stability was observed with the two-way-split injection strategy at the retarded spark timings allowing for up to 2.5x increase in exhaust heat rate when engine operation is stability constrained. Similar fuel-loss-to-oil trends with exhaust heat rate were observed for both single and two-way-split injection strategies. However, the two-way split injection was observed to produce higher NOx emissions per unit exhaust heat rate. A single data point run with three-way-split direct injection at a very retarded spark-timing of 30 dATDCf pointed to further improvements in engine stability and reduction in fuel-loss-to-oil as compared to single injection strategy. Engine stability decreased as spark timing was initially retarded with a single injection but was observed to plateau and stabilize beyond spark timing of 10 dATDCf. Finally, for the two-way-split-injection strategy, retarding the start of injection (SOI) timing of the second injection led to a decrease in engine stability as well as an increase in soot emissions.

42 ENGINEERING↗

Numerical Prediction of CCV in a PFI Engine using a Parallel LES Approach

Cycle-to-cycle variability (CCV) is detrimental to IC engine operation and can lead to partial burn, misfire, and knock. Predicting CCV numerically is extremely challenging due to two key reasons. Firstly, high-fidelity methods such as large eddy simulation (LES) are required to accurately resolve the incylinder turbulent flowfield both spatially and temporally. Secondly, CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. Ameen et al. (Int. J. Eng. Res., 2017) developed a parallel perturbation model (PPM) approach to dissociate this long time-scale problem into several shorter timescale problems. The strategy is to perform multiple single-cycle simulations in parallel by effectively perturbing the initial velocity field based on the intensity of the in-cylinder turbulence. This strategy was demonstrated for motored engine and it was shown that the mean and variance of the in-cylinder flowfield was captured reasonably well by this approach. In the present study, this PPM approach is extended to simulate the CCV in a fired port-fuel injected (PFI) SI engine. Two operating conditions are considered – a medium CCV operating case corresponding to 2500 rpm and 16 bar BMEP and a low CCV case corresponding to 4000 rpm and 12 bar BMEP. The predictions from this approach are also shown to be similar to the consecutive LES cycles. Both the consecutive and PPM LES cycles are observed to under-predict the variability in the early stage of combustion. The parallel approach slightly underpredicts the cyclic variability at all stages of combustion as compared to the consecutive LES cycles. However, it is shown that the parallel approach is able to predict the coefficient of variation (COV) of the in-cylinder pressure and burn rate related parameters with sufficient accuracy, and is also able to predict the qualitative trends in CCV with changing operating conditions. The convergence of the statistics predicted by the PPM approach with respect to the number of consecutive cycles required for each parallel simulation is also investigated. It is shown that this new approach is able to give accurate predictions of the CCV in fired engines in less than one-tenth of the time required for the conventional approach of simulating consecutive engine cycles.

Ameen, Muhsin M↗

The Effect of Pore Morphology on Hot Spot Temperature

Composite explosives contain pores that collapse under shock wave interaction generating localized regions of heat known to be important in the initiation of high explosives. Understanding pore collapse under shock loading is essential to create predictive reactive flow models to simulate the initiation process. While spherical pore collapse has been thoroughly simulated, other geometries have been relatively neglected. By simulating microoscale hot spot nucleation in this study, we analyze the effect of pore morphology on the post-shock hot spot temperature. Several pore morphologies that yield higher temperatures than the spherical case are revealed and discussed.

42 ENGINEERING↗

Grain boundary inter-connections in polycrystalline aluminum with random orientation

Highlights: • The GBICs in a pure aluminum are not random, showing remarkable preference on the planes of low Miller index. • {1 1 1}/{1 1 1} is the most frequent GBIC in pure aluminum. • {1 1 1}/{1 1 1} GBIC is mainly coming from the GBs formed by rotations around , and axes. • {1 1 1}/{1 1 1} GBIC possesses higher PCSD and definite dislocation structures compared to the general GBs. • To pursue {1 1 1}/{1 1 1} GBIC is a pint-cut for the GBE research in high stacking fault energy FCC materials. - Abstract: Grain boundary inter-connection (GBIC) is the matching of two crystallographic planes from two abutting grains ending on the grain boundary (GB) position in polycrystalline materials, which can be expressed as {h_1k_1l_1}/{h_2k_2l_2}. GBIC is the critical parameter that intrinsically defines the character and properties of a GB. In current work, a zone-melted polycrystalline aluminum bar with a purity higher than 99.99% (mass fraction) was subjected to a multi-directional forging (MDF) with a true strain of 4 followed by a recrystallization annealing at 360 °C. Such process repeated at least 4 times until an equiaxed-grain microstructure with random orientation and averaged grain size approximate 30 μm was achieved. Then the GBICs were determined by electron backscatter diffraction (EBSD) measurement and stereology-based five-parameter analysis (FPA) coupled with crystallographic analysis after the grain boundaries (GBs) were filtered according to their misorientations (e.g. angle/axis pair). The results revealed that the GBICs for any group of GBs with a given misorientation are not random, showing remarkable preference on the planes of low Miller index forming mixed and twist GBs. The work also demonstrated that among the high angle boundaries (HABs), {1 1 1}/{1 1 1}, including coherent ∑3 boundaries, is the most frequent GBIC, mainly due to the GBs formed by rotations around <1 1 1>, <1 2 2> and <1 1 2> axes. Near coincidence site (NCS) and O-lattice theory analyses indicate that the {1 1 1}/{1 1 1} GBICs usually possess higher planar coincidence site density (PCSD) and definite dislocation structures compared to the general GBs, implying their more structural stability when only crystallography is taken into account. This result agrees very well with the recent results obtained by molecular dynamic simulations. It is significant to the grain boundary engineering (GBE) in the high stacking fault energy (SFE) face-centered cubic (FCC) materials such as aluminum and its alloys.

36 MATERIALS SCIENCE↗

Predicting large-scale pool fire dynamics using an unsteady flamelet- and large-eddy simulation-based model suite

A low-Mach, unstructured, large-eddy-simulation-based, unsteady flamelet approach with a generalized heat loss combustion methodology (including soot generation and consumption mechanisms) is deployed to support a large-scale, quiescent, 5-m JP-8 pool fire validation study. The quiescent pool fire validation study deploys solution sensitivity procedures, i.e., the effect of mesh and time step refinement on capturing key fire dynamics such as fingering and puffing, as mesh resolutions approach O(1) cm. A novel design-order, discrete-ordinate-method discretization methodology is established by use of an analytical thermal/participating media radiation solution on both low-order hexahedral and tetrahedral mesh topologies in addition to quadratic hexahedral elements. Here, the coupling between heat losses and the flamelet thermochemical state is achieved by augmenting the unsteady flamelet equation set with a heat loss source term. Soot and radiation source terms are determined using flamelet approaches for the full range of heat losses experienced in fire applications including radiative extinction. The proposed modeling and simulation paradigm are validated using pool surface radiative heat flux, maximum centerline temperature location, and puffing frequency data, all of which are predicted within 10% accuracy. Simulations demonstrate that under-resolved meshes predict an overly conservative radiative heat flux magnitude with improved comparisons as compared to a previously deployed hybrid Reynolds-averaged Navier–Stokes/eddy dissipation concept-based methodology.

42 ENGINEERING↗

A generalized deep learning approach for local structure identification in molecular simulations

Identifying local structure in molecular simulations is of utmost importance. The most common existing approach to identify local structure is to calculate some geometrical quantity referred to as an order parameter. In simple cases order parameters are physically intuitive and trivial to develop (e.g., ion-pair distance), however in most cases, order parameter development becomes a much more difficult endeavor (e.g., crystal structure identification). Using ideas from computer vision, we adapt a specific type of neural network called a PointNet to identify local structural environments in molecular simulations. A primary challenge in applying machine learning techniques to simulation is selecting the appropriate input features. This challenge is system-specific and requires significant human input and intuition. In contrast, our approach is a generic framework that requires no system-specific feature engineering and operates on the raw output of the simulations, i.e., atomic positions. We demonstrate the method on crystal structure identification in Lennard-Jones (four different phases), water (eight different phases), and mesophase (six different phases) systems. The method achieves as high as 99.5% accuracy in crystal structure identification. The method is applicable to heterogeneous nucleation and it can even predict the crystal phases of atoms near external interfaces. We demonstrate the versatility of our approach by using our method to identify surface hydrophobicity based solely upon positions and orientations of surrounding water molecules. Our results suggest the approach will be broadly applicable to many types of local structure in simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large-scale large eddy simulation of nuclear reactor flows: Issues and perspectives

Numerical simulation has been an intrinsic part of nuclear engineering research since its inception. In recent years a transition is occurring toward predictive, first-principle-based tools such as computational fluid dynamics. Even with the advent of petascale computing, however, such tools still have significant limitations. In the present work some of these issues, and in particular the presence of massive multiscale separation, are discussed, as well as some of the research conducted to mitigate them. Petascale simulations at high fidelity (large eddy simulation/direct numerical simulation) were conducted with the massively parallel spectral element code Nek5000 on a series of representative problems. These simulations shed light on the requirements of several types of simulation: (1) axial flow around fuel rods, with particular attention to wall effects; (2) natural convection in the primary vessel; and (3) flow in a rod bundle in the presence of spacing devices. Finally, the focus of the work presented here is on the lessons learned and the requirements to perform these simulations at exascale. Additional physical insight gained from these simulations is also emphasized.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Estimating the carbon footprint of computational fluid dynamics

In this study, computational resources have grown exponentially in the past few decades. These machines make possible research and design in fields as diverse as medicine, astronomy, and engineering. Despite ever-increasing computational capabilities, direct simulation of complex systems has remained challenging owing to the degrees of freedom involved. At the cusp of exascale computing, high-resolution simulation of practical problems with minimal model assumptions may soon experience a renaissance. However, growing reliance on modern computers comes at the cost of a growing carbon footprint. To illustrate this, we examine historic computations in fluid dynamics where larger computers have afforded the opportunity to simulate flows at increasingly relevant Reynolds numbers. Under a variety of flow configurations, the carbon footprint of such simulations is found to scale roughly with the fourth power of Reynolds number. This is primarily explained by the computation cost in core-hours, which is also described by similar scaling, though regional differences in renewable energy use also play a role. Using the established correlation, we examine a large database of simulations to develop estimates for the carbon footprint of computational fluid dynamics in a given year. Collectively, the analysis provides an additional benchmark for new computations where, in addition to balancing considerations of model fidelity, carbon footprint should also be considered.

42 ENGINEERING↗

Large-Scale Simulation of Nuclear Reactors: Issues and Perspectives

Numerical simulation has been an intrinsic part of nuclear engineering research since its inception. In recent years a transition is occurring toward predictive, first-principle-based tools such as computational fluid dynamics. Even with the advent of petascale computing, however, such tools still have significant limitations. In the present work some of these issues, and in particular the presence of massive multiscale separation, are discussed, as well as some of the research conducted to mitigate them. Petascale simulations at high fidelity (large eddy simulation/direct numerical simulation) were conducted with the massively parallel spectral element code Nek5000 on a series of representative problems. These simulations shed light on the requirements of several types of simulation: (1) axial flow around fuel rods, with particular attention to wall effects; (2) natural convection in the primary vessel; and (3) flow in a rod bundle in the presence of spacing devices. The focus of the work presented here is on the lessons learned and the requirements to perform these simulations at exascale. Additional physical insight gained from these simulations is also emphasized.

CFD↗

EMAPS: An Efficient Multiscale Approach to Plasma Systems with Non-MHD Scale Effects

Global interactions of energetic ions with magnetoplasmas and neutral gases lie at the core of many space and laboratory plasma phenomena ranging from solar wind entry into and transport within planetary magnetospheres and exospheres to fast-ion driven instabilities in fusion devices to astrophysics-in-lab experiments. The ability of computational models to properly account for physical effects that underlie such interactions, namely ion kinetic, ion cyclotron, Hall, collisional and ionization processes is important for the success and planning of experimental research in plasma physics. Understanding the physics of energetic ions, in particular their nonlinear resonance interactions with Alfvén waves, is central to improving the heating performance of magnetically confined plasmas for future energy generation. Fluid models are not adequate for high-beta plasmas as they cannot fully capture ion kinetic and cyclotron physics (e.g., ion behavior in the presence of magnetic nulls, shock structures, plasma interpenetration, etc.). Recent results from global reconnection simulations show that even in a MHD-like regime there may be significant differences between kinetic and MHD simulations. Therefore, kinetic modeling becomes essential for meeting modern day challenges in plasma physics. The hybrid approximation is an intermediate approximation between the fluid and fully kinetic approximations. It eliminates light waves, removes the electron inertial temporal and spatial scales from the problem and enables full-orbit ion kinetics. As a result, hybrid codes have become effective tools for exploring ion-scale driven phenomena associated with ion beams, shocks, reconnection and turbulence that control the large-scale behavior of laboratory and space magnetoplasmas. A number of numerical issues, however, make three-dimensional (3D) large-scale hybrid simulations of inhomogeneous magnetized plasmas prohibitively expensive or even impossible. To resolve these difficulties we have developed a novel Event-driven Multiscale Asynchronous Parallel Simulation (EMAPS) technology that replaces time stepping with self-adaptive update events. Local calculations are carried out only on an “as needed basis”. EMAPS (i) guarantees accurate and stable processing of physical variables in time accurate simulations, and (ii) eliminates unnecessary computation. Applying EMAPS to the hybrid model has resulted in the development of a unique parallel code, dimension-independent (compile-time-configurable) HYPERS (Hybrid Parallel Event-Resolved Simulator) that scales to hundreds of thousands of parallel processors. HYPERS advances electromagnetic fields and particles asynchronously on time scales determined by local physical laws and mesh properties. To achieve high computational accuracy in complex device geometries, HYPERS employs high-fidelity Cartesian grids with masked conductive cells. The HYPERS model includes multiple ion species, energy and momentum conserving ion-ion collisions, and provides a number of approximations for plasma resistivity and vacuum regions. Both local and periodic boundary conditions are allowed. The HYPERS solver preserves zero divergence of magnetic field. The project has demonstrated HYPERS capabilities on a number of applications of interest to fusion and astrophysical plasma physics applications listed below. 1. Theta-pinch formation of FRCs The formation, spontaneous spin-up, and stability of theta-pinch formed field-reversed configurations have been studied self-consistently in 3D. The end-to-end hybrid simulations reveal poloidal profiles of implosion-driven fast toroidal plasma rotation and demonstrate three discharge regimes as a function of experimental parameters: the decaying stable configuration, the tilt unstable configuration, and the nonlinear evolution of a fast growing tearing mode. 2. FRC collisions with magnetic mirrors Interactions of fast plasma streams and objects with magnetic obstacles (dipoles, mirrors, etc) lie at the core of many space and laboratory plasma phenomena ranging from magnetoshells and solar wind interactions with planetary magnetospheres to compact fusion plasmas. HYPERS simulations are compared with data from the MSX experiment (LANL) that focuses on the physics of magnetized collisionless shocks through the acceleration and subsequent stagnation of FRC plasmoids against a strong magnetic mirrors and flux-conserving boundaries. 3. Exploding magnetoplasmas Results from hybrid simulations of two experiments at the LAPD and Nevada Terawatt Facility are discussed where short-pulse lasers are used to ablate solid targets to produce plasmas that expand across external magnetic fields. The first simulation recreates flutelike density striations observed at the leading edge of a carbon plasma and predicts an early destruction of the magnetic cavity in agreement with experimental evidence. In the second simulation a polyethylene target is ablated into a mixture of protons and carbon ions. A mechanism is demonstrated that allows protons to penetrate the magnetic field in the form of a collimated flow. The results are compared to experimental data and single-fluid MHD simulations. The EMAPS framework has the potential for wide application in many other engineering and scientific fields, such as climate models, biological systems, electronic devices, seismic events, oil reservation simulators that all involve advancing solutions of partial differential equations in time where the rate of activity can be adapted widely over the spatial domain depending on locally space/time phenomena (“events”).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reactivity-controlled compression ignition drive cycle emissions and fuel economy estimations using vehicle system simulations

In-cylinder blending of gasoline and diesel to achieve reactivity-controlled compression ignition has been shown to reduce NO X and soot emissions while maintaining or improving brake thermal efficiency as compared with conventional diesel combustion. The reactivity-controlled compression ignition concept has an advantage over many advanced combustion strategies in that the fuel reactivity can be tailored to the engine speed and load, allowing stable low-temperature combustion to be extended over more of the light-duty drive cycle load range. In this paper, a multi-mode reactivity-controlled compression ignition strategy is employed where the engine switches from reactivity-controlled compression ignition to conventional diesel combustion when speed and load demand are outside of the experimentally determined reactivity-controlled compression ignition range. The potential for reactivity-controlled compression ignition to reduce drive cycle fuel economy and emissions is not clearly understood and is explored here by simulating the fuel economy and emissions for a multi-mode reactivity-controlled compression ignition–enabled vehicle operating over a variety of US drive cycles using experimental engine maps for multi-mode reactivity-controlled compression ignition, conventional diesel combustion, and a 2009 port-fuel injected gasoline engine. Drive cycle simulations are completed assuming a conventional mid-size passenger vehicle with an automatic transmission. Multi-mode reactivity-controlled compression ignition fuel economy simulation results are compared with the same vehicle powered by a representative 2009 port-fuel injected gasoline engine over multiple drive cycles. Finally, engine-out drive cycle emissions are compared with conventional diesel combustion, and observations regarding relative gasoline and diesel tank sizes needed for the various drive cycles are also summarized.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗