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DOE OSTI2023

MatRIS: Multi-level Math Library Abstraction for Heterogeneity and Performance Portability using IRIS Runtime

Vendor libraries are tuned for a specific architecture and are not portable to others. Moreover, they lack support for heterogeneity and multi-device orchestration, which is required for efficient use of contemporary HPC and cloud resources. To address these challenges, we introduce MatRIS—a multilevel math library abstraction for scalable and performance-portable sparse/dense BLAS/LAPACK operations using IRIS runtime. The MatRIS-IRIS co-design introduces three levels of abstraction to make the implementation completely architecture agnostic and provide highly productive programming. We demonstrate that MatRIS is portable without any change in source code and can fully utilize multi-device heterogeneous systems by achieving high performance and scalability on Summit, Frontier, and a CADES cloud node equipped with four NVIDIA A100 GPUs and four AMD MI100 GPUs. A detailed performance study is presented in which MatRIS demonstrates multi-device scalability. When compared, MatRIS provides competitive and even better performance than libraries from vendors and other third parties.

Monil, M. A. H.↗

DOE OSTI2021

Multi-Fluid and Kinetic Models of Partially Ionized Magnetic Reconnection

Magnetic reconnection in partially ionized plasmas is a ubiquitous and important phenomena in both laboratory and astrophysical systems. Here, simulations of partially ionized magnetic reconnection with well-matched initial conditions are performed using both multi-fluid and fully-kinetic approaches. Despite similar initial conditions, the time-dependent evolution differs between the two models. In multi-fluid models, the reconnection rate locally obeys either a decoupled Sweet-Parker scaling, where neutrals are unimportant, or a fully coupled Sweet-Parker scaling, where neutrals and ions are strongly coupled, depending on the resistivity. In contrast, kinetic models show a faster reconnection rate that is proportional to the fully-coupled, bulk Alfv\'en speed, $v_A^\star$. These differences are interpreted as the result of operating in different collisional regimes. Multi-fluid simulations are found to maintain $\nu_{ni}L/v_A^\star \gtrsim 1$, where $\nu_{ni}$ is the neutral-ion collision frequency and $L$ is the time-dependent current sheet half-length. This strongly couples neutrals to the reconnection outflow, while kinetic simulations evolve to allow $\nu_{ni}L/v_A^\star < 1$, decoupling neutrals from the reconnection outflow. Differences in the way reconnection is triggered may explain these discrepancies.

Magnetic reconnection↗

DOE OSTI2021

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems [SWR-22-07]

NREL's PowerGridworld provides a modular simulation environment for training heterogenous, grid-aware, multi-agent reinforcement learning (RL) policies at scale. The package enables the user to create component gym environments that can be composed into more complex agents. For example, a grid interactive building environment can be created by composing together component environments each encapsulating the building, PV, and battery physics. These multi-component environments can then be combined into multi-agent simulation where each agent's power consumption/injection becomes an input for solving the optimal power flow on a distribution feeder modeled in OpenDSS. Information from OpenDSS, such as bus voltages and line flows, can be included in the agents' observation spaces to enable grid-aware rewards. The default API for the PowerGridworld simulator conforms to RLLib's MultiAgent API and thus enables distributed training using HPC and cloud resources.

Biagioni, David↗

DOE OSTI2024

MLEC-Sim: A Simulator for Evaluating Multi-Level Erasure Coding

We present MLEC-Sim, a sophisticated simulator for Multi-Level Erasure Coding (MLEC), developed in approximately 13 KLOC. The simulator is engineered to analyze the impact of various system configurations and erasure coding policies on system durability and network overhead. It supports a comprehensive range of parameters including disk capacity, disk I/O bandwidth, failure rates, network bandwidth, and system scale, accommodating various erasure coding approaches such as Single-Level Erasure Coding (SLEC), Multi-Level Erasure Coding (MLEC), and Local Reconstruction Codes (LRC). MLEC-Sim provides support for multiple chunk placement policies, including clustered parity and declustered parity, and encompasses a variety of repair methods like Repair-ALL, Repair-FCO, Repair-HYB, and Repair-MIN. It is capable of simulating disk failures through a variety of means, including distribution-based or trace-based mechanisms, and can handle complex multi-level (de)clustered placements and repair processes. A key feature of MLEC-Sim is its adoption of the splitting simulation method for evaluating system durabilities at extremely high levels, which are challenging to assess with traditional simulation approaches. This feature allows for a detailed evaluation of system resilience under a range of conditions, aiding in the selection of appropriate erasure coding solutions for enhancing system durability. MLEC-Sim contributes to the field of data storage and reliability by providing a tool for the detailed evaluation of the durability and efficiency of erasure coding configurations, intended for use by researchers and practitioners in the design and optimization of storage systems.

Wang, Meng↗

DOE OSTI2022

Development of a high-fidelity multi-physics coupling between MCNP6.2 and CTF4.0 for VVER applications

Ensuring system safety in the design, licensing, and operation phases is a priority in the nuclear industry. Performing extensive, full-scale reactor safety experiments is often prohibitive due to the large associated costs. Computational simulations offer an alternative safety analysis method, typically with significant cost reductions. Recent high-level developments in technology and increased availability of computational resources have allowed the development of high-fidelity, high-resolution multi-physics coupled codes. Such developments may be used to generate reference models for deterministic core calculations. Under this framework, the high-fidelity continuous energy Monte Carlo-based neutron transport code MCNP6.2 was coupled externally with the state-of-the-art thermal-hydraulics subchannel code, CTF4.0 for VVER (Water-Water Energetic Reactor) applications. A VVER-1000 fuel assembly model was used to demonstrate the capability of the coupled code. The converged coupled solution is compared to initial results, consisting of the first MCNP evaluation and first CTF evaluation after initialization. The VVER-1000 type assembly results are compared to other evaluations of the same assembly model. The findings indicate good agreement with expectations and reference cases, where available. The initial results of the coupled MCNP6.2/CTF4.0 calculations at the assembly level for steady-state calculations are presented in this study, which may support future work toward high-fidelity coupled full-core modeling capabilities. The multi-physics model may be further improved, enhanced, and expanded for both cycle depletion and transient applications. Such a multi-physics system will also be applicable to the VVER-1200 and other triangular lattice designs and support their deployment and operation safely and economically. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Multi-tool optimization for computer controlled optical surfacing

With the rapid development of precision technologies, the demand of high-precision optical surfaces has drastically increased. These optical surfaces are mainly fabricated with computer controlled optical surfacing (CCOS). In a CCOS process, a target surface removal profile is achieved by scheduling the dwell time for a set of machine tools. The optimized dwell time should be positive and smooth to ensure convergence to the target while considering CNC dynamics. The total run time of each machine tool is also expected to be balanced to improve the overall processing efficiency. In the past few decades, dwell time optimization for a single machine tool has been extensively developed. While the methods are applicable to multi-tool scenarios, they fail to consider the overall contributions of multiple tools simultaneously. In this paper, we conduct a systematic study on the strategies for multi-tool dwell time optimization and propose an innovative method for simultaneously scheduling dwell time for multiple tools for the first time. First, the influential factors to the positiveness and smoothness of dwell time solutions for a single machine tool are analyzed. The compensation strategies that minimize the residual while considering the CNC dynamics limit are then proposed. Afterwards, these strategies are extended to the proposed multi-tool optimization that further balances the run time of machine tools. Finally, the superiority of each strategy is carefully studied via simulation and experiment. The experiment is performed by bonnet polishing a 60 mm × 60 mm mirror with three tools of different diameters ( i.e., 12 mm, 8 mm, and 5 mm). The figure error of the mirror is reduced from 45.42 nm to 11.18 nm root mean square in 13.28 min. Moreover, the measured polishing result well coincides with the estimation, which proves the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multi-parameter distributed fiber optic sensing using double-Brillouin peak fiber in Brillouin optical time domain analysis

In this paper, we demonstrate a multi-parameter fiber sensing system based on stimulated Brillouin scattering in a double-Brillouin peak specialty fiber with enhanced Brillouin gain response. The amplitude level of the second Brillouin gain peak, which originated from the higher-order acoustic modes, has been improved with an approximately similar amplitude level to the first Brillouin gain peak from the fundamental acoustic mode. Compared to other multi-Brillouin peak fibers presented in the literature, the proposed fiber significantly reduces the measured Brillouin frequency shift error, thus improving strain and temperature accuracies. By utilizing the sensitivity values of the strain and temperature associated with each Brillouin gain spectrum (BGS) peak, a successful discriminative measurement of strain and temperature is performed with an accuracy of ±13 μɛ, and ±0.5 °C, respectively. The proposed double-Brillouin peak fiber appears to be a possible alternative to other multi-BGS peak fibers, for instance, large effective area fiber and dispersion compensating fibers, which are inherently accompanied by large measurement errors due to the weak Brillouin gain values originating from the higher-order acoustic modes. The demonstrated results show different strain and temperature coefficients of 47 kHz/µɛ, 1.15 MHz/°C for peak 1 and 51 kHz/µɛ, 1.37 MHz/°C for peak 2. Moreover, the enhanced BGS peak gains having nearly the same amplitude levels enable the discriminative measurement of strain and temperature. Such fibers in Brillouin interrogation eliminate the need for complex monitoring setups and reduce measurement errors. We recommend that for long-distance natural gas pipeline monitoring, where discriminative strain and temperature measurement is crucial, the proposed double-Brillouin peak fiber can be highly beneficial.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Multi-mode THz quantum-cascade VECSELs based on disordered metasurfaces

Quantum-cascade vertical-external-cavity surface-emitting-lasers (VECSELs) based on disordered amplifying metasurfaces are demonstrated and explored as potential broadband, multi-mode THz sources. The disorder is introduced along one spatial axis of the metasurface by pseudo-randomly varying the width of its resonant ridge antennas. Compared to a quantum-cascade (QC) VECSEL based on a uniform metasurface, the disordered structure supports much more localized transverse modes with reduced spatial overlap within the QC gain material. This localization is hypothesized to facilitate the spatial hole burning of the gain material and, therefore, enable multi-mode lasing, particularly for short cavities on the order of a few wavelengths. Several devices have been fabricated and shown to differ from uniform QC-VECSELs in a few key ways, possessing highly nonlinear light-current characteristics, angle-dependent emission spectra and broadband multi-mode lasing. At most, 17 modes are simultaneously observed, spanning 680 GHz. The number of VECSEL modes is shown to have an inverse relationship with the cavity length, which is attributed to increased diffractive losses in the open plano-plano cavity. As the cavity length is tuned, the device emits over a quasi-continuous band from 3.15 to 3.97 THz or up to 4.24 THz with a longitudinal mode hop.

Morag, Eilam [Univ. of California, Los Angeles, CA↗

DOE OSTI2020

Multi-line FLEET by imaging periodic masks

A simple linear configuration for multi-line FLEET velocimetry is used for the first time to image an overexpanded unsteady supersonic jet. The FLEET lines are spaced 0.5-1.0 mm apart and up to six lines can simultaneously be used to visualize the flowfield. These lines are created using periodic masks, despite the mask blocking 25 — 30% of the 10 mJ incident beam. Maps of mean single-component velocity in the direction along the principal flow axis, and turbulence intensity in that same direction, are created using multi-line FLEET, and computed velocities agree well with that obtained from single-line (traditional) FLEET. Compared to traditional FLEET, multi-line FLEET offers increased simultaneous spatial coverage and the ability to produce spatial correlations in the streamwise direction. This FLEET permutation is especially well-suited for short-duration test facilities

42 ENGINEERING↗

DOE OSTI2020

Integrating Health and Energy Efficiency in Multi-Family Buildings

The intersection between health and the built environment has long been known. Since the 18 th century, public health officials have been targeting building issues, such as crowding, poor sanitation, and inadequate ventilation in efforts to reduce infectious diseases and fire hazards. More recently, federal agencies, such as the U.S. Environmental Protection Agency (EPA), the Centers for Disease Control and Prevention, HUD, and the DOE have been working to reduce or eliminate indoor building factors that are known to have adverse health impacts on Americans, including reducing lead in housing and indoor air pollution that causes respiratory disease, and ensuring access to adequate heating, cooling, and moisture control. PNNL, in support of FEMP’s HBI, undertook a review of literature and existing best practices to identify current activities and research on the intersection between traditional energy-efficiency measures and occupant health within multi-family buildings. While the HBI methodology has focused on traditional office building spaces, it is now expanding into additional building use types. This overview explores some of the most impactful resources to help property owners and managers understand more about multi-family residential buildings that are both healthy and energy efficient. The federal government provides direct oversight and operation across several types of multi-family residential housing, including dormitories, barracks, and senior community living centers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Multi-Axis Resonant Plate Shock Testing Evaluation and Test Specification Development

Resonant plate testing is a shock test method that is frequently used to simulate pyroshock events in the laboratory. Recently, it was discovered that if the unit under test is installed at an off-center location, a tri-axial accelerometer would record a shock response in three directions and the resulting shock response spectra implied that the test may have qualified the component in three directions simultaneously. The purpose of this research project was to evaluate this idea of multi-axis shock testing to determine if it was truly a multi-axis shock environment and if such a test could be used as an equivalent component qualification test. A study was conducted using generic, additively manufactured components tested on a resonant plate, along with an investigation of plate motion to evaluate the component response to off- center plate excitation. The data obtained here along with the analytical simulations performed indicate that off-center resonant plate tests are actually not three-axis shock tests, but rather single axis shocks at an arbitrary angle dictated by the location of the unit under test on the plate. This conclusion is supported by the fact that only one vectored shock input is provided to the component in a resonant plate test. Thus, the output response is a coupled response of the transverse plate vibration and the rotational motion of the component on the plate. Additionally, a multi-axis shock test defined by three single axis test environments always results in a significant component over-test in one direction.

42 ENGINEERING↗

DOE OSTI2020

Multi-Functional Distributed Fiber Sensors for Pipeline Monitoring and Methane Detections. Final Report

As an abundant and cheap fossil energy source, natural gas has become a significant energy supply to support the United States’ economy. However, the large-scale extraction and utilization of natural gas also impose significant challenges on methane leakage. This problem is exacerbated by aging gas utility delivery systems, including interstate high-pressure pipelines, storage, and transmission facilities. This project aims to develop a cost-effective fiber optical sensing method that can perform multi-parameter real-time measurements of natural gas pipelines across long interrogation distances up to 100 km with 1-meter spatial resolution. This sensing tool can evaluate overall pipeline efficiency and reduce methane emissions for mid-stream methane infrastructures. To accomplish this objective, research and development efforts funded by this project have resulted in the following accomplishments: This project successfully has developed new functional sensory polymer materials using Metal-Organic Frameworks (MOFs) that can be coated on optical fiber through the reel-to-reel coating process. Functional polymer-coated optical fibers can perform sensitive methane detection through evanescence wave interaction and strain-based measurements to achieve 1% detection sensitivities. The new sensors fibers support both distributed measurements and multiplexed fiber sensors array for multi-point measurements. This project developed and optimized a new multi-core optical fiber that supports simultaneous and distributed measurements of strain and temperatures with 1-meter spatial resolutions across up to 100-km interrogation distance. This new fiber, combined with sensory polymercoated fiber, could perform both distributed temperature and methane detections. This project developed a new artificial intelligence big data algorithm approach that can effectively analyze high-resolution data harnessed by distributed fiber sensors to protect natural gas pipelines against external threats and detect internal defects induced by corrosion. Working with our industry partner, this project developed new optical fibers that support fiber sensor fabrications through polymer coating after the fibers are drawn. These new fibers eliminate the need for direct sensor fabrication when the fiber is fabricated on a fiber draw tower, which drastically expands fiber sensors' applicability. This research project has significantly advanced the distributed fiber sensing technology. It will dramatically increase the applicability and adaptability of distributed fiber sensors for a wide array of applications in energy, sustainability, and environmental science, including structural health monitoring of natural gas pipelines, oil infrastructures, hydrogen facilities, and environmental monitoring of carbon storage sites, water supply systems, and others.

03 NATURAL GAS↗

DOE OSTI2021

Large-Scale, GPU-Enhanced DFTB Approaches for Probing Multi-Component Alloys

The major goals of the project are to develop and apply GPU-enhanced density functional theory tight binding (DFTB) calculations for efficient simulations of structural materials of alloy systems. The figure below depicts the GPU algorithmic developments on the left that will be carried out, and the solid-state structures on the right are representative of the complex alloys that can be computed with the GPU-enhanced DFTB approach. The methodology and tools developed in this project encompass accurate intermolecular potentials and GPU enhancements to the density functional tight binding (DFTB) approach for high-throughput ab initio molecular dynamics calculations of multi-component alloys at elevated temperatures. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of large, multi-component alloys at the predictive quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum nature of chemical systems; however, these methods cannot tackle the large sizes relevant to these multi-component systems. The DFTB-based ab initio molecular dynamics approach (coupled with our in-house GPU capabilities for enhanced speed) used in this project provides a viable approach for probing these large systems at a quantum level of detail that is significantly faster than current first-principle methods Collectively, the capabilities developed in this project directly respond to DOE HBCU-OMI, AOI 2-1 initiatives by (1) enabling accurate and efficient predictions and (2) bringing a fundamental understanding of structural interactions in these complex systems at elevated temperatures.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Modeling and Optimizing Pumped Storage in a Multi-stage Large Scale Electricity Market under Portfolio Evolution

To leverage the fast-ramping capability of resources to provide great value to the grid, electricity system operators such as the Midcontinent Independent System Operator (MISO) continue to evolve their approaches for integrating energy storage resources, including pumpedstorage hydro (PSH), into the electricity markets. However, new challenges arise in modeling and optimizing these energy-limited resources across multiple market clearing processes and planning studies with uncertainties and imperfect information. For instance, current market practices of PSH owners specifying pumping/generating hours can result in sub-optimal generation dispatch. Letting grid operators optimize PSH with the consideration of multiple operating modes and energy limitation constraints can potentially bring economic benefits to both the system and the PSH owners. However, in multi-stage clearing process of electricity markets, utilizing the PSH flexibility to deal with realized uncertainties can cause deviation in the multi-stage scheduling processes. The resulting financial risks from the schedule deviation may not be acceptable to PSH owners. In addition, to effectively utilize this energy limited resource, the state of charge (SOC) constraints of PSH needs to be continuously optimized and the marginal cost of deviation need to reflect the expected cost to purchase or sell energy at future times to compensate for deviations. This project aims to develop a prototype enhanced PSH model and improved price signals in the multi-stage market clearing process with proper consideration of the unique characteristics of PSH, in order to better align underlying PSH capabilities with evolving grid needs, particularly including the needs for more frequent and larger cycling to manage variability and uncertainty from renewables.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Multi-Process Tooling

Decisions made early in the automotive design process influence material selection, which in turn dictates process selection and tool design. Because of tool build time and cost of tooling, the original path is not easily altered, even if there is compelling evidence that another material or process would be beneficial. This project focused on tool design that is agile enough to allow its use in multiple processes—injection, injection compression, and extrusion-compression. This tool design allows for the manufacture of components with the most efficient process or materials, without building multiple, single-process tools. The primary purpose of the Multi-Process Tool project was to physically demonstrate that a single, well-designed tool could be used to manufacture parts with a variety of materials that require different processes. A multi-process tool would be beneficial to providing data for any changes to the process since materials and processes can be interchanged without incurring additional tool cost(s). Battery tray parts, (representative of a multi-process tool, were successfully manufactured using various types of materials, such as fiber reinforced (carbon fiber and/or glass fibers, recycled carbon fibers), amorphous (PP, TPU), semi-crystalline (PA6, PA66), and crystalline (thermoset epoxy resin) polymers. Processing of the parts was achieved by injection molding, compression molding, compression overmolding, and injection overmolding. Specimens extracted from various locations on the battery tray parts were evaluated for mechanical properties (flexure and interlaminar shear strength properties). The results show that the tool can be used to produce parts from a wide range of materials and processes with no degradation of the physical or cosmetic properties.

42 ENGINEERING↗

DOE OSTI2023

In Situ Infrared Spectroscopy of a Plasma Jet and Data-Driven Solution of Multi-Scale Plasma Chemistry Problems

Multi-scale problems are commonly known in many scientific and engineering fields where microscopic behaviors are coupled with macroscopic processes. This is also an unsolved problem in low-temperature plasma chemistry where hundreds of chemical species are involved in thousands of chemical reactions. To address this problem, a physics-informed data-driven modeling is developed to solve such a multi-scale problem using the experimental Fourier-transform infrared spectroscopy (FTIR) measurements of several species’ concentrations. The modeling based on modern machine learning techniques provides concentrations of other relevant species along with the electron temperature and gas temperature at the location of FTIR measurements. For example, the concentrations O, OH, and H 2 O 2 play key roles in plasma-based cancer therapy. This approach overcomes the multi-scale difficulties of microscopic low-temperature plasma chemistry coupling with macroscopic gas flow and allows the acquisition of a full picture of output species concentrations. Presented here for the helium-air jet at atmospheric pressure, the ML-based modeling can be used to describe and possibly control multiscale systems using partial experimental data sets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

A Full-scale Demonstration of Pressurized Water Reactor Core Design Optimization using Multi-Cycle Optimization Methodology

The U.S. nuclear sector encounters a difficulty in upholding essential safety standards while also securing economic viability for continued operation. Safety stands as a pivotal factor across all facets of operations within light-water reactor nuclear power plants. Achieving economic feasibility alongside safety can be facilitated through the utilization of a risk-informed framework, exemplified by the ongoing development within the Risk-Informed Systems Analysis Pathway under the auspices of the U.S. Department of Energy's LWRS Program. This initiative advocates for a diverse array of research and development endeavors aimed at optimizing both safety and economic efficacy within nuclear power plants, particularly pertinent as many plants contemplate second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: deploy methodologies and technologies that better represent safety margins and cost and safety factors and develop advanced applications that enable cost-effective plant operation. This report assesses the potential for resolving multi-cycle plant reload challenges through real-world scenarios utilizing the Plant ReLoad Optimization (PRLO) framework. This framework offers reactor core design developers analytic tools of reactor safety and fuel performance with the assistance of artificial intelligence (AI) to enhance core design solutions. Multi-objective genetic algorithm alongside acceleration techniques is explored as an enabling technology for improving fuel efficiency while upholding safety thresholds. The demonstration of multi-cycle core design optimization is performed. This report investigates the practical application of the PRLO platform in addressing real-world core design challenges, supporting AI efforts, and contrasting outcomes with those derived from heuristic or conventional algorithms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Enabling Low-Temperature (LTP) Ignition Technologies for Multi-Mode Engines through the Development of a Validated High-Fidelity LTP Model for Predicative Simulations Tools

The goal of multi-mode engine architectures is to extend current lean-burn dilution limits with renewable fuels, which requires spark plugs to deposit high energies (hundreds of mJ) in order to initiate ignition and complete combustion. At elevated energy deposition rates, spark plugs experience increased electrode erosion and thermal losses, which ultimately shortens the spark-plug lifetime and lowers ignition efficiency. As such, in order to safeguard the efficiency gains of multi-mode concepts, new and improved ignition technologies are required. Recently, non-equilibrium low-temperature plasmas (LTP) have been shown to promote energy-efficient ignition via quenching and transport of electronically excited atoms and molecules, selective radical production and fast heating of hydrocarbon/air mixtures [1-2]. Thus, LTP is seen as a technology that can potentially improve the energy extraction efficiency of fuels, while enabling kinetically controlled combustion modes towards fuel leaner conditions to realize current DOE VTO goals of improving the sustainability of future mobility [3]. Although many previous studies have demonstrated the efficacy of plasma-assisted ignition to enhance combustion, the detailed enhancement mechanisms remain largely unknown, especially for oxygenated fuels and at elevated pressures that are most relevant to practical engine conditions. These barriers hinder the development of accurate and comprehensive numerical models that seek to describe LTP-based ignition in existing engine design software tools and methods. Current state-of-the-art simulation capabilities for LTP ignition systems are in need of improvements since they deliver qualitative results only due to important limitations of existing approaches. Firstly, validated kinetic models with elementary steps for plasma discharges in oxygenated fuel/air mixtures of relevance to the transportation sector are required. Such kinetic models do not exist at present and will be developed and validated within this project. Secondly, plasma discharges and reactive mixture ignition are multi-scale, unsteady processes requiring high-performance numerical methods and software that execute efficiently on DOE supercomputers. Such software does not exist at present and will be developed and applied to practical LTP ignition scenarios as part of this project. Thirdly, experimental databases that are tailored to serve as benchmark in support of the development of predictive computational models of LTP ignition do not exist and will be part of this project.

33 ADVANCED PROPULSION SYSTEMS↗