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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Quantum learning of classical stochastic processes: The completely positive realization problem

Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651–664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine learning, device-independent characterization and reverse-engineering of stochastic processes and quantum processors, and more generally, of dynamical processes with quantum memory [M. Guţă, Phys. Rev. A 83(6), 062324 (2011); M. Guţă and N. Yamamoto, e-print http://arxiv.org/abs/1303.3771 (2013)].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

A Prototyping Environment for Research on Human-Machine Interfaces in Process Control: Use of Microsoft WPF for Microworld and Distributed Control System Development

Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, but the set of tools for developing and designing HMIs is still in its infancy. Here we propose that Microsoft Windows Presentation Foundation (WPF) is well suited for many roles in the research and development of HMIs for process control.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗
DOE OSTI2014

Generic Argillite/Shale Disposal Reference Case

Radioactive waste disposal in a deep subsurface repository hosted in clay/shale/argillite is a subject of widespread interest given the desirable isolation properties, geochemically reduced conditions, and widespread geologic occurrence of this rock type (Hansen 2010; Bianchi et al. 2013). Bianchi et al. (2013) provides a description of diffusion in a clay-hosted repository based on single-phase flow and full saturation using parametric data from documented studies in Europe (e.g., ANDRA 2005). The predominance of diffusive transport and sorption phenomena in this clay media are key attributes to impede radionuclide mobility making clay rock formations target sites for disposal of high-level radioactive waste. The reports by Hansen et al. (2010) and those from numerous studies in clay-hosted underground research laboratories (URLs) in Belgium, France and Switzerland outline the extensive scientific knowledge obtained to assess long-term clay/shale/argillite repository isolation performance of nuclear waste. In the past several years under the UFDC, various kinds of models have been developed for argillite repository to demonstrate the model capability, understand the spatial and temporal alteration of the repository, and evaluate different scenarios. These models include the coupled Thermal-Hydrological-Mechanical (THM) and Thermal-Hydrological-Mechanical-Chemical (THMC) models (e.g. Liu et al. 2013; Rutqvist et al. 2014a, Zheng et al. 2014a) that focus on THMC processes in the Engineered Barrier System (EBS) bentonite and argillite host hock, the large scale hydrogeologic model (Bianchi et al. 2014) that investigates the hydraulic connection between an emplacement drift and surrounding hydrogeological units, and Disposal Systems Evaluation Framework (DSEF) models (Greenberg et al. 2013) that evaluate thermal evolution in the host rock approximated as a thermal conduction process to facilitate the analysis of design options. However, the assumptions and the properties (parameters) used in these models are different, which not only make inter-model comparisons difficult, but also compromise the applicability of the lessons learned from one model to another model. The establishment of a reference case would therefore be helpful to set up a baseline for model development. A generic salt repository reference case was developed in Freeze et al. (2013) and the generic argillite repository reference case is presented in this report. The definition of a reference case requires the characterization of the waste inventory, waste form, waste package, repository layout, EBS backfill, host rock, and biosphere. This report mainly documents the processes in EBS bentonite and host rock that are potentially important for performance assessment and properties that are needed to describe these processes, with brief description other components such as waste inventory, waste form, waste package, repository layout, aquifer, and biosphere. A thorough description of the generic argillite repository reference case will be given in Jové Colon et al. (2014).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Influence of Microbial Membranes on Biofilm Formation, Scaling Reactions, and Production Chemistry in Engineered Energy Systems (Final Report)

Humans are engineering the deep subsurface for the purposes of energy-capture, energy-storage, and environmental mitigation. Despite the potential for microbial communities to significantly alter the effectiveness of these technologies, we have historically lacked a clear understanding of how microbial cells interact in a fractured shale system. Existing knowledge has been heavily based on genomic information, lacking studies on in situ physiologies, kinetic rates, and attachment mechanisms governing biogeochemical reactions in the system. The overarching goal of this research was to advance understanding of engineered hydrocarbon extraction systems as they evolve from newly developed environments to mature use. Plasma membranes protect microbial cells, mediate many critical functions, and respond to intracellular cues and ecological perturbations through physicochemical modifications. The project objectives were to 1) characterize variables influencing growth and membrane features of shale taxa, 2) characterize the interactions between shale matrices and microorganisms and 3) elucidate engineered and environmental processes driving biogeochemical signatures at the field scale. Objectives were realized through laboratory experiments involving growth of pure cultures and enrichments in continuous culture and biofilms; access to samples from two DOE-NETL funded energy-capture sites: Marcellus Shale Energy and Environmental Laboratory (MSEEL and MSEEL II); and through collaborations with scientists and engineers at the Environmental Molecular Science Laboratory (EMSL) and National Energy Technology Laboratory (NETL). Key findings showed (a) Halanaerobium congolense WG10 makes its membrane more fluid and thicker through increasing its polyunsaturated fatty acid (PUFA) composition under non-optimal salinities (7% and 20%) compared to the optimum (13% NaCl); (b) anionic phospholipids within the plasma membrane are important for high salinity tolerance in H. congolense WG10 while zwitterionic species modulate biofilm physiologies in both isolate and mixed cultures, and (c) tyrosine accumulation with overexpression of Na+/H+ antiporters are essential for osmoprotection in H. congolense WG10 under high salinity while upregulation of aromatic amino acid synthesis and cell envelope maintenance underpin biofilm formation. It is clear from these results that microbial persistence in fractured shale reservoirs under environmental and engineered perturbations requires strategic plasma membrane lipid chemistry adjustments and metabolic restructuring, with implications for improved shale microbiology management and more efficient hydrocarbon extraction approaches targeting microorganisms.

03 NATURAL GAS↗
DOE OSTI2021

Water treatment based on atomically engineered materials: Atomic layer deposition and beyond

Global water stress and challenges for producing sufficient supplies of fit-for-purpose water are amplifying. Atomically engineered interfaces are emerging as a powerful tool in the fabrication of advanced water treatment materials. Atomic layer deposition (ALD) and recently developed related methods, such as sequential infiltration synthesis (SIS), offer a tremendously diverse library of chemistries for interface functionalization. Thickness, stoichiometry, and physicochemical properties can be manipulated with precision. We review their fundamental physical chemistry and processing factors. ALD/SIS engineering strategies, including direct deposition, growth with intermediate layers, and secondary treatment are presented with realization of efficient water treatment. We lay out a pathway to establishing an ALD/SIS-based universal functionalization platform for water treatment, including sensitization strategies, in situ regulation, secondary reactions, and simulation/machine learning. Furthermore, we also provide a perspective on ALD/SIS-based interface engineering via synergy with other widely used interface engineering techniques to develop facile, versatile, and energy-efficient strategies for tackling increasingly complex water challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Automated System of Diagnostic Monitoring at Bureya HPP Hydraulic Engineering Installations: a New Level of Safety

This article presents the design, hardware, and software solutions developed and placed in service for the automated system of diagnostic monitoring (ASDM) for hydraulic engineering installations at the Bureya HPP, and assuring a reliable process for monitoring hydraulic engineering installations. Project implementation represents a timely solution of problems addressed by the hydraulic engineering installation diagnostics section.

42 ENGINEERING↗
DOE OSTI2021

A fast reduced model for a shell-and-tube based latent heat thermal energy storage heat exchanger and its application for cost optimal design by nonlinear programming

Numerical simulation of latent heat thermal energy storage (LHTES) systems plays a fundamental role in studying the physical process and guiding the engineering design. Discretization of the PDEs describing the nonlinear solidification/melting process of phase change materials (PCMs) leads to a large-scale complex dynamics system, where the system behavior depends on a set of parameters. In a design setting, repeated model evaluations are required over the set of parameters results in significant computational burden. In this paper, an explicit analytic solution was built for the propagation of the solidification front in a cylindrical coordinate. The analytic solution approach is further employed to develop a low computational reduced model (RM) as a module for a shell-and-tube based LHTES heat exchanger. The levelized Cost of Energy (LCOE) is used as a design metric and the RM model is used to apply system-level constraints in the nonlinear programming formulation that facilitates efficient global optimal design of the PCM properties, flow conditions and tube geometries. The use of LCOE as the design metric prevents over design of the heat transfer rate and also establishes a fair ground for evaluation of different thermal storage technologies and their integrated applications with other systems. Optimal results showed that a higher effectiveness results in a higher LCOE; the velocity of the HTF and the length of the channel are highly correlated with each other; both larger PCM latent energy and conductivity result in lower LCOE.

25 ENERGY STORAGE↗
DOE OSTI2014

Site Management Guide (Blue Book)

The U.S. Department of Energy (Department) Office of Legacy Management (LM), established in 2003, manages the Department’s postclosure responsibilities and ensures the future protection of human health and the environment. During World War II and the Cold War, the Federal government developed and operated a vast network of industrial facilities for the research, production, and testing of nuclear weapons, as well as other scientific and engineering research. These processes left a legacy of radioactive and chemical waste, environmental contamination, and hazardous facilities and materials at well over 100 sites. Since 1989, the Department has taken an aggressive accelerated cleanup approach to reduce risks and cut costs. At most Departmental sites undergoing cleanup, some residual hazards will remain at the time cleanup is completed due to financial and technical impracticality. However, the Department still has an obligation to protect human health and the environment after cleanup is completed. LM fulfills DOE’s postclosure obligation by providing long-term management of postcleanup sites which do not have continuing missions. LM is also responsible for sites under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Currently, the U.S. Army Corps of Engineers (USACE) is responsible for site surveys and remediation at FUSRAP sites. Once remediation is completed, LM becomes responsible for long-term management. LM also has responsibility for uranium processing sites addressed by Title II of the Uranium Mill Tailings Radiation Control Act (UMTRCA). UMTRCA Title II sites are sites that were commercially owned and are regulated under a U.S. Nuclear Regulatory Commission (NRC) license. For license termination, the owner must conduct an NRC-approved cleanup of any on-site radioactive waste remaining from former uranium ore-processing operations. The site owner must also provide full funding for inspections and, if necessary, ongoing maintenance. Once site cleanup is complete, LM accepts title to these sites on behalf of the United States and assumes long-term management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Operation of internal combustion engine with improved fuel efficiency

A process of operating a spark-ignited internal combustion engine (SI-ICE) with improved fuel efficiency and reduced emissions including under steady state and under lean-operating conditions at high overall air to fuel (AFR) ratios. A first supply of high octane hydrocarbon fuel, such as gasoline or natural gas, and a first supply of oxidant are fed to a fuel reformer to produce a gaseous reformate with a reforming efficiency of greater than 75 percent relative to equilibrium. The gaseous reformate is mixed with a second supply of oxidant, after which the resulting reformate blended oxidant is fed with a second supply of high octane hydrocarbon fuel to the SI-ICE for combustion. Steady state fuel efficiency is improved by more than 3 percent, when the reformate comprises from greater than about 1 to less than about 18 percent of the total volume of reformate blended oxidant fed to the engine.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Assessment of Enthalpy-Based Conditional Moment Closure Models in Predicting Ignition of Lean and Stoichiometric PRF-Air Mixtures with Temperature Inhomogeneity

Accurate prediction of the ignition delay in turbulent flows is important in developing advanced combustion technology for internal combustion engines. Enthalpy-based conditional moment closure (CMC) models are assessed with 2-D direct numerical simulation (DNS) data for ignition of homogeneous PRF-air mixtures with temperature inhomogeneity in homogeneous isotropic turbulence. The sensible-enthalpy-based CMC model is compared with the total-enthalpy-based formulation, with the focus being placed on assessing the capability of the CMC models in predicting ignition processes under different engine conditions. A priori analysis shows that the total-enthalpy-based CMC gives good predictions of the heat release rates in the lean mixtures when the temperature inhomogeneity level is low, but leads to significant overprediction under the stoichiometric condition regardless of the thermal stratification levels. On the other hand, the sensible enthalpy formulation performs well for all conditions considered in this study due to the suppressed conditional temperature fluctuations. A mapping method to model conditional scalar dissipation rates and probability density function of sensible enthalpy is also assessed.

Wang, Wei↗
DOE OSTI2024

Bioblendstocks to Optimize Mixing Controlled Compression Ignition (MCCI) Engines

In this project, a team of researchers from the University of Massachusetts Lowell, the University of Maine, and Mainstream Engineering developed an integrated process for the product of bioblendstocks to optimize mixing controlled compression ignition (MCCI) engines. The objective was to improve the energy density, sooting propensity, and cetane number of base diesel fuel while maintaining cold weather behavior. The process converts woody biomass (e.g. sawmill residues) into bio-oil through selective fast pyrolysis; the bio-oil is then selectively upgraded to form selectively oxygenated, minimally-branched hydrocarbons using non-noble metal catalysts in combination with metal-catalyzed hydrogenation. Advanced predictive models, in conjunction with existing property databases, and experimental testing are used to evaluate overall bioblendstock properties and their impact on base diesel fuel. An iterative, targeted upgrading approach was implemented to optimize the proposed bioblendstock’s properties. Assessment methodologies included techno-economic analysis, life-cycle assessment, property testing, and engine testing. Ultimately, the project team successfully produced a viable bioblendstock while identifying critical process points related to scale-up efforts. It was found that producing pyrolysis oils at 500 degrees C and with pine particle sizes of 1-2 mm led to bio-oil with a higher yield (of approximately 45 wt%) and rich amounts of aromatic alcohols. The resultant pyrolysis oil was then upgraded using a sequence of mild hydrotreating, followed by catalytic etherification and esterification, followed by another final mild hydrotreating to produce a blendstock containing saturated species with a limited, but non-zero, amount of oxygen. The aromatic alcohols produced by pyrolysis were especially helpful in this regard, as the resulting bicycloethers and derivatives exhibited high cetane numbers. While most bulk properties of the bioblendstock met or exceeded targeted thresholds, viscosity and cloud point notably fell outside the expected range; this could be addressed by blending limits and/or through the use of additives that are commonplace in current refinding practices. Identification of a bioblendstock that can be produced economically at scale while improving the performance and emissions characteristics of internal combustion engines positively affects the economy by boosting domestic fuel production and the environment by decreasing harmful emissions and increasing efficiency.

09 BIOMASS FUELS↗
DOE OSTI2020

CO 2 Capture Using Electrochemically Mediated Amine Regeneration

We describe the current status of our research on, and the development of, the Electrochemically Mediated Amine Regeneration (EMAR) process for the capture of CO2 from flue gases. The absorption step in the EMAR process is the same as in the widely used amine process, but the desorption step is accomplished electrochemically as opposed to by a thermal swing used in the amine process. Our laboratory unit has operated continuously for over 200 h, spanning 130 absorption/desorption cycles. We have established an understanding of the thermodynamics of the EMAR process and provided engineering estimates of key features (energetics and sizing) of this technology. The EMAR system does not rely on steam integration, making it a truly plug-and-play unit that can be easily deployed for a range of applications. The EMAR system can also be scaled-down for distributed, modular, and small-scale operations (e.g., stainless steel mini-mills, etc.). Here, results to date indicate that the EMAR process has the potential to be a viable option for post-combustion CO2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Understanding the ignition mechanism of high-pressure spray flames

A conceptual model for turbulent ignition in high-pressure spray flames is presented. The model is motivated by first-principles simulations and optical diagnostics applied to the Sandia n-dodecane experiment. The Lagrangian flamelet equations are combined with full LLNL kinetics (2755 species; 11,173 reactions) to resolve all time and length scales and chemical pathways of the ignition process at engine-relevant pressures and turbulence intensities unattainable using classic DNS. The first-principles value of the flamelet equations is established by a novel chemical explosive mode-diffusion time scale analysis of the fully-coupled chemical and turbulent time scales. Contrary to conventional wisdom, this analysis reveals that the high Damköhler number limit, a key requirement for the validity of the flamelet derivation from the reactive Navier–Stokes equations, applies during the entire ignition process. Corroborating Rayleigh-scattering and formaldehyde PLIF with simultaneous schlieren imaging of mixing and combustion are presented. Our combined analysis establishes a characteristic temporal evolution of the ignition process. First, a localized first-stage ignition event consistently occurs in highest temperature mixture regions. This initiates, owed to the intense scalar dissipation, a turbulent cool flame wave propagating from this ignition spot through the entire flow field. This wave significantly decreases the ignition delay of lower temperature mixture regions in comparison to their homogeneous reference. This explains the experimentally observed formaldehyde formation across the entire spray head prior to high-temperature ignition which consistently occurs first in a broad range of rich mixture regions. There, the combination of first-stage ignition delay, shortened by the cool flame wave, and the subsequent delay until second-stage ignition becomes minimal. A turbulent flame subsequently propagates rapidly through the entire mixture over time scales consistent with experimental observations. As a result, we demonstrate that the neglect of turbulence-chemistry-interactions fundamentally fails to capture the key features of this ignition process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Catalytic and electrochemical behaviour of solid oxide fuel cell operated with simulated-biogas mixtures

Being produced from organic matters of wastes (bio-wastes) through a fermentation process, biogas mainly composed of CH{sub 4} and CO{sub 2} and can be considered as a secondary energy carrier derived from solar energy. To generate electricity from biogas through the electrochemical process in fuel cells is a state-of-the-art technology possessing higher energy conversion efficiency without harmful emissions compared to combustion process in heat engines. Getting benefits from high operating temperature such as direct internal reforming ability and activation of electrochemical reactions to increase overall system efficiency, solid oxide fuel cell (SOFC) system operated with biogas becomes a promising candidate for distributed power generator for rural applications leading to reductions of environmental issues caused by greenhouse effects and bio-wastes. CO{sub 2} reforming of CH{sub 4} and electrochemical oxidation of the produced syngas (H{sub 2}–CO mixture) are two main reaction processes within porous anode material of SOFC. Here catalytic and electrochemical behavior of Ni-ScSZ (scandia stabilized-zirconia) anode in the feed of CH{sub 4}–CO{sub 2} mixtures as simulated-biogas at 800 °C were evaluated. The results showed that CO{sub 2} had strong influences on both reaction processes. The increase in CO{sub 2} partial pressure resulted in the decrease in anode overvoltage, although open-circuit voltage was dropped. Besides that, the simulation result based on a power-law model for equimolar CH{sub 4}−CO{sub 2} mixture revealed that coking hazard could be suppressed along the fuel flow channel in both open-circuit and closed-circuit conditions.

09 BIOMASS FUELS↗
DOE OSTI2019

Validation of Puncture Simulations with Various Probe Geometries

Ductile materials fail through mechanisms of void nucleation and coalescence. A tensile test of a ductile metal begins with reversible elastic deformation, proceeds through permanent plastic deformation, and ends with rupture. Dislocations in the grains of a metal do not slip in the elastic range but begin moving in the plastic range. As the dislocations interact with grain boundaries and each other, they cause increasing resistance to plastic deformation, termed work hardening. The applied load and the true stress rise together during this process. When the dislocations have no room to move, voids open up in the material. As these voids coalesce into cracks, the true stress rises rapidly and the sustained load decreases. Rupture occurs when the cracks propagate through the specimen and it loses all load-carrying capacity. The complexity of the ductile fracture phenomenon continues to attract substantial attention from researchers. Sharp objects in a production environment can puncture fragile components made from ductile metals. Non-linear dynamic simulations help engineers to plan processes such that these components do not fail when an accident happens. The projectile is termed a probe, and the component is the target. The surface of the probe that contacts the target may be sharp, blunt, or flat. Probes are typically cylindrical for simplicity, but other shapes that exist in the production environment are equally applicable.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗