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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Sorbent-based oxygen separation with YBC114 for energy storage systems

In our report we aimed to design, build, and evaluate an oxygen separation system to provide an inert sweep gas with low oxygen partial pressure (pO2) to redox-active thermochemical energy conversion reactors for a range of applications, including two-step redox cycles for thermochemical energy storage, water splitting, and carbon-dioxide splitting. The separation is based on an oxygen-selective sorbent, YBaCo4O7+δ (YBC114), which has excellent oxygen sorption and desorption properties demonstrated in our previous work. The oxygen separation performance of YBC114 was comprehensively studied by thermogravimetric analysis, sorption breakthrough experiments, and temperature swing sorption - desorption cycles. The results reveal that YBC114 can produce inert sweep gas with an oxygen concentration of less than 100 ppmv for at least 20 min during the thermal swing adsorption (TSA) cycle with the current sorption bed configuration, and the performance is consistent from cycle to cycle. The optimal sorption and desorption temperatures for the TSA process with YBC114 are determined to be 300 °C and 500 °C, respectively. Although challenges remain for the current separation system (e.g., high sorption temperature and slow kinetics), this study demonstrates the potential to use the oxygen-selective sorbent to produce an inert sweep gas, the feasibility of the oxygen separation concept, and guides new sorbent material development to make this application economically practical. A simple procedure is described for designing the YBC114 oxygen separation process.

42 ENGINEERING↗
DOE OSTI2016

Aging Infrastructure: Application of System Health Monitoring at the Defense Waste Processing Facility - 16069

The disposition of high level waste (HLW) into borosilicate glass canistered waste forms began at SRS in 1996. Since that time, the Defense Waste Processing Facility (DWPF) has produced nearly four thousand HLW canisters. The DWPF is now approaching 20 years of radioactive service and 25 years of operation since the commencement of nonradioactive testing in 1990. Many facility systems are challenged by equipment or component obsolescence, which places a premium on proper work planning, engineering, and maintenance resource allocation to ensure facility reliability. To this end, Savannah River Remediation (SRR) implements programs and procedures for performance monitoring of structures, systems, and components (SSCs) within all of its processing facilities. As these programs have matured, they have helped to identify vulnerabilities within facility systems and provided a framework for ranking system assets to ensure correct priority is established and maintained. This paper provides an overview of how SRR structures and implements system performance monitoring with specific focus on the recent replacement of the DWPF Safety Grade Purge Flowmeters. This case study will discuss: 1) How the performance monitoring process identified an availability risk due to the minimal vendor support for the in-use flow transmitters, 2) The design changes developed as part of the project to transition to a different measurement technology, which includes operational lessons learned from the original installation, 3) The execution of the replacement effort, which was complicated by the fact that the purge system is a Vital Safety System (VSS) and not easily taken out of service for extended maintenance, and 4) The need to consider future maintainability, particularly given that continued acceleration in technical innovation will likely increase the frequency of equipment obsolescence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Molten Salt Oxidation of Ion Exchange and Oils in Carbonate Salts and Evaporator Residue - 16531

Molten Salt Oxidation is a well-studied and robust technology. Recently, renewed interest in the technology has been seen due to limitations on the use of incineration for hazardous and radioactive waste streams. The nuclear research center at Rez, near Prague, has been investigating a bench scale molten salt oxidation system to provide insight for the design of a pilot scale system to condition spent ion exchange resin and scintillator oils. The use of both an eutectic K/Na/Li carbonate salt and a simulated residue salt for liquid waste obtained from evaporated primary coolant of nuclear reactors was examined. In these studies the usable capacity of the salts were examined. Materials doped with surrogate radioisotopes were processed and the capture efficiency was measured. Corrosion of the reactor vessel is of significant engineering concern. Corrosion coupon tests were performed for Inconel HX and stainless steel. These tests provided corrosion rates to assist in design of pilot scale systems. While the bench scale reactor's detention time was too short to provide complete combustion, the values of emissions were tracked and showed an increase in the combustion efficiency at temperatures greater than 750 deg. C. A two part reactor has been designed and work is planned to continue to optimize the system. Additionally, further work has examined the final conditioning of salt which has been saturated with radionuclides after processing organic waste streams A conceptual pilot plant has been designed to solidify radionuclide saturated salt into a form acceptable for repositories according to EU directives. Saturated salt is milled to a powder and immobilized in a matrix with a high percentage of waste loading. Both geo-polymer and polysiloxane matrices have been methods for low temperature immobilization. Conditioning in this manner decreases operating and capital costs when compared to current conditioning technologies and procedures utilized for high volume reduction factors of final waste forms. (authors)

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

Supercritical Reforming of Wet Ethanol for High Efficiency Direct-injection Heavy-duty Compression-ignition Engines

The purpose of the research was to investigate the potential of using a mature bio-fuel in heavy-duty compression ignition engines. By co-optimizing both the fuel characteristics and engine system the potential for a superior outcome was demonstrated. The use of wet bio-ethanol eliminates the majority of the energy intensive distilling and dehydrating fuel production processes, which moves the fuel towards carbon neutral and also lowers the fuel costs. The relatively high water content of the resulting fuel is leveraged in the proposed novel combustion system by incorporating an integrated high efficiency exhaust waste heat recovery system. This results in significantly higher thermal efficiency. In addition the combustion system features low criteria pollutant emissions and the potential to reduce the initial cost of the engine system hardware. Substantial societal benefits are demonstrated through the co-optimization of the fuel and engine system. A computational proof-of-concept study has been performed to demonstrate the potential benefits of a novel wet ethanol heavy-duty compression ignition combustion system featuring integrated exhaust waste heat recovery. A combined in-cylinder closed cycle 3D computational fluid dynamics (CFD) - 1D engine system simulation approach was used. The models were validated to baseline engine data using diesel fuel and then applied to the wet ethanol study. The original concept was to maximize exhaust waste heat recovery through supercritical reforming of the wet ethanol fuel. Phase I simulation results indicated that the optimal solution for maximum engine efficiency gains were realized through maximizing thermo-mechanical recuperation with negligible fuel reformation. The results show the potential to achieve impressive gains in brake thermal efficiency (BTE) over the base diesel engine. The potential to increase BTE up to 20.9% over the base diesel engine was demonstrated, with even larger gains possible through reduced in-cylinder heat transfer losses. The majority of the efficiency gains were realized through integrated high efficiency exhaust waste heat recovery. The concept also has the potential to achieve future ultra-low NO x emissions standards and negligible engine-out soot emissions. The mixing controlled combustion of high temperature wet ethanol features relatively low engine-out NO x emissions without the need for exhaust gas recirculation (EGR). The soot free combustion enabled by the relatively high oxygen content of ethanol also allows for the use of stoichiometric mixing controlled combustion, which is not practical with diesel fuel. When stoichiometric combustion is used a simple passive 3-way catalyst can be used for exhaust emissions after-treatment and near zero tailpipe emissions. The Phase I simulations results have defined the system layout and requirements in preparation for the Phase II experimental proof-of-concept study. The potential applications of the research include most current applications of diesel engines. The Phase I study focused on heavy-duty on-highway class 8 trucks. However, virtually any application that requires highly efficient clean power generation would benefit from the novel engine system proposed. The results indicate substantial fuel cost savings and reduced greenhouse gas emissions with similar or reduced initial system hardware costs compared to modern diesel engine systems.

09 BIOMASS FUELS↗
DOE OSTI2023

Operation Optimization using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

NEAMS Workbench Status and Capabilities

The mission of the US Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished by using computing architectures that range from laptops to leadership-class facilities. The NEAMS Workbench is a new initiative that will facilitate the transition from conventional tools to highfidelity tools by providing a common user interface for model creation, review, execution, output review, and visualization for integrated codes. The Workbench can use common user input, including engineering-scale specifications that are expanded into application-specific input requirements through the use of customizable templates. The templating process can enable multifidelity analysis of a system from a common set of input data. Additionally, the common user input processor can provide an enhanced alternative application input that provides additional conveniences compared with native input, especially for legacy codes. Expansion of the integrated codes and application templates available in the Workbench will broaden the NEAMS user community and will facilitate system analysis and design. Current and planned capabilities of the NEAMS Workbench are detailed herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

NEAMS Workbench Status and Capabilities

The mission of the US Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished by using computing architectures that range from laptops to leadership-class facilities. The NEAMS Workbench is a new initiative that will facilitate the transition from conventional tools to high fidelity tools by providing a common user interface for model creation, review, execution, output review, and visualization for integrated codes. The Workbench can use common user input, including engineering-scale specifications that are expanded into application-specific input requirements through the use of customizable templates. The templating process can enable multifidelity analysis of a system from a common set of input data. Additionally, the common user input processor can provide an enhanced alternative application input that provides additional conveniences over the native input, especially for legacy codes. Expansion of the integrated codes and application templates available in the Workbench will broaden the NEAMS user community and will facilitate system analysis and design. Current and planned capabilities of the NEAMS Workbench are detailed here.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗
DOE OSTI2023

Signal Decomposition for Intrusion Detection in Reliability Assessment in Cyber Resilience (Summary Report)

The complexity of assuring cyber resilience for physical process interactions in connected systems such as energy grids increases dramatically as the coupling between processes becomes more direct and responsive. An example of this growing complexity is provided by Integrated Energy Systems (IES), in which various processes such as nuclear heat generation and commodity production are being directly coupled for increased responsiveness to highly variable signals such as market pricing or electricity demand. As such, the potential attack surface of the coupled processes is larger than the two processes independently. Securing these complex systems requires two-fold monitoring: cybersecure monitoring for potential malicious incursion, and physics monitoring for system tampering. Physics monitoring includes analyzing the behavior of the signals within the system for anomalous behavior. This analysis has been shown to be insufficient if approached by only data-driven machine learning and artificial intelligence (MLAI) techniques or only low-level model comparison. Previous efforts at Purdue University suggested combining high-fidelity models with MLAI algorithms as a basis for a software tool for detecting anomalies in physical processes. This work built on that suggestion, developing an advanced library for signal decomposition and analysis using both MLAI and high-fidelity physics algorithms for greatly improved anomaly detection, especially false data injection. This software can be used as part of a secure imbedded intelligence (SEI) system designed under Consequence-driven Cyber-informed Engineering (CCE) for complex coupled systems. This library established a foundation for online and posteriori analysis of digital signals for the purpose of detecting potential malicious tampering in digital signals representing physical processes. Demonstrations carried out throughout the development highlight the effective use of characterization algorithms to detect signal perturbations, particularly triangle attack-style perturbations, in three wide-ranging applications: seismic monitoring, nuclear thermal hydraulics system simulation, and custom manufacturing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Rewiring cell-free metabolic flux in E. coli lysates using a block—push—pull approach

Abstract Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the ‘block—push—pull’ concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A novel tool for improving the data collection process during control room modernization human-system interface testing and evaluation activities - 271

The U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program is developing a scientific basis to extend the existing U.S. nuclear power plant (NPP) operating life beyond the current 60-year licensing period and to ensure NPP long-term reliability, productivity, safety, and security. Under the Advanced Instrumentation, Information, and Control (II and C) Systems Technologies pathway, the LWRS Program conducts targeted research and development to address long-term aging and obsolescence of existing instrumentation and control technologies, as well as to implement and test new digital II and C technology that enables broad innovation and business improvement in the NPP operating model. To this end, the role of human factors engineering (HFE) is important as part of ensuring that the control room modernization (CRM) activities account for the operator's cognitive and physiological characteristics. Part of the HFE process for CRM entails conducting tests and evaluations (T and Es) that will inform the design of new human-system interface (HSI) technologies. Qualitative data that captures operator feedback and important human-system interactions are an important part of T and E. However, the analyzing this qualitative data in order to provide actionable design recommendations can be time-consuming and error prone. This paper presents an early version of a tool, which uses a combination of natural language processing and supervised machine learning to support the analysis of qualitative data. The objectives of this tool is to improve the process of (1) sifting through freeform text for improved design issue identification, (2) maintaining consistency in theme coding conventions, and (3) readily providing actionable design guidance that can be traceable to state-of-the-art HFE guidelines such as NUREG-0700. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗
DOE OSTI2019

Experimental and Mathematical Simulation Study on the Granulation of a Modified Basic Oxygen Furnace Steel Slag

Basic oxygen furnace (BOF) steel slag is a major waste of the steelmaking industry. Utilization of BOF slag contributes to the sustainability of the steel industry by alleviating its environmental impact. Vitrification during cooling is an effective method to promote the cementitious activity of slags with the aim to apply slags in high value-added applications. In the present study, an Al{sub 2}O{sub 3}- and SiO{sub 2}-modified BOF slag was water granulated at a pilot scale. The amorphous and mineral fractions were measured quantitatively. The critical cooling rate to vitrify the modified slag was calculated through the Time-Temperature-Transformation diagrams constructed using in situ confocal scanning laser microscopy. To provide an insight into the crystallization behavior during the granulation process, a mathematical model was developed. The model was validated by comparing the amorphous fraction obtained from experiments with that from simulation. Temperature profiles of the slag particles with varied sizes were calculated with the aid of COMSOL Multiphysics software. The effect of particle size on the vitrified fraction was discussed in detail and the temperature gradient from surface to center of the particle was identified. The results provide novel fundamental understanding of the vitrification process regarding to the slag valorization, which will help the industrial implementation of granulation for pollution remediation and other engineered environmental systems such as chemical industry and pharmaceutical industry.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Manganese in drinking-water reservoirs: a multi-disciplinary review of current issues, biogeochemical controls, and oxygenation-based management

Decreased water quality and increased treatment costs due to excess manganese (Mn) in drinking-water supplies are critical issues globally. To combat on-going and emerging taste and odour issues with Mn and other contaminants (e.g., algal toxins), many utilities are using engineered oxygenation or aeration (EOA) systems to improve water quality in lakes and reservoirs. Resultant shifts in key biogeochemical and physical processes are still poorly understood, often leading to inefficiently managed systems. Paired with knowledge gaps regarding environmental drivers of Mn and the complexity of Mn redox kinetics, Mn problems persist. This review presents the state of current research in areas critical to optimisation of EOA mitigation of Mn, with focus on i) Mn biogeochemical cycling within drinking-water reservoirs; ii) influences of local catchment geology, hydrology, and land use on Mn dynamics; and iii) Mn management using different EOA approaches. The importance of considering the combined implications of these factors for successful Mn management in reservoirs is highlighted by an evaluation of relevant field-based studies; a wide range in EOA performance is observed, from a 97 % decrease in soluble Mn up to a ∼400 % increase in total Mn. Despite the breadth of studies that consider Mn in water-supply systems, there are still several areas of research which warrant further investigation, including: the influence of natural sources and anthropogenic activities on Mn within a given catchment, Mn speciation and transport in stratified and destratified lakes and reservoirs, and optimal site-specific EOA strategies for Mn mitigation.

Aeration↗
DOE OSTI2026

Bridge Connectivity Dictates Spin Interactions and Triplet Pair Dynamics in Intramolecular Singlet Fission

Electron spin plays a critical role in determining the structure, dynamics, and reactivities of molecular excited states, including multiexciton processes such as singlet fission. These systems exhibit triplet pair states whose excited state dynamics can be widely tuned through molecular engineering. For example, the electronic coupling between covalently linked chromophores can be readily modulated using chemical bridges to control proximity, quantum interference, or resonance effects. However, less is known about how spin coupling interactions are impacted by chromophore architecture, and how this influences triplet pair recombination dynamics. Here, in this study, we investigate the role of bridge connectivity and chromophore identity in modulating interchromophore exchange and dipolar coupling interactions for a series of pentacene and tetracene dimers bridged by alternant hydrocarbons (phenylene, naphthalene, anthracene). Using both time-resolved electron paramagnetic resonance and transient absorption spectroscopy, we find that the boundedness and recombination pathways of the triplet pair spins are highly sensitive to molecular architecture and chromophore-specific magnetic dipolar interactions. Notably, nominally ferromagnetic and antiferromagnetic eigenstates result in distinct spin state orderings, consistent with predictions from quantum interference-based graphical models. These findings establish new design principles for tuning spin dynamics in iSF materials, with implications for photonic and quantum information applications.

He, Guiying [City Univ. of New York (CUNY), NY (Un↗
DOE OSTI2017

Stability of entrainment of a continuum of coupled oscillators

Complex natural and engineered systems are ubiquitous, and their behavior is challenging to characterize and control. Here, we examine the design of the entrainment process for an uncountably infinite collection of coupled phase oscillators that are all subject to the same periodic driving signal. In the absence of coupling, an appropriately designed input can result in each oscillator attaining the frequency of the driving signal, with a phase offset determined by its natural frequency. We also consider a special case of interacting oscillators in which the coupling tends to destabilize the phase configuration to which the driving signal would send the collection in the absence of coupling. In this setting, we derive stability results that characterize the trade-off between the effects of driving and coupling, and compare these results to the well-known Kuramoto model of a collection of free-running coupled oscillators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Effect of Premixed Fuel Preparation for Partially Premixed Combustion with a Low Octane Gasoline on a Light-Duty Multi-Cylinder Compression Ignition Engine

Gasoline compression ignition concepts with the majority of the fuel being introduced early in the cycle are known as partially premixed combustion (PPC). Previous research on single- and multi-cylinder engines has shown that PPC has the potential for high thermal efficiency with low NOx and soot emissions. A variety of fuel injection strategies has been proposed in the literature. These injection strategies aim to create a partially stratified charge to simultaneously reduce NOx and soot emissions while maintaining some level of control over the combustion process through the fuel delivery system. The impact of the direct injection strategy to create a premixed charge of fuel and air has not previously been explored, and its impact on engine efficiency and emissions is not well understood. This paper explores the effect of sweeping the direct injected pilot timing from -91° to -324° ATDC, which is just after the exhaust valve closes for the engine used in this study. During the sweep, the pilot injection consistently contained 65% of the total fuel (based on command duration ratio), and the main injection timing was adjusted slightly to maintain combustion phasing near top dead center. A modern four cylinder, 1.9 L diesel engine with a variable geometry turbocharger, high pressure common rail injection system, wide included angle injectors, and variable swirl actuation was used in this study. The pistons were modified to an open bowl configuration suitable for highly premixed combustion modes. The stock diesel injection system was unmodified, and the gasoline fuel was doped with a lubricity additive to protect the high pressure fuel pump and the injectors. The study was conducted at a fixed speed/load condition of 2000 rpm and 4.0 bar brake mean effective pressure (BMEP). The pilot injection timing sweep was conducted at different intake manifold pressures, swirl levels, and fuel injection GTP-15-1067, Dempsey 2 pressures. The gasoline used in this study has relatively high fuel reactivity with a research octane number of 68. The results of this experimental campaign indicate that the highest brake thermal efficiency and lowest emissions are achieved simultaneously with the earliest pilot injection timings (i.e., during the intake stroke).

33 ADVANCED PROPULSION SYSTEMS↗