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NASA NTRS2019

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and data science, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Core Size↗

NASA NTRSDate not supplied

A New Concurrent Engineering Tool for the New Mission Design Center at NASA Ames Research Center

The NASA Ames Mission Design Center (MDC) has undergone a significant transformation process in recent years, culminating in becoming a true Concurrent Engineering Center. The underlying goal of this transformation is to better serve the Ames PI community in a cost-effective and rapidly-responsive way, providing quality products pivotal to the decision-making proposal strategy of our center. The four pillars of the change focus on four areas: personnel, physical places, tools, and training. Personnel: the MDC switched from using a dedicated pool of engineers—mostly entry-level career—for a matrixed approach with more experienced Subject Matter Experts, usually involved in spaceflight projects. These SMEs get detailed to the MDC for the duration of the study on a part-time or full-time basis. Physical places: The physical aspect pertains mostly to the layout of the new Engineering building and the dedicated concurrent engineering layout to foster collaboration. The current plan includes a dedicated space for concurrent engineering sessions as well as dedicated project rooms for concept studies. Tool: the MDC team is developing a new in-house concurrent engineering tool to facilitate concurrent engineering sessions. The team leveraged the many lessons learned and insight gained from using the current concurrent engineering tool, in use since 2007. SMEs have been involved throughout its design and development, ensuring accuracy and providing validity to the implementation approach. This new tool is database-driven and allows a team to work concurrently on the same model of a mission concept. “Workspaces” are provided for each of the traditional spacecraft mission design disciplines, including cost accounting and systems engineering. There are multiple tiers of fidelity available within each workspace, which can be completed parametrically or independently from the other disciplines as needed or synchronously with the other disciplines. A “commit” step synchronizes a workspace with the mission database and identifies any potential conflicts, along with the user who entered the conflicting data. A Mission Summary workspace enables a Study Lead to run an effective CE session, displaying key graphics, workspace status information, and technical and monetary budget information. This new CE tool will be undergoing Beta Testing with its primary user base and a limited Parts database in the summer of 2020. The team plans to release the first fully operational version in December 2020. Training: working in early concept development and maturation for a space mission requires a unique mindset and being comfortable with uncertainties in an environment where requirements are not yet fully developed, and where changes and trade-offs happen at a high tempo. The MDC started a weekly training program to ensure a common knowledge base on how do develop and mature early concept studies, as well as how to operate in a concurrent engineering environment. In conclusion, the MDC transformation will provide the overall PI community focused on cost-effective small satellite scientific missions with a powerful tool to address and mature early concepts more effectively and efficiently.

David Mauro↗

NASA NTRS2020

Assisted Authoring of Model-Based Systems Engineering Documents

In systems engineering practices system design and analysis have historically been performed using a document-centric approach where stakeholders produce a number of documents that represent their views on a system under development. Given the ad-hoc, disparate, and informal nature of natural language documents, these views become quickly inconsistent. Rigor in engineering work is also lost in the transition from model based engineering design and analysis to engineering documents. Once the documents are delivered, the engineering portion of the work is disconnected. In the Open Model Based Engineering Environment (OpenMBEE), Cross-References (aka transclusions) synthesize data for engineering when the information is not simply hyperlinked, but referenced in place in a document, upgrading a document-based process with model-based engineering technology. Those Cross-References are nowadays partially created manually, putting a burden on the engineer who is authoring the document.This paper presents an approach which can assist the engineer by providing machine-generated suggestions for Cross-References using language processing, graph analysis, and clustering technologies on model data managed by the OpenMBEE infrastructure.

Gomes, Ivan↗

DOE OSTI2019

3-D Modeling of the CFR Engine for the Investigation of Knock on Natural Gas

Engine knock and misfire are barriers to pathways leading to higher efficiency natural gas (NG) engines, where the general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by low emissions limits and the wide range of chemical reactivity in pipeline quality NG, making the understanding of fuel-engine interactions essential to achieving high efficiencies in spark-ignited NG engines. The present work highlights a three-dimensional computational fluid dynamics (CFD) model of the Cooperative Fuel Research (CFR) engine to investigate knock behavior when running on NG. Using a Converge CFD model of the CFR engine fuel-engine interactions that lead to knock with NG, including effects of fuel reactivity, engine operating parameters, and exhaust gas recirculation, are being investigated. A GT-Power model is used to estimate appropriate initial conditions in the Converge CFD model, including cylinder wall, piston, valves, and port surface temperatures as well as residual gas fraction. In order to validate the model, in-cylinder pressure data taken with a CFR engine is compared to model predictions while varying compression ratio, CA50, and BMEP.

Bestel, Diego↗

DOE OSTI2019

3-D Modeling off the CFR Engine for the Investigation of Knock on Natural Gas

Engine knock and misfire are barriers to pathways leading to high-efficiency Natural Gas (NG) engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by low emissions limits and the wide range of chemical reactivity in pipeline quality NG (65< MN<95). In order to realize diesel-like efficiencies, spark-ignited NG engines must be designed to operate at high BMEP near knock limits over a wide range of fuel reactivity. This requires a deep understanding regarding combustion-engine interactions important in flame propagation and end-gas autoignition. The present work highlights a three-dimensional computational fluid dynamics (CFD) model of the Cooperative Fuel Research (CFR) engine to investigate knock behavior with NG. The CFR engine model is used to investigate fuel-engine interactions that lead to knock with NG, including effects of fuel reactivity, engine operating parameters, and exhaust gas recirculation (EGR). Cylinder wall, piston, valves, and port surface temperatures are estimated with a 1-D Three-Pressure Analysis (TPA) model. Model validation was performed by comparing model predictions with experimental data taken with a CFR engine over varying compression ratio, CA50, EGR fraction and BMEP.

Bestel, Diego↗

DOE OSTI2025

Fuel Property Effects on Stochastic Preignition Events During Engine Load Transitions

Stochastic preignition (SPI) is an abnormal combustion phenomenon that can cause catastrophic engine damage. There have been several proposed mechanisms of SPI, where a uniform source is still not certain, however, SPI tendencies have been shown to be influenced by engine operating conditions, oil composition, engine age, and fuel chemical and physical properties. Laboratory research and testing for SPI propensity is challenging given the stochastic nature of events, as well as the potential for significant degradation of the engine platform and measuring equipment over time. Thus, SPI specific experiments are generally conducted under either sustained or cyclic patterning of steady-state operating conditions to avoid the influence of transient engine boundary conditions on test parameters of interest (e.g. oil additive package, fuel properties, engine speed/load, etc.). In this work a cyclically varying SPI test sequence involves a 5 min engine warmup period at a low engine load of around 4 bar gross indicated mean effective pressure (IMEPg), followed by a transition to high load (~20 bar IMEPg) at a constant 2000 rev/min engine speed for a total of 25 min. This individual test sequence load schedule is then sequentially repeated 10 times to generate significant statistical data for analysis. This work examines the influence of fuel chemical and physical properties on SPI tendency during the unsteady portion of the 10-cycle sequence (the first 5 min of the high load operation in each sequence of the loading cycle) which has been discarded from previous analyses due to the uncertainty in engine operating and thermal boundary conditions. Results from this analysis suggest an increasing trend in the ratio of SPI events during the unsteady test period relative to the steady test period with increasing fuel Reid Vapor Pressure (RVP), implying differences in uncontrolled ignition source terms, possibly from, fuel wall interactions and retention during the load transition phase of the test.

Splitter, Derek [ORNL] (ORCID:0000000174044047)↗

DOE OSTI2017

A numerical investigation on methane combustion and emissions from a natural gas-diesel dual fuel engine using CFD model

Natural gas (NG)-diesel dual fuel engines have been criticized for their high emissions of unburned methane. The past research on methane emissions from dual fuel engines has focused on the measurement of methane concentration in exhaust gases. The development of approaches capable of minimizing methane emissions requests the detailed spatial distribution of methane in-cylinder during the combustion and post combustion processes. However, it is difficult to experimentally measure the spatial distribution of methane in-cylinder. Here this research presents a numerical study on the combustion process of a NG-diesel dual fuel engine using the computational fluids dynamics (CFD) model CONVERGE coupled with a reduced primary reference fuel (PRF) mechanism. The model was validated against the heat release process and the emissions of nitrogen oxide, methane and carbon monoxide measured in a single cylinder dual fuel engine. The validated CFD model was applied to investigate the combustion of methane and n-heptane and the spatial distribution of methane in the dual fuel engine. This is most likely the first attempt to visualize the spatial distribution of methane in dual fuel engines using CFD. The objective of this study is to numerically simulate the methane combustion process, especially the methane present outside the pilot spray, quantify the methane combustion in each combustion stage, and visualize the spatial methane distribution in cylinder. The results showed that the momentum produced by the pilot fuel injection and combustion pushed the combustion products of pilot fuel and methane within the pilot spray plume toward the unburned methane-air mixture. Such a movement enhanced the mixing of the hot combustion products and the relatively cold unburned methane-air mixture during the main combustion process and dominated the combustion of methane presented outside the pilot fuel spray plume. Based on the simulation results at a low load condition (4.05 bar), the main combustion process consumed 43–53% of the methane fumigated into the intake mixture. The post-combustion oxidation process consumed 17–29% of the intake methane, which was 36.2–51.8% methane that survived the main combustion process. In comparison, 27–35% methane emitted the engine without participating the combustion process. The unburned methane at exhaust valve opening was mainly observed at the center of the cylinder. In comparison, the contribution of the crevice and boundary layer around the cylinder liner to methane emissions was relatively small. The slip of methane through the dual fuel engines was due to the fact that the premixed mixture was too lean to support the propagation of the turbulent flame initiated by the pilot fuel and the lack of pilot fuel vapor reaching the center of the combustion chamber because of the geometric limitations of the fuel injection system and the reduced mass of pilot fuel injected into the cylinder. The approaches aiming to enhance the combustion of methane and minimize methane emissions from dual fuel engines should focus on those capable of increasing the volume of pilot fuel vapor formed after injected into the cylinder.

42 ENGINEERING↗

DOE OSTI2012

Effects of Gasoline Direct Injection Engine Operating Parameters on Particle Number Emissions

A single-cylinder, wall-guided, spark ignition direct injection engine was used to study the impact of engine operating parameters on engine-out particle number (PN) emissions. Experiments were conducted with certification gasoline and a splash blend of 20% fuel grade ethanol in gasoline (E20), at four steady-state engine operating conditions. Independent engine control parameter sweeps were conducted including start of injection, injection pressure, spark timing, exhaust cam phasing, intake cam phasing, and air-fuel ratio. The results show that fuel injection timing is the dominant factor impacting PN emissions from this wall-guided gasoline direct injection engine. The major factor causing high PN emissions is fuel liquid impingement on the piston bowl. By avoiding fuel impingement, more than an order of magnitude reduction in PN emission was observed. Increasing fuel injection pressure reduces PN emissions because of smaller fuel droplet size and faster fuel-air mixing. PN emissions are insensitive to cam phasing and spark timing, especially at high engine load. Cold engine conditions produce higher PN emissions than hot engine conditions due to slower fuel vaporization and thus less fuel-air homogeneity during the combustion process. E20 produces lower PN emissions at low and medium loads if fuel liquid impingement on piston bowl is avoided. At high load or if there is fuel liquid impingement on piston bowl and/or cylinder wall, E20 tends to produce higher PN emissions. This is probably a function of the higher heat of vaporization of ethanol, which slows the vaporization of other fuel components from surfaces and may create local fuel-rich combustion or even pool-fires.

02 PETROLEUM↗

DOE OSTI2015

Identification and quantification analysis of nonlinear dynamics properties of combustion instability in a diesel engine

The cycling combustion instabilities in a diesel engine have been analyzed based on chaos theory. The objective was to investigate the dynamical characteristics of combustion in diesel engine. In this study, experiments were performed under the entire operating range of a diesel engine (the engine speed was changed from 600 to 1400 rpm and the engine load rate was from 0% to 100%), and acquired real-time series of in-cylinder combustion pressure using a piezoelectric transducer installed on the cylinder head. Several methods were applied to identify and quantitatively analyze the combustion process complexity in the diesel engine including delay-coordinate embedding, recurrence plot (RP), Recurrence Quantification Analysis, correlation dimension (CD), and the largest Lyapunov exponent (LLE) estimation. The results show that the combustion process exhibits some determinism. If LLE is positive, then the combustion system has a fractal dimension and CD is no more than 1.6 and within the diesel engine operating range. We have concluded that the combustion system of diesel engine is a low-dimensional chaotic system and the maximum values of CD and LLE occur at the lowest engine speed and load. This means that combustion system is more complex and sensitive to initial conditions and that poor combustion quality leads to the decrease of fuel economy and the increase of exhaust emissions.

42 ENGINEERING↗

DOE OSTI2011

Materials-Enabled High-Efficiency (MEHE) Heavy-Duty Diesel Engines

The purpose of this Cooperative Research and Development Agreement (CRADA) between UTBattelle, Inc. and Caterpillar, Inc. was to improve diesel engine efficiency by incorporating advanced materials to enable higher combustion pressures and temperatures necessary for improved combustion. The project scope also included novel materials for use in advanced components and designs associated with waste-heat recovery and other concepts for improved thermal efficiency. Caterpillar initially provided ORNL with a 2004 Tier 2 C15 ACERT diesel engine (designed for on-highway use) and two 600 hp motoring dynamometers. The first year of the CRADA effort was focused on establishing a heavy-duty experimental engine research cell. First year activities included procuring, installing and commissioning the cell infrastructure. Infrastructure components consisted of intake air handling system, water tower, exhaust handling system, and cell air conditioning. Other necessary infrastructure items included the fuel delivery system and bottled gas handling to support the analytical instrumentation. The second year of the CRADA focused on commissioning the dynamometer system to enable engine experimentation. In addition to the requirements associated with the dynamometer controller, the electrical system needed a power factor correction system to maintain continuity with the electrical grid. During the second year the engine was instrumented and baseline operated to confirm performance and commission the dynamometer. The engine performance was mapped and modeled according to requirements provided by Caterpillar. This activity was further supported by a Work-for-Others project from Caterpillar to evaluate a proprietary modeling system. A second Work-for-Others activity was performed to evaluate a novel turbocharger design. This project was highly successful and may lead to new turbocharger designs for Caterpillar heavy-duty diesel engines. During the third (and final) year of the CRADA, a novel valve material was evaluated to assess high temperature performance and durability. A series of prototype valves, composed of a unique nickel-alloy was placed in the engine head. The engine was aggressively operated using a transient test cycle for 200 hours. The valve recession was periodically measured to determine valve performance. Upon completion of the test the valves were removed and returned to Caterpillar for additional assessment. Industrial in-kind support was available throughout the project period. Review of the status and research results were carried out on a regular basis (meetings and telecons) which included direction for future work activities. A significant portion of the industrial support was in the form of information exchange and technical consultation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Heavy Duty Natural Gas Single Cylinder Research Engine Installation, Commissioning, and Baseline Testing

Natural Gas (NG) Internal Combustion Engines (ICE) are a promising alternative to diesel engines for on-road heavy-duty applications to reduce greenhouse gas and harmful pollutant emissions. NG engines have not been widely adopted due to the lower thermal efficiency compared with diesel engine counterparts. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform to acquire reliable and repeatable data. A SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit implementation of real-time advanced combustion control. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions while achieving effective control of all engine control and operation variables. This test cell will be used to conduct a research program to develop new and innovative control algorithms and CFD optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE heavy-duty on-road applications.

03 NATURAL GAS↗

NASA NTRS2021

Future Model-Based Systems Engineering Vision and Strategy Bridge for NASA

A vision for the future of model-based systems engineering (MBSE) at NASA in 2029 and a strategy bridge towards that future are presented. Strategic thinking and leading change concepts were used to analyze reports and presentations on global trends and visionary thinking about the future of systems and digital engineering. The context, strategic time horizon, stakeholders, strategic challenges, strategic advantages, driving forces, and opportunities were considered. The analysis resulted in a future vision of MBSE that shows what NASA systems engineers and digital machines will do to perform rapid, extraordinary, and unprecedented missions. The NASA systems engineer, in this future vision, works with a global project team in a virtual and collaborative environment, engineers the system, and uses digital approaches as the routine and default way of working. The digital machines provide data-driven and automated mission designs; have a backbone of program and project management, systems engineering, and product life-cycle management; and are a knowledge-sharing infrastructure. The NASA systems engineer and the systems engineering team are envisioned to use digital machines to plan and perform rapid exploration missions, develop a digital twin that lasts across the life cycle, and develop enduring and adaptable systems. NASA has an engineering enterprise and a life-cycle management framework that endure, adapt, and respond. A strategy bridge based on the Baldrige Criteria for Performance Excellence Framework and lessons learned from a recent MBSE initiative illuminates a way forward from today to this desired future. The bridge lays out a strategy for leaders and recommends investments of today for immediate benefits and for benefits in 2029.

model-based systems engineering, digital engineeri↗

DOE OSTI2017

Parallel Multi-cycle LES of an Optical Pent-roof DISI Engine Under Motored Operating Conditions

The use of Large-eddy Simulations (LES) has increased due to their ability to resolve the turbulent fluctuations of engine flows and capture the resulting cycle-to-cycle variability. One drawback of LES, however, is the requirement to run multiple engine cycles to obtain the necessary cycle statistics for full validation. The standard method to obtain the cycles by running a single simulation through many engine cycles sequentially can take a long time to complete. Recently, a new strategy has been proposed by our research group to reduce the amount of time necessary to simulate the many engine cycles by running individual engine cycle simulations in parallel. With modern large computing systems this has the potential to reduce the amount of time necessary for a full set of simulated engine cycles to finish by up to an order of magnitude. In this paper, the Parallel Perturbation Methodology (PPM) is used to simulate up to 35 engine cycles of an optically accessible, pent-roof Directinjection Spark-ignition (DISI) engine at two different motored engine operating conditions, one throttled and one un-throttled. Comparisons are made against corresponding sequential-cycle simulations to verify the similarity of results using either methodology. Mean results from the PPM approach are very similar to sequential-cycle results with less than 0.5% difference in pressure and a magnitude structure index (MSI) of 0.95. Differences in cycle-to-cycle variability (CCV) predictions are larger, but close to the statistical uncertainty in the measurement for the number of cycles simulated. PPM LES results were also compared against experimental data. Mean quantities such as pressure or mean velocities were typically matched to within 5- 10%. Pressure CCVs were under-predicted, mostly due to the lack of any perturbations in the pressure boundary conditions between cycles. Velocity CCVs for the simulations had the same average magnitude as experiments, but the experimental data showed greater spatial variation in the root-mean-square (RMS). Conversely, circular standard deviation results showed greater repeatability of the flow directionality and swirl vortex positioning than the simulations.

I.C. Engines↗

DOE OSTI2014

Replication of engine block cylinder bridge microstructure and mechanical properties with lab scale 319 Al alloy billet castings

In recent years, aluminum alloy gasoline engine blocks have in large part successfully replaced nodular cast iron engine blocks, resulting in improved vehicle fuel efficiency. However, because of the inadequate wear resistance properties of hypoeutectic Al–Si alloys, gray iron cylinder liners are required. These liners cause the development of large tensile residual stress along the cylinder bores and necessitate the maximization of mechanical properties in this region to prevent premature engine failure. The aim of this study was to replicate the engine cylinder bridge microstructure and mechanical properties following TSR treatment (which removes the sand binder to enable easy casting retrieval) using lab scale billet castings of the same alloy composition with varying cooling rates. Comparisons in microstructure between the engine block and the billet castings were carried out using optical and scanning electron microscopy, while mechanical properties were assessed using tensile testing. The results suggest that the microstructure at the top and middle of the engine block cylinder bridge was successfully replicated by the billet castings. However, the microstructure at the bottom of the cylinder was not completely replicated due to variations in secondary phase morphology and distribution. The successful replication of engine block microstructure will enable the future optimization of heat treatment parameters. - Highlights: • A method to replicate engine block microstructure was developed. • Billet castings will allow cost effective optimization of heat treatment process. • The replication of microstructure in the cylinder region was mostly successful. • Porosity was more clustered in the billet castings compared to the engine block. • Mechanical properties were lower in billet castings due to porosity and inclusions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor’s sensitivity (EC 50 ) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC 50 . Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

30-kW Maintenance-Free Stirling Engine for High-Performance Dish Concentrating Solar

This final report summarizes the final results of the 30-kW Maintenance-Free Stirling Engine for High-Performance Dish Concentrating Solar project performed by Infinia Corporation for the U.S. Department of Energy under contract DE-FC36-08GO18032 during the project period of March 1, 2008 – March 31, 2012. Over the course of the project, Infinia Corporation achieved substantial progress in the design, fabrication, assembly, testing and evaluation of a 30-kW multi-cylinder, free-piston Stirling engine (MCFPSE) prototype. In this effort, prior MCFPSE conceptual design approaches were adapted for the development of a 30-kW design, thereby producing a cohesive design package and detailed performance specifications. Numerical analysis using the Stirling Engine Analysis and Optimization Code (SAGE) was completed culminating in the selection of a fully balanced 6-cylinder configuration composed of two 3-cylinder engine modules. The model was refined throughout the program to include all wall conduction losses, piston and rod seal losses, appendix, shuttle and pumping losses, and piston radiation loss to closely represent the real system. Performance mapping of the engine was then completed using the detailed model. Based on knowledge and experience from its existing commercial products, and using the results from the extensive numerical modeling discussed above, Infinia successfully fabricated, assembled and tested two sets of 30-kW engine modules. One of these configurations was driven by an external power supply and operated as a cooler in order to verify the mechanical integrity of the system. In the engine configuration, induction heaters provided the energy to the heater head to operate the engine. Considerable effort was expended on correcting problems associated with contact and rubbing of internal components, identification and subsequent elimination of internal leaks, and undesirable amounts of piston bias. Many details concerning the fabrication and testing efforts are considered proprietary. As a result, those findings are not disclosed herein but rather can be found in proprietary reports supplied to the DOE on a periodic basis. The prototype did not fully demonstrate performance nor did it realize the projected cost targets. Furthermore, the basis of the mechanical and electrical architecture of the 30-kW multi-cylinder prototype design is now at least two generations old. Alternatively, Infinia’s 8-kW Bonneville generator, which was successfully demonstrated in April 2012, and is slated to enter commercial production in late 2013, offers immediate benefits of lower cost and significantly higher power density such that the generator will likely meet DOE’s Sunshot LCOE target goal of $\$$0.07-0.10/kWh by 2015 and $\$$0.05-0.07/kWh by 2020. Therefore, the design of a 30-kW Stirling engine as disclosed in the project will not be pursued further. However, Infinia remains keenly interested in developing higher power Stirling machines in the future based on the new Bonneville mechanical design.

14 SOLAR ENERGY↗

DOE OSTI2016

Systematic Literature Review: How is Model-Based Systems Engineering Justified?

The genesis for this systematic literature review was to search for industry case studies that could inform a decision of whether or not to support the change process, investment, training, and tools needed to implement an MBSE approach across the engineering enterprise. The question asked was, how the change from a document - based systems engineering approach (DBSE) to a model-based systems engineering approach (MBSE) is justified? The methodology employed for this systematic literature review was to conduct a document search of electronically published case studies by authors from the defense, space, and complex systems product engineering industries. The 67 case studies without metrics mainly attributed success to completeness, consistency, and communication of requirements. The 21 case studies with metrics on cost and schedule primarily attributed success to the ability of an MBSE approach to improve defect prevention strategies. The primary conclusion is that there is a significant advantage to project performance by applying an MBSE approach. An MBSE approach made the engineering processes on a complex system development effort more efficient by improving requirements completeness, consistency, and communication. These were seen in engineering processes involved in requirements management, concept exploration, design reuse, test and qualification, Verification and Validation, and margins analyses. An MBSE approach was most effective at improving defect prevention strategies. The approach was found to enhance the capability to find defects early in the system development life cycle (SDLC), when they could be fixed with less impact and prevented rework in later phases, thus mitigating risks to cost, schedule, and mission. However, if a program only employed an MBSE approach for requirements management, advantages from finding defects early could not be leveraged in later phases, where the savings in cost and schedule from rework prevention is realized. Significant performance success was achieved when the systems engineer (SE) held a leadership role over engineering process es. A number of the case studies addressed a general lack of skilled MBSE engineers as a major hindrance to implementing an MBSE approach successfully.

42 ENGINEERING↗

DOE OSTI2021

Ducted Fuel Injection and Cooled Spray Technologies for Particulate Control in Heavy-Duty Diesel Engines

Heavy-Duty diesel engine manufacturers are continuously in pursuit of simple and low-cost technologies that can reduce emissions. Ducted fuel injection (DFI) and Cooled Spray (CS) technologies are two technologies that continue to show promise for significant particulate emissions reductions. These technologies represent a breakthrough in diesel engine combustion from the potential of nearly sootless diesel combustion. This can provide a significant decrease in harmful PM emissions and may enable further system optimization for reduced NOx emissions and increased efficiency. Combustion vessel experiments and engine demonstrations at Sandia, together with the large bore engine tests performed by Wabtec show that this technology may be applicable to heavy duty diesel engines across a wide range of engine sizes and speeds representing the majority of off-road diesel engines. However, very little is known about the ideal geometry, scaling properties or effectiveness of these technologies over the engine operating map. This project will address those uncertainties through a series of experiments performed in an optical and a metal single-cylinder engine.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗