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At least 217 records · Page 12

Predicting Cycle-to-Cycle Variation With Concurrent Cycles in a Gasoline Direct Injected Engine With Large Eddy Simulations

High cycle-to-cycle variation (CCV) is detrimental to engine performance, as it leads to poor combustion and high noise and vibration. In this work, CCV in a gasoline engine is studied using large eddy simulation (LES). The engine chosen as the basis of this work is a single-cylinder gasoline direct injection (GDI) research engine. Two stoichiometric part-load engine operating points (6 BMEP, 2000 RPM) were evaluated: a non-dilute (0% EGR) case and a dilute (18% EGR) case. The experimental data for both operating conditions had 500 cycles. The measured CCV in IMEP was 1.40% for the non-dilute case and 7.78% for the dilute case. To estimate CCV from simulation, perturbed concurrent cycles of engine simulations were compared to consecutively obtained engine cycles. The motivation behind this is that running consecutive cycles to estimate CCV is quite time-consuming. For example, running 100 consecutive cycles requires 2–3 months (on a typical cluster), however, by running concurrently one can potentially run all 100 cycles at the same time and reduce the overall turnaround time for 100 cycles to the time taken for a single cycle (2 days). The goal of this paper is to statistically determine if concurrent cycles, with a perturbation applied to each individual cycle at the start, can be representative of consecutively obtained cycles and accurately estimate CCV. 100 cycles were run for each case to obtain statistically valid results. The concurrent cycles began at different timings before the combustion event, with the motivation to identify the closest time before spark to minimize the run time. Only a single combustion cycle was run for each concurrent case. The calculated standard deviation of peak pressure and coefficient of variance (COV) of indicated mean effective pressure (IMEP) were compared between the consecutive and concurrent methods to quantify CCV. It was found that the concurrent method could be used to predict CCV with either a velocity or numerical perturbation. Here, a large and small velocity perturbation were compared and both produced correct predictions, implying that the type of perturbation is not important to yield a valid realization. Starting the simulation too close to the combustion event, at intake valve close (IVC) or at spark timing, under-predicted the CCV. When concurrent simulations were initiated during or before the intake even, at start of injection (SOI) or earlier, distinct and valid realizations were obtained to accurately predict CCV for both operating points. By simulating CCV with concurrent cycles, the required wall clock time can be reduced from 2–3 months to 1–2 days. Additionally, the required core-hours can be reduced up to 41%, since only a portion of each cycle needs to be simulated.

42 ENGINEERING↗

Electronic Design Automation: Integrating the Design and Manufacturing Functions

As the complexity of electronic systems grows, the traditional design practice, a sequential process, is replaced by concurrent design methodologies. A major advantage of concurrent design is that the feedback from software and manufacturing engineers can be easily incorporated into the design. The implementation of concurrent engineering methodologies is greatly facilitated by employing the latest Electronic Design Automation (EDA) tools. These tools offer integrated simulation of the electrical, mechanical, and manufacturing functions and support virtual prototyping, rapid prototyping, and hardware-software co-design. This report presents recommendations for enhancing the electronic design and manufacturing capabilities and procedures at JSC based on a concurrent design methodology that employs EDA tools.

Bachnak, Rafic↗

Utilization of CAD/CAE for concurrent design of structural aircraft components

The feasibility of installing the Stratospheric Observatory for Infrared Astronomy telescope (named SOFIA) into an aircraft for NASA astronomy studies is investigated using CAD/CAE equipment to either design or supply data for every facet of design engineering. The aircraft selected for the platform was a Boeing 747, chosen on the basis of its ability to meet the flight profiles required for the given mission and payload. CAD models of the fuselage of two of the aircraft models studied (747-200 and 747 SP) were developed, and models for the component parts of the telescope and subsystems were developed by the various concurrent engineering groups of the SOFIA program, to determine the requirements for the cavity opening and for design configuration. It is noted that, by developing a plan to use CAD/CAE for concurrent engineering at the beginning of the study, it was possible to produce results in about two-thirds of the time required using traditional methods.

Kahn, William C.↗

Reengineering Space Projects

In an era of shrinking funds for space exploration, JPL is undergoing a significant reengineering effort designed to reduce costs of flight projects by 33 percent, and time to launch by 50 percent.

devlopment MSD DBAT VIVO↗

Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

JT9D-7A (SP) jet engine performance deterioration trends

The levels, trends, and causes of engine performance deterioration were investigated. A series of installed engine calibrations (both on-the-ground and in-flight) were performed on two new Pan American World Airways 747 SP aircraft. The performance data gathered covered from before the first flight through approximately 1000 flight cycles and 6900 flight hours. To accomplish the calibrations a special instrumentation system for ground testing of installed engines over a broad power range was used along with performing concurrent in-flight engine calibrations under revenue service conditions. Results of the analysis of the data, which provide a better understanding of short and long term performance deterioration of both engines and modules are presented.

Richter, G. P.↗

Field Deployment of a Portable Optical Spectrometer for Methane Fugitive Emissions Monitoring on Oil and Gas Well Pads

We present field deployment results of a portable optical absorption spectrometer for localization and quantification of fugitive methane (CH 4 ) emissions. Our near-infrared sensor targets the 2$ν_3$ R(4) CH 4 transition at 6057.1 cm −1 (1651 nm) via line-scanned tunable diode-laser absorption spectroscopy (TDLAS), with Allan deviation analysis yielding a normalized 2.0 ppmv∙Hz −1/2 sensitivity (4.5 × 10 −6 Hz −1/2 noise-equivalent absorption) over 5 cm open-path length. Controlled CH 4 leak experiments are performed at the METEC CSU engineering facility, where concurrent deployment of our TDLAS and a customized volatile organic compound (VOC) sensor demonstrates good linear correlation (R 2 = 0.74) over high-flow (>60 SCFH) CH 4 releases spanning 4.4 h. In conjunction with simultaneous wind velocity measurements, the leak angle-of-arrival (AOA) is ascertained via correlation of CH 4 concentration and wind angle, demonstrating the efficacy of single-sensor line-of-sight (LOS) determination of leak sources. Finally, source magnitude estimation based on a Gaussian plume model is demonstrated, with good correspondence (R 2 = 0.74) between calculated and measured release rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long term technology development program

In the Advanced Adiabatic Development program, the following technology were identified as critical: piston development for oil-less, adiabatic engine; positive displacement compounding and charge system; experimental evaluation of the preheat concept; combustion system with positive ignition assist; and ceramic manufacturing technology. Of these five areas, ceramic manufacturing technology is the pacing item, and is already being addressed by several organizations. Therefore the four remaining areas need immediate attention. Since the lead time involved in engine development and production is long, this technology development should be done concurrently with the AAD engine development. A four year program is outlined which will simultaneously study these first four areas. This program requires two test rigs; one single cylinder adiabatic engine; and one multicylinder adiabatic turbocompound engine.

Sekar, R.↗

Transputer parallel processing at NASA Lewis Research Center

The transputer parallel processing lab at NASA Lewis Research Center (LeRC) consists of 69 processors (transputers) that can be connected into various networks for use in general purpose concurrent processing applications. The main goal of the lab is to develop concurrent scientific and engineering application programs that will take advantage of the computational speed increases available on a parallel processor over the traditional sequential processor. Current research involves the development of basic programming tools. These tools will help standardize program interfaces to specific hardware by providing a set of common libraries for applications programmers. The thrust of the current effort is in developing a set of tools for graphics rendering/animation. The applications programmer currently has two options for on-screen plotting. One option can be used for static graphics displays and the other can be used for animated motion. The option for static display involves the use of 2-D graphics primitives that can be called from within an application program. These routines perform the standard 2-D geometric graphics operations in real-coordinate space as well as allowing multiple windows on a single screen.

Ellis, Graham K.↗

Adjoint-Based Mesh Adaptation and Shape Optimization for Simulations with Propulsion

We demonstrate a well-posed formulation of permeable boundary conditions and mass- flow-rate functionals for adjoint-based mesh refinement and shape optimization governed by the steady Euler equations. The boundary conditions are used to model propulsion- system effects of inlets and nozzles. A two-shock diffuser with an analytic solution is used to verify the implementation. Numerical examples show that the adjoint solution is smooth at the boundary, indicating that the discretization is adjoint consistent when exit pressure is specified at subsonic outflow, and stagnation temperature and pressure at subsonic inflow. The results focus on improving simulation techniques for low-boom aircraft analysis and design. By including mass-flow-rate outputs, we obtain reliable estimates of engine flow rates concurrently with nearfield pressure signatures without increasing simulation cost. We also demonstrate the importance of mass-flow-rate constraints in shape optimization by examining trade-offs between maximizing performance of a shrouded supersonic nozzle and minimizing shocks in its nearfield.

Nemec, Marian↗

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

33 ADVANCED PROPULSION SYSTEMS↗

Inference-Engine v0.1.0

Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's "do concurrent" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside "do concurrent" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's "dot_product" intrinsic function inside "do concurrent" blocks and another method that instead uses Fortran' "matmul" array intrinsic function. We plan to investigate automatic compiler offloading of "do concurrent" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for "matmul" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.

Rouson, Damian↗

A Machine Learning-Genetic Algorithm (ML-GA) Approach for Rapid Optimization Using High-Performance Computing

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC). The outputs (targets) of interest from these simulations included five metrics related to engine performance and emissions. Over 2000 samples generated from CFD were then used to train an ML model that could predict these five targets based on the nine input features. A robust super learner approach was employed to build the ML model, where results from a collection of different ML algorithms were pooled together. Thereafter, a stochastic global optimization genetic algorithm (GA) was used, with the ML model as the objective function, to optimize the input parameters based on a merit function so as to minimize fuel consumption while satisfying CO and NOx emissions constraints. The optimized configuration from ML-GA was found to be very close to that obtained from a sequentially performed CFD-GA approach, where a CFD simulation served as the objective function. In addition, the overall turnaround time was (at least) 75% lower with the ML-GA approach, as the training data was generated from concurrent CFD simulations and employing the ML model as the objective function significantly accelerated the GA optimization. Finally, this study demonstrates the potential of ML-GA and high-performance computing (HPC) to reduce the number of CFD simulations to be performed for optimization problems without loss in accuracy, thereby providing significant cost savings compared to traditional approaches.

97 MATHEMATICS AND COMPUTING↗

Membrane assisted continuous production of solvents with integrated solvent removal using liquid-liquid extraction

The aim was to demonstrate an industrially relevant pilot scale integrated process to produce butanol and other solvents from lignocellulosic sugars produced with AVAP® biomass fractionation technology from southern pine wood. The concentrated sugars were concurrently fermented using genetically engineered Clostridium acetobutylicum to n-butanol, acetone, isopropanol and ethanol in continuous membrane assisted cell recycle fermentation with steady-state solvent productivity exceeding 10 g/L/h. The solvents from the cell free permeate were recovered with extractant of butyl butyrate in a continuous liquid-liquid extraction column and aqueous product (raffinate) along with unused sugars, nutrients, and metabolic intermediates were recycled back to the fermentors. The total solvent yield approached 0.30 g/g sugars.

09 BIOMASS FUELS↗

Independent Metadata Update VOL Connector for HDF5 (IMM VOL) v0.1

We have built a new framework that enables independent metadata updates within HDF5 files. Our framework includes the following components: an overlay network that's optimized for 1-to-All and All-to-All communication; root-less/server-less Bcast and AllReduce operations for reduced synchronization; a distributed consensus-making platform; an execution order keeping system, and a progress engine for generic threadless concurrence handling.

Li, Tonglin↗

System software for the finite element machine

The Finite Element Machine is an experimental parallel computer developed at Langley Research Center to investigate the application of concurrent processing to structural engineering analysis. This report describes system-level software which has been developed to facilitate use of the machine by applications researchers. The overall software design is outlined, and several important parallel processing issues are discussed in detail, including processor management, communication, synchronization, and input/output. Based on experience using the system, the hardware architecture and software design are critiqued, and areas for further work are suggested.

Crockett, T. W.↗

Computer Sciences and Data Systems, volume 1

Topics addressed include: software engineering; university grants; institutes; concurrent processing; sparse distributed memory; distributed operating systems; intelligent data management processes; expert system for image analysis; fault tolerant software; and architecture research.

Source record↗

Is bigger always better? An economic study of U.S. ETO vehicle architectures

This analysis, performed as part of NASA's Space Transportation Infrastructure Study, compares the cost efficiency of two candidate launch vehicle families, used in conjunction with existing expendable launch vehicles and the Shuttle, to accomplish the nation's future space missions through 2030. Missions analyzed include those identified in NASA's Civil Needs Data Base (CNDB) and Space Exploration Initiative (SEI) Option E program, as well as estimates of commercial and U.S. Department of Defense flights. A family of Shuttle-derived In-line vehicles is compared against a family designed around a vehicle optimized for large (250t) payloads. The analysis is performed within the context of an entire space transportation architecture. The goal is to determine which architecture best captures the required missions most cost-effectively. Results indicate that, for the particular mission model analyzed, neither option is clearly superior across the entire payload range. The Shuttle-derived family displays a better evolutionary path for supporting the total mission model (CNDB plus SEI missions). It also reduces earth-to-orbit (ETO) peak funding by 20 percent. The architecture incorporating the Heavy Lift ETO family minimizes SEI program cost and on-orbit operations but is subject to greater schedule risk because of the need for concurrent ETO core and engine development.

Eimers, Dan R.↗