Development of Laser Powder Directed Energy Deposited NASA HR-1 to Optimize Properties for Liquid Rocket Engine Applications
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Results for “engine optimization”
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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Systems and methods for quality of service (QoS) based management of bottlenecks and flows in networks
Techniques based on the Theory of Bottleneck Ordering can reveal the bottleneck structure of a network, and the Theory of Flow ordering can take advantage of the revealed bottleneck structure to manage and configure network flows so as to improve the overall network performance. These two techniques provide insights into the inherent topological properties of a network at least in three areas: (1) identification of the regions of influence of each bottleneck; (2) the order in which bottlenecks (and flows traversing them) may converge to their steady state transmission rates in distributed congestion control algorithms; and (3) the design of optimized traffic engineering policies.
97 MATHEMATICS AND COMPUTING↗
Optimizing the tuning range of the Fermilab Recycler 53MHz RF cavities by exploiting the avoided crossing of the tuner and cavity modes
The electromagnetic eigenmodes of the Fermilab Recycler RF cavities were simulated with ACE3P running on NERSC's 'Perlmutter' supercomputer in an attempt to optimize their tuning range to comfortably support slip-stacking. A theory, based on coupled circuits and avoided crossings, was developed to explain the origins of the tuning range for tuner-cavity waveguide systems. This provided a logical, rigorous method to carry out this optimization, although engineering problems due to high voltages in the tuner and the operational $\mu$ range of the garnet had to be carefully implemented. It was shown that the desired goal of 10kHz of tuning was not attainable with the current cavity specifications. The maximum tuning range obtained was 5.59kHz for a single tuner with a coaxial line of length 63in. A double tuner cavity was also studied using the simulation software, although with little improvement in the tuning range. A promising technique to improve the tuning range involving the desynchronization of the garnets' magnetic permeabilities is proposed.
43 PARTICLE ACCELERATORS↗
Sensor System and Observer Algorithm Co-Design For Modern Internal Combustion Engine Air Management Based on H2 Optimization
This paper outlines a novel sensor selection and observer design algorithm for linear time-invariant systems with both process and measurement noise based on H 2 optimization to optimize the tradeoff between the observer error and the number of required sensors. The optimization problem is relaxed to a sequence of convex optimization problems that minimize the cost function consisting of the H 2 norm of the observer error and the weighted l 1 norm of the observer gain. An LMI formulation allows for efficient solution via semi-definite programing. The approach is applied here, for the first time, to a turbo-charged spark-ignited engine using exhaust gas circulation to determine the optimal sensor sets for real-time intake manifold burnt gas mass fraction estimation. Simulation with the candidate estimator embedded in a high fidelity engine GT-Power model demonstrates that the optimal sensor sets selected using this algorithm have the best H 2 estimation performance. Sensor redundancy is also analyzed based on the algorithm results. This algorithm is applicable for any type of modern internal combustion engines to reduce system design time and experimental efforts typically required for selecting optimal sensor sets.
Zhang, Xu↗
Cascade Optimization Strategy Maximizes Thrust for High-Speed Civil Transport Propulsion System Concept
The design of a High-Speed Civil Transport (HSCT) air-breathing propulsion system for multimission, variable-cycle operations was successfully optimized through a soft coupling of the engine performance analyzer NASA Engine Performance Program (NEPP) to a multidisciplinary optimization tool COMETBOARDS that was developed at the NASA Lewis Research Center. The design optimization of this engine was cast as a nonlinear optimization problem, with engine thrust as the merit function and the bypass ratios, r-values of fans, fuel flow, and other factors as important active design variables. Constraints were specified on factors including the maximum speed of the compressors, the positive surge margins for the compressors with specified safety factors, the discharge temperature, the pressure ratios, and the mixer extreme Mach number. Solving the problem by using the most reliable optimization algorithm available in COMETBOARDS would provide feasible optimum results only for a portion of the aircraft flight regime because of the large number of mission points (defined by altitudes, Mach numbers, flow rates, and other factors), diverse constraint types, and overall poor conditioning of the design space. Only the cascade optimization strategy of COMETBOARDS, which was devised especially for difficult multidisciplinary applications, could successfully solve a number of engine design problems for their flight regimes. Furthermore, the cascade strategy converged to the same global optimum solution even when it was initiated from different design points. Multiple optimizers in a specified sequence, pseudorandom damping, and reduction of the design space distortion via a global scaling scheme are some of the key features of the cascade strategy. HSCT engine concept, optimized solution for HSCT engine concept. A COMETBOARDS solution for an HSCT engine (Mach-2.4 mixed-flow turbofan) along with its configuration is shown. The optimum thrust is normalized with respect to NEPP results. COMETBOARDS added value in the design optimization of the HSCT engine.
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Dual Engine application of the Performance Seeking Control algorithm
The Dual Engine Performance Seeking Control (PSC) flight/propulsion optimization program has been developed and will be flown during the second quarter of 1993. Previously, only single engine optimization was possible due to the limited capability of the on-board computer. The implementation of Dual Engine PSC has been made possible with the addition of a new state-of-the-art, higher throughput computer. As a result, the single engine PSC performance improvements already flown will be demonstrated on both engines, simultaneously. Dual Engine PSC will make it possible to directly compare aircraft performance with and without the improvements generated by PSC. With the additional thrust achieved with PSC, significant improvements in acceleration times and time to climb will be possible. PSC is also able to reduce deceleration time from supersonic speeds. This paper traces the history of the PSC program, describes the basic components of PSC, discusses the development and implementation of Dual Engine PSC including additions to the code, and presents predictions of the impact of Dual Engine PSC on aircraft performance.
Mueller, F. D.↗
Optimization of wave rotors for use as gas turbine engine topping cycles
Use of a wave rotor as a topping cycle for a gas turbine engine can improve specific power and reduce specific fuel consumption. Maximum improvement requires the wave rotor to be optimized for best performance at the mass flow of the engine. The optimization is a trade-off between losses due to friction and passage opening time, and rotational effects. An experimentally validated, one-dimensional CFD code, which includes these effects, has been used to calculate wave rotor performance, and find the optimum configuration. The technique is described, and results given for wave rotors sized for engines with sea level mass flows of 4, 26, and 400 lb/sec.
Wilson, Jack↗
Structural Analysis and Optimization of a Composite Fan Blade for Future Aircraft Engine
This report addresses the structural analysis and optimization of a composite fan blade sized for a large aircraft engine. An existing baseline solid metallic fan blade was used as a starting point to develop a hybrid honeycomb sandwich construction with a polymer matrix composite face sheet and honeycomb aluminum core replacing the original baseline solid metallic fan model made of titanium. The focus of this work is to design the sandwich composite blade with the optimum number of plies for the face sheet that will withstand the combined pressure and centrifugal loads while the constraints are satisfied and the baseline aerodynamic and geometric parameters are maintained. To satisfy the requirements, a sandwich construction for the blade is proposed with composite face sheets and a weak core made of honeycomb aluminum material. For aerodynamic considerations, the thickness of the core is optimized whereas the overall blade thickness is held fixed so as to not alter the original airfoil geometry. Weight is taken as the objective function to be minimized by varying the core thickness of the blade within specified upper and lower bounds. Constraints are imposed on radial displacement limitations and ply failure strength. From the optimum design, the minimum number of plies, which will not fail, is back-calculated. The ply lay-up of the blade is adjusted from the calculated number of plies and final structural analysis is performed. Analyses were carried out by utilizing the OpenMDAO Framework, developed at NASA Glenn Research Center combining optimization with structural assessment.
Coroneos, Rula M.↗
Implementation of fuel management multi-cycle optimization capabilities in RAVEN optimization framework
Optimization in nuclear fuel-management assists the core reload engineer with finding optimal out-of-core and in-core strategies. RAVEN is INL’s open source software that is equipped with fuel-management optimization capabilities including single-cycle, single- and multi-objective optimization of pressurized water reactors (PWRs) loading patterns (LP) of a fresh core using genetic algorithm (GA) and non-dominated sorting genetic algorithm (NSGA-II). In practice, however, medium and long term planning of fuel-management needs a multi-cycle approach, where the history and availability of fuel assemblies is considered in the optimization process. In this paper, we present a description of an initial expansion of RAVEN fuel-management optimization capabilities for a multi-cycle optimization framework. N-th cycle optimization capabilities that account for the unique history of recycled fuel assembly in the core were added. The multi-cycle optimization approach taken is formulated as a cycle-wise optimization problem where out-of-core decisions are used to onset each cycle optimization. Out-of-core decisions are managed externally to the in-core optimization by a fuel inventory management module. A proof-of-concept optimization problem is also presented.
42 - ENGINEERING↗
AAFE man-made noise experiment project. Volume 2: Project and experiment discussions
An experiment for the acquisition and processing of man-made noise interference data on earth orbital altitudes is discussed. The objectives of the project are to confirm the results of analytical studies concerning radio frequency man-made noise in space. It is stated that the measurements of the amounts and types of noise in frequency bands of interest could allow the allocation and utilization of frequencies to be optimized and would also contribute to the engineering objective of optimizing flight receiving systems. A second objective of the project was to design and fabricate a noise measuring receiver which would demonstrate the feasibility of the experiment design under the project. The procedures for acquiring and processing the electromagnetic radiation data are discussed.
Source record↗
OTIS 3.2 Software Released
Trajectory, mission, and vehicle engineers concern themselves with finding the best way for an object to get from one place to another. These engineers rely upon special software to assist them in this. For a number of years, many engineers have used the OTIS program for this assistance. With OTIS, an engineer can fully optimize trajectories for airplanes, launch vehicles like the space shuttle, interplanetary spacecraft, and orbital transfer vehicles. OTIS provides four modes of operation, with each mode providing successively stronger optimization capability. The most powerful mode uses a mathematical method called implicit integration to solve what engineers and mathematicians call the optimal control problem. OTIS 3.2, which was developed at the NASA Glenn Research Center, is the latest release of this industry workhorse and features new capabilities for parameter optimization and mission design. OTIS stands for Optimal Control by Implicit Simulation, and it is implicit integration that makes OTIS so powerful at solving trajectory optimization problems. Why is this so important? The optimization process not only determines how to get from point A to point B, but it can also determine how to do this with the least amount of propellant, with the lightest starting weight, or in the fastest time possible while avoiding certain obstacles along the way. There are numerous conditions that engineers can use to define optimal, or best. OTIS provides a framework for defining the starting and ending points of the trajectory (point A and point B), the constraints on the trajectory (requirements like "avoid these regions where obstacles occur"), and what is being optimized (e.g., minimize propellant). The implicit integration method can find solutions to very complicated problems when there is not a lot of information available about what the optimal trajectory might be. The method was first developed for solving two-point boundary value problems and was adapted for use in OTIS. Implicit integration usually allows OTIS to find solutions to problems much faster than programs that use explicit integration and parametric methods. Consequently, OTIS is best suited to solving very complicated and highly constrained problems.
Riehl, John P.↗
Hyper-Differential Sensitivity Analysis of Uncertain Parameters in PDE-Constrained Optimization
Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional complexity, namely, uncertain parameters in the PDEs. Uncertainty quantification (UQ) is necessary to characterize, prioritize, and study the influence of these uncertain parameters. Sensitivity analysis, a classical tool in UQ, is frequently used to study the sensitivity of a model to uncertain parameters. In this article, we introduce "hyper-differential sensitivity analysis" which considers the sensitivity of the solution of a PDE-constrained optimization problem to uncertain parameters. Our approach is a goal-oriented analysis which may be viewed as a tool to complement other UQ methods in the service of decision making and robust design. We formally define hyper-differential sensitivity indices and highlight their relationship to the existing optimization and sensitivity analysis literatures. Assuming the presence of low rank structure in the parameter space, computational efficiency is achieved by leveraging a generalized singular value decomposition in conjunction with a randomized solver which converts the computational bottleneck of the algorithm into an embarrassingly parallel loop. Two multi-physics examples, consisting of nonlinear steady state control and transient linear inversion, demonstrate efficient identification of the uncertain parameters which have the greatest influence on the optimal solution.
97 MATHEMATICS AND COMPUTING↗
Optimizing Societal Benefit using a Systems Engineering Approach for Implementation of the GEOSS Space Segment
The Group on Earth Observations (GEO) is driving a paradigm shift in the Earth Observation community, refocusing Earth observing systems on GEO Societal Benefit Areas (SBA). Over the short history of space-based Earth observing systems most decisions have been made based on improving our scientific understanding of the Earth with the implicit assumption that this would serve society well in the long run. The space agencies responsible for developing the satellites used for global Earth observations are typically science driven. The innovation of GEO is the call for investments by space agencies to be driven by global societal needs. This paper presents the preliminary findings of an analysis focused on the observational requirements of the GEO Energy SBA. The analysis was performed by the Committee on Earth Observation Satellites (CEOS) Systems Engineering Office (SEO) which is responsible for facilitating the development of implementation plans that have the maximum potential for success while optimizing the benefit to society. The analysis utilizes a new taxonomy for organizing requirements, assesses the current gaps in spacebased measurements and missions, assesses the impact of the current and planned space-based missions, and presents a set of recommendations.
Killough, Brian D., Jr.↗
Risk-averse optimization for resilience enhancement of complex engineering systems under uncertainties
With the growth of complexity and extent, large scale interconnected network systems, e.g., transportation networks or infrastructure networks, become more vulnerable to external disturbances. Hence, managing potential disruptive events during the design, operating, and recovery phase of an engineered system and therefore improving the system’s resilience is an important yet challenging task. Here, to ensure system resilience after the occurrence of failure events, this study proposes a mixed-integer linear programming (MILP) based restoration framework using heterogeneous dispatchable agents. The scenario-based stochastic optimization (SO) technique is adopted to deal with the inherent uncertainties imposed on the recovery process from nature. Moreover, different from conventional SO using deterministic equivalent formulations, the CVaR risk measure is implemented for this study because of the temporal sparsity of the decision making in applications such as the recovery from extreme events. The resulting restoration framework involves a large-scale MILP problem and thus an adequate decomposition technique i.e. modified Lagrangian dual decomposition, is also employed to achieve tractable computational complexity. Case study results based on the IEEE 37-bus test feeder demonstrate the benefits of using the proposed framework for resilience improvement as well as the advantages of adopting SO formulations.
42 ENGINEERING↗
Reverse and Forward Engineering of Local Voltage Control in Distribution Networks
The increasing penetration of renewable and distributed energy resources in distribution networks calls for real-time and distributed voltage control. As such, in this paper we investigate local Volt/VAR control with a general class of control functions, and show that the power system dynamics with non-incremental local voltage control can be seen as a distributed algorithm for solving a well-defined optimization problem (reverse engineering). The reverse engineering further reveals a fundamental limitation of the non-incremental voltage control: the convergence condition is restrictive and prevents better voltage regulation at equilibrium. This motivates us to design two incremental local voltage control schemes based on the subgradient and pseudo-gradient algorithms respectively for solving the same optimization problem (forward engineering). The new control schemes decouple the dynamical property from the equilibrium property, and have much less restrictive convergence conditions. This work presents another step towards developing a new foundation—network dynamics as optimization algorithms—for distributed real-time control and optimization of future power networks.
42 ENGINEERING↗
The Neutronic Engine: A Platform for Operando Neutron Diffraction in Internal Combustion Engines
Neutron diffraction is a powerful tool for noninvasive and nondestructive characterization of materials and can be applied even in large devices such as internal combustion engines thanks to neutrons’ exceptional ability to penetrate many materials. While proof-of-concept experiments have shown the ability to measure spatially and temporally resolved lattice strains in a small aluminum engine on a timescale of minutes over a limited spatial region, extending this capability to timescales on the order of a crank angle degree over the full volume of the combustion chamber requires careful design and optimization of the engine structure to minimize attenuation of the incident and diffracted neutrons to maximize count rates. Here, we present the design of a “neutronic engine,” which is analogous to an optical engine in that the materials and external geometry of a typical automotive engine have been optimized to maximize access of the diagnostic while maintaining the internal combustion chamber geometry and operability of the engine. The high transparency of aluminum to neutrons makes it the ideal window material for neutron diagnostics, which allows the neutronic engine to be a truly all-metal engine with the same load and boundary condition capabilities of a modern downsized passenger car engine. The neutronic engine will enable 3D and time-resolved measurements of strain, stress, and temperature fields as well as phase transformation, texture, and microstructure throughout the metal components of the combustion chamber.
Wissink, Martin↗
Data for Engineering and Evolution of Yarrowia lipolytica for Producing Lipids from Lignocellulosic Hydrolysates
Yarrowia lipolytica , an oleaginous yeast, shows promise for industrial fermentation due to its robust acetyl-CoA flux and well-developed genetic engineering tools. However, its lack of an active xylose metabolism restricts the conversion of cellulosic sugars to valuable products. To address this, metabolic engineering, and adaptive laboratory evolution (ALE) were applied to the Y. lipolytica PO1f strain, resulting in an efficient xylose-assimilating strain (XEV). Whole-genome sequencing (WGS) of the XEV followed by reverse engineering revealed that the amplification of the heterologous oxidoreductase pathway and a mutation in the GTPase-activating protein gene (YALI0B12100g) might be the primary reasons for improved xylose assimilation in the XEV strain. When a sorghum hydrolysate was used, the XEV strain showed superior xylose consumption and lipid production compared to its parental strain (X123). This study advances our understanding of xylose metabolism in Y. lipolytica and proposes effective metabolic engineering strategies for optimizing lignocellulosic hydrolysates.
Hydrolysate↗
System-Level Optimization to Improve Biofuel Potential via Genetic Engineering and Hydrothermal Liquefaction
The economic success of biofuels and bioproducts depends on system-level optimization including biomass production and conversion. Hydrothermal liquefaction (HTL) can convert wet biomass such as microalgae into a biofuel intermediate (BFI) under elevated temperatures and pressure. An understanding of the impacts of biomass composition on BFI yield and quality can inform genetic engineering strategies in the improvement of biochemical composition for biofuel production. In this work, wild type cyanobacterium Synechocystis sp. PCC 6803 biomass was doped with various common cellular storage compounds in lab-scale HTL experiments. Doping with glycogen or polyhydroxybutyrate (PHB) significantly reduced BFI yields, while doping with triglycerides (TAG) or medium chain-length polyhydroxyalkanoate (mcl-PHA) increased BFI yield and quality. In light of these observations, a genetically engineered Synechocystis strain deficient in glycogen biosynthesis was cultivated to produce biomass for HTL, leading to a 17% increase in BFI yield. In addition, we built a multiphase component additivity (MCA) model that can predict BFI yield and quality with PHAs in the biomass. This work demonstrates an effective strategy to integrate strain development with downstream biomass conversion to maximize biofuel yield, with lessons applicable to microalgae as well as other biomass.
09 BIOMASS FUELS↗