Improved multilevel optimization approach for the design of complex engineering systems
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NASA's Advanced Engineering Environment (AEE) is a research and development program that will improve collaboration among design engineers for launch vehicle conceptual design and provide the infrastructure (methods and framework) necessary to enable that environment. In this paper, three major technical challenges facing the AEE program are identified, and three specific design problems are selected to demonstrate how advanced methods can improve current design activities. References are made to studies that demonstrate these design problems and methods, and these studies will provide the detailed information and check cases to support incorporation of these methods into the AEE. This paper provides background and terminology for discussing the launch vehicle conceptual design problem so that the diverse AEE user community can participate in prioritizing the AEE development effort.
Advancement of U.S. scientific, security, and economic interests through a robust space exploration program requires high performance propulsion systems to support a variety of robotic and crewed missions beyond low Earth orbit. Past studies, in particular those in support of the Space Exploration Initiative (SEI), have shown nuclear thermal propulsion systems provide superior performance for high mass high propulsive delta-V missions. The recent NASA Design Reference Architecture (DRA) 5.0 Study re-examined mission, payload, and transportation system requirements for a human Mars landing mission in the post-2030 timeframe. Nuclear thermal propulsion was again identified as the preferred in-space transportation system. A common nuclear thermal propulsion stage with three 25,000-lbf thrust engines was used for all primary mission maneuvers. Moderately lower thrust engines may also have important roles. In particular, lower thrust engine designs demonstrating the critical technologies that are directly extensible to other thrust levels are attractive from a ground testing perspective. An extensive nuclear thermal rocket technology development effort was conducted from 1955-1973 under the Rover/NERVA Program. Both graphite and refractory metal alloy fuel types were pursued. Reactors and engines employing graphite based fuels were designed, built and ground tested. A number of fast spectrum reactor and engine designs employing refractory metal alloy fuel types were proposed and designed, but none were built. The Small Nuclear Rocket Engine (SNRE) was the last engine design studied by the Los Alamos National Laboratory during the program. At the time, this engine was a state-of-the-art graphite based fuel design incorporating lessons learned from the very successful technology development program. The SNRE was a nominal 16,000-lbf thrust engine originally intended for unmanned applications with relatively short engine operations and the engine and stage design were constrained to fit within the payload volume of the then planned space shuttle. The SNRE core design utilized hexagonal fuel elements and hexagonal structural support elements. The total number of elements can be varied to achieve engine designs of higher or lower thrust levels. Some variation in the ratio of fuel elements to structural elements is also possible. Options for SNRE-based engine designs in the 25,000-lbf thrust range were described in a recent (2010) Joint Propulsion Conference paper. The reported designs met or exceeded the performance characteristics baselined in the DRA 5.0 Study. Lower thrust SNRE-based designs were also described in a recent (2011) Joint Propulsion Conference paper. Recent activities have included parallel evaluation and design efforts on fast spectrum engines employing refractory metal alloy fuels. These efforts include evaluation of both heritage designs from the Argonne National Laboratory (ANL) and General Electric Company GE-710 Programs as well as more recent designs. Results are presented for a number of not-yet optimized fast spectrum engine options.
Seeking a breakthrough in the development of efficient nitrogen fixation catalysts has become the frontier of energy and chemical conversion schemes. In this work, we report that the MXene Ti 3 C 2 can serve as a promising catalyst for the electrochemical N 2 reduction reaction (NRR) under ambient conditions. The electrocatalytic performance of Ti 3 C 2 can be further optimized through surface engineering. Specifically, Ti 3 C 2 with the increased surface hydroxyl moieties demonstrates enhanced production of NH 3 with a yield rate of 1.71 μg h -1 cm -2 , a Faradaic efficiency of 7.01% at -0.2 V vs. RHE at 20 °C and an even higher yield rate of 12.46 μg h -1 cm -2 together with a Faradaic efficiency of 9.03% at -0.2 V vs. RHE at 60 °C. The detailed electrochemical analysis suggests that the surface hydroxyl modification can effectively facilitate the electron transfer, surface adsorption and activation of dinitrogen. Our work sheds light on the development of efficient NRR catalysts based on earth-abundant elements.
Aircraft with flight capability above 1.4 normally have an RPM lockup or similar feature to prevent inlet buzz that would occur at low engine airflows. This RPM lockup has the effect of holding the engine thrust level at the intermediate power (maximum non-afterburning). For aircraft such as military fighters or supersonic transports, the need exists to be able to rapidly slow from supersonic to subsonic speeds. For example, a supersonic transport that experiences a cabin decompression needs to be able to slow/descend rapidly, and this requirement may size the cabin environmental control system. For a fighter, there may be a desire to slow/descend rapidly, and while doing so to minimize fuel usage and engine exhaust temperature. Both of these needs can be aided by achieving the minimum possible overall net propulsive force. As the intermediate power thrust levels of engines increase, it becomes even more difficult to slow rapidly from supersonic speeds. Therefore, a mode of the performance seeking control (PSC) system to minimize overall propulsion system thrust has been developed and tested. The rapid deceleration mode reduces the engine airflow consistent with avoiding inlet buzz. The engine controls are trimmed to minimize the thrust produced by this reduced airflow, and moves the inlet geometry to degrade the inlet performance. As in the case of the other PSC modes, the best overall performance (in this case the least net propulsive force) requires an integrated optimization of inlet, engine, and nozzle variables. This paper presents the predicted and measured results for the supersonic minimum thrust mode, including the overall effects on aircraft deceleration.
Abstract Halocyclization of alkenes is a powerful bond-forming tool in synthetic organic chemistry and a key step in natural product biosynthesis, but catalyzing halocyclization with high enantioselectivity remains a challenging task. Identifying suitable enzymes that catalyze enantioselective halocyclization of simple olefins would therefore have significant synthetic value. Flavin-dependent halogenases (FDHs) catalyze halogenation of arene and enol(ate) substrates. Herein, we reveal that FDHs engineered to catalyze site-selective aromatic halogenation also catalyze non-native bromolactonization of olefins with high enantioselectivity and near-native catalytic proficiency. Highly selective halocyclization is achieved by characterizing and mitigating the release of HOBr from the FDH active site using a combination of reaction optimization and protein engineering. The structural origins of improvements imparted by mutations responsible for the emergence of halocyclase activity are discussed. This expansion of FDH catalytic activity presages the development of a wide range of biocatalytic halogenation reactions.
NASA's Software Engineering Laboratory (SEL), one of the earliest pioneers in the areas of software process improvement and measurement, has had a significant impact on the software business at NASA Goddard. At the heart of the SEL's improvement program is a belief that software products can be improved by optimizing the software engineering process used to develop them and a long-term improvement strategy that facilitates small incremental improvements that accumulate into significant gains. As a result of its efforts, the SEL has incrementally reduced development costs by 60%, decreased error rates by 85%, and reduced cycle time by 25%. In this paper, we analyze the SEL's experiences on three major improvement initiatives to better understand the cyclic nature of the improvement process and to understand why some improvements take much longer than others.
Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58 using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a maximum piston power increase of 14. Analytical predictions are compared to experimental data showing close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.
The FCC-ee, with its unprecedented luminosity goal and high energy reach, creates challenges and requires solutions to many issues in order to produce a realistic design for the complex machine detector interface. The interaction region design for the FCC-ee adopts the crab-waist collision scheme and proposes an elegant local chromaticity correction system. An asymmetric layout of nearby dipoles suppresses the critical energy of synchrotron radiation incoming to the detector at the interaction point to a maximum value of 100 keV. The main challenge of the FCC-ee machine detector interface design is to combine the many conflicting accelerator and 2 T detector constraints, aiming for the optimal trade-off choices that simultaneously allow for a best machine performance in terms of integrated luminosity and data taking efficiency. Much of the success of the FCC-ee will be related to the interaction region design, as a result of the ingredients coming from areas of accelerator physics, mechanical engineering and detector optimization.
Typical LEO networks use constellations which provide a uniform coverage. However, the demand for telecom service is dynamic and unevenly distributed around the world. We examine a more efficient and cost effective design by matching the satellite coverage with the cyclical demand for service around the world. Our approach is to use a non-uniform satellite distribution for the network. We have named this constellation design NUONCE for Non Uniform Optimal Network Communications Engine.
With stringent emission regulations, it has become more important for modern diesel engine manufacturers to accurately predict engine-out nitrogen oxide (NO x ) emissions across a wide range of operating conditions. Thermal NO is the major source of engine-out NO x in modern diesel engines. For thermal NO formation, several earlier studies have recommended the forward and reverse reaction rate coefficients of the rate-limiting reaction (O + N 2 ⇌ NO + N). However, due to deficiencies in sub-models and inadequacies of reduced chemical mechanisms to represent diesel combustion, these recommended values more often than not need to be adjusted in reduced order combustion models to accurately predict engine-out NO x . Hence, in this work a systematic and computationally efficient approach has been proposed to streamline the process of determining the optimum reaction rate coefficients. Here, to develop the optimization approach, four different production diesel engines with different operating conditions in terms of speed, load, and exhaust-gas recirculation have been considered. Numerical simulations have been performed using a detailed zero-dimensional velocity-composition-frequency transported probability density function (0D-VCF-tPDF) model that uses hundreds of notional particles to capture in-cylinder stratification. Four different combinations of hydrocarbon and NO x chemical mechanisms were used to represent chemistry. It was found that for the rate-limiting reaction, the pre-exponent factors (A f1 , A r1 ) and activation energies (E A,f1 , E A,r1 ) of the forward and reverse reaction rates follow a linear band in A f1 - E A,f1 and A r1 - E A,r1 space where predicted engine-out NO x match the measured values closely. By encompassing such bands from different engines and considering constraints on activation energies, a reduced search domain of pre-exponent factors and activation energies was constructed that is expected to be applicable to any diesel engine. Eventually, computationally efficient three-line and one-line search approaches were proposed to determine the optimum values of the pre-exponent factors and activation energies that led to a minimum error between measured and predicted engine-out NO x . Finally, these three-line and one-line NO x optimization approaches were applied to a fifth production diesel engine for which the 0D-VCF-tPDF model showed a very good predictive performance in terms of predicting peak pressure, 50% burn rate, and engine-out NO x when compared to measured and 3D-CFD values.
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.
Ultra High Temperature Metal Matrix Composites (UHT-MMCs) are of interest to the due to their potential defense and aerospace applications. These materials consist of a metal matrix reinforced with a stiff ceramic or cermet. Based on a preliminary literature survey, this project will focused on a pure titanium (Ti) matrix reinforced with tungsten carbide-cobalt (WC-Co). UHT-MMC technology is still at a nascent stage of development and requires extensive experimental work to optimize the structure and resulting material properties of a particular UHT-MMC material system. An accurate and complete high-performance computing (HPC) model of the Ti/WC-Co material system could greatly accelerate the development and deployment Ti/WC-Co materials by connecting processing parameters to material properties. This type of model could then be used in an integrated computational materials engineering approach to optimize the material structure to achieve a targeted level of performance.
Computer structural optimization is applied to the design of Space Shuttle main engine turbopump blades. The optimization is implemented by the program SSME/STAEBL. A general description of this program is given. Design optimization studies for typical blade designs are presented.
Studies to define the optimum turbopump configurations for the Space Shuttle propulsion system are reported. For each propellant, two turbopumps - one low-pressure and one high-pressure - are needed to generate the high discharge pressures required for engine operation. The optimization of the four pumps resulted in the selection of an axial inducer type for both low-pressure pumps and in a three-stage centrifugal pump for the high-pressure hydrogen turbopump; meanwhile the oxygen pump features a double inlet main impeller. This impeller feeds the thrust chamber injector, as well as a preburner pump, which boosts the main impeller discharge pressure to the required preburner pressure. The interaction between engine performance and obtainable turbopump performance is discussed, and the reasons for the final selection of the turbine and pump types are presented.
The more easily available system performance data and advances in data analytics have provided us with opportunities to optimize maintenance programs for engineered systems, for example nuclear power plants. One key task in maintenance optimization is to obtain an accurate model for system degradation. Here, in this research, we propose a Bayesian method to address this problem. Noting that systems usually exhibit multiple states and that the actual state of a system usually is not directly observable, in the method we first model the system degradation process and the observation process based on a hidden Markov model. Then we develop a sequential Bayesian inference algorithm based on importance sampling and the forward algorithm to infer the posterior distributions of the transition rates in the hidden Markov model based on available observations. The proposed Bayesian method allows us to take advantage of evidence from multiple sources, and also allows us to perform Bayesian inference sequentially, without the need to use the entire history of observations every time new observations are collected. We demonstrate the proposed method using both synthetic data for a nuclear power plant feedwater pump and realistic data for a nuclear power plant chemistry analytical device.
An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.
Low thrust chemical (hydrogen-oxygen) propulsion systems configured specifically for low acceleration orbit transfer of large space systems were defined. Results indicate that it is cost effective and least risk to combine the OTV and stowed spacecraft in a single 65 K Shuttle. The study shows that the engine for an optimized low thrust stage (1) does not require very low thrust; (2) 1-3 K thrust range appears optimum; (3) thrust transient is not a concern; (4) throttling probably not worthwhile; and (5) multiple thrusters complicate OTV/LSS design and aggravate LSS loads. Regarding the optimum vehicle for low acceleration missions, the single shuttle launch (LSS and expendable OTV) is most cost effective and least risky. Multiple shuttles increase diameter 20%. The space based radar structure short OTV (which maximizes space available for packaged LSS) favors use of torus tank. Propellant tank pressures/vapor residuals are little affected by engine thrust level or number of burns.