Results for “Engineering - Particle accelerators” — Page 24

DOE OSTI2020

Reinforcement learning for bluff body active flow control in experiments and simulations

Significance Reinforcement learning (RL) has been applied effectively in games and robotic manipulation. We demonstrate the effectiveness of RL in experimental fluid mechanics by applying it to reduce the drag of circular cylinders in turbulent flow, a canonical fluid–structure interaction problem. Although physics agnostic, RL managed to reduce the drag by 30 % or reach another specified optimum point very quickly. Following this discovery, we used high-fidelity simulations to probe the underlying physical mechanisms so that the discovered control techniques can be generalized to other similar flow problems. More broadly, RL-guided active control can lead to efficient exploration of additional flow-control strategies in experimental fluid mechanics, potentially paving the way for accelerating scientific discovery and different designs in flow-related engineering problems.

42 ENGINEERING↗

NASA NTRS1984

Airstart performance of a digital electronic engine control system on an F100 engine

The digital electronic engine control (DEEC) system installed on an F100 engine in an F-15 aircraft was tested. The DEEC system incorporates a closed-loop air start feature in which the fuel flow is modulated to achieve the desired rate of compressor acceleration. With this logic the DEEC equipped F100 engine can achieve air starts over a larger envelope. The DEEC air start logic, the test program conducted on the F-15, and its results are described.

Burcham, F. W., Jr.↗

DOE OSTI2024

Catalyzing the future: recent advances in chemical synthesis using enzymes

Biocatalysis has the potential to address the need for more sustainable organic synthesis routes. Pro-tein engineering can tune enzymes to perform in cascade reactions and for efficient synthesis of en-antiomerically enriched compounds, using both natural and new-to-nature reaction pathways. This review highlights recent achievements in biocatal-ysis, especially the development of novel enzymatic syntheses to access versatile small molecule inter-mediates and complex biomolecules. Biocatalytic strategies for the degradation of persistent pollu-tants and approaches for biomass valorization are also discussed. Here, the transition of chemical synthesis to a greener future will be accelerated by imple-menting enzymes and engineering them for high performance and new activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗

NASA NTRSDate not supplied

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗

NASA NTRS2024

Transient Optimization of an Electrified Gas Turbine Engine Using Machine Learning

Gas turbine engines are designed with sufficient margin to prevent stall under normal operating conditions throughout their life. This compromise ensures that during rapid accelerations, compressor operation remains stable, but at the cost of efficiency and thrust responsiveness. The design margin encompasses multiple sources of uncertainty and systematic deviances from the operating line, the largest of which is the transient allowance. This set-aside accounts for the temporary incoordination of the engine spools during an acceleration while still enabling it to meet the certification requirement to accelerate from low to high power within a specified time, and without experiencing overtemperature, surge, stall, or other detrimental factors. Electrification of the powertrain provides the opportunity to address this reserve and truly optimize the design. The addition of electric machines inherent in hybrid propulsion concepts offers a means to interact with the engine shafts such that the necessary margin can be reduced, which can positively impact the engine design. By adjusting the amount of power extracted from or injected to the engine spools by the electric machines during transient operation, excursions from the operating line can be minimized. Past work using a dynamic engine model has shown that optimization of the fuel flow schedule during acceleration can reduce the required margin while still meeting the time requirement, and results are further improved when combined with power injection and extraction. The current work uses machine learning through a genetic algorithm to address the problem holistically by concurrently optimizing the electric machine power command and fuel flow acceleration schedule using an updated, higher fidelity version of the original engine model.

Stall Margin↗

NASA NTRS2004

Going Up

The accelerated Leadership Option (ALO) combines business management and systems engineering studies at the Massachusetts Institute of Technology (MIT) culminating in a Master of Science degree, with a one year developmental assignment. The program accelerates the development process of exceptionally promising project leaders to positions of increased responsibility. Participants are selected because of technical expertise and proven leadership abilities.

Douglas, Freddie, III↗

NASA NTRSDate not supplied

Evaluation of Composite Airframe Dynamic Impact Modeling Using Hawker 4000 Fuselage Drop Test Data

Two drop tests of partial Hawker 4000 fuselage sections were conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) to characterize the response of representative composite aerospace structure to dynamic impact loads. Test conditions were selected to induce damage into the composite structure in order to study material failure within a composite fuselage and evaluate the capability of finite element (FE) model analysis to predict that failure. The tests were simulated using FE models which were generated to isolate the effect of developmental data availability on predictive capability. FE Models of the tested fuselage sections were generated using two limited data sets. The first model configuration was reverse engineered from the test article with no information related to design or fabrication details which would be known only by the manufacturer. The second model was generated from data provided by the manufacturer but without additional material characterization test data. Models were developed using these methodologies for both fuselage sections tested. Correlation of each model to the tests conducted was evaluated in terms of damage, deformation, and cabin acceleration measurements. Correlation between the developed models and the tested fuselage sections showed that the reverse engineered model predicted the composite damage and cabin acceleration measured during test though it was limited due to lack of detail in the composite layup changes through the structure. The model developed using manufacturer specifications did not predict damage, due to limited material and component model characterization data, but it did predict acceleration on par with the reverse engineered model. Model capability and limitation sources identified were verified through correlation of a final model which was developed by combining the individual data sets. The combined model demonstrated that the addition of calibrated composite material models to accurate composite layup definitions and detailed geometry led to improved correlation of damage and acceleration response within the composite fuselage structures.

Crashworthiness↗

NASA NTRSDate not supplied

Evaluation of Composite Airframe Dynamic Impact Modeling Using Hawker 4000 Fuselage Drop Test Data

Two drop tests of partial Hawker 4000 fuselage sections were conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) to characterize the response of representative composite aerospace structure to dynamic impact loads. Test conditions were selected to induce damage into the composite structure in order to study material failure within a composite fuselage and evaluate the capability of finite element (FE) model analysis to predict that failure. The tests were simulated using FE models which were generated to isolate the effect of developmental data availability on predictive capability. FE Models of the tested fuselage sections were generated using two limited data sets. The first model configuration was reverse engineered from the test article with no information related to design or fabrication details which would be known only by the manufacturer. The second model was generated from data provided by the manufacturer but without additional material characterization test data. Models were developed using these methodologies for both fuselage sections tested. Correlation of each model to the tests conducted was evaluated in terms of damage, deformation, and cabin acceleration measurements. Correlation between the developed models and the tested fuselage sections showed that the reverse engineered model predicted the composite damage and cabin acceleration measured during test though it was limited due to lack of detail in the composite layup changes through the structure. The model developed using manufacturer specifications did not predict damage, due to limited material and component model characterization data, but it did predict acceleration on par with the reverse engineered model. Model capability and limitation sources identified were verified through correlation of a final model which was developed by combining the individual data sets. The combined model demonstrated that the addition of calibrated composite material models to accurate composite layup definitions and detailed geometry led to improved correlation of damage and acceleration response within the composite fuselage structures.

Crashworthiness↗

NASA NTRS2007

High-Heat-Flux Cyclic Durability of Thermal and Environmental Barrier Coatings

Advanced ceramic thermal and environmental barrier coatings will play an increasingly important role in future gas turbine engines because of their ability to protect the engine components and further raise engine temperatures. For the supersonic vehicles currently envisioned in the NASA fundamental aeronautics program, advanced gas turbine engines will be used to provide high power density thrust during the extended supersonic flight of the aircraft, while meeting stringent low emission requirements. Advanced ceramic coating systems are critical to the performance, life and durability of the hot-section components of the engine systems. In this work, the laser and burner rig based high-heat-flux testing approaches were developed to investigate the coating cyclic response and failure mechanisms under simulated supersonic long-duration cruise mission. The accelerated coating cracking and delamination mechanism under the engine high-heat-flux, and extended supersonic cruise time conditions will be addressed. A coating life prediction framework may be realized by examining the crack initiation and propagation in conjunction with environmental degradation under high-heat-flux test conditions.

Zhu, Dongming↗

DOE OSTI2026

Hybridization of Excited Interlayer Excitons with Intralayer Excitons in Transition-Metal Dichalcogenide Heterostructures: Interplay of Orbital and Structural Symmetry

Hybridization between interlayer exciton (ILX) and intralayer excitons offers a powerful route to engineer light–matter interactions in transition-metal dichalcogenide (TMDC) heterostructures, yet the underlying mechanism and selection rules remain elusive. Here we probe exciton hybridization in MoTe2/MoSe2 heterobilayers under a tunable out-of-plane electric field and observe distinct avoided crossings in the electric-field dependent reflection spectra. We associate them with coupling between excited ILX states, including the 2p and 2s Rydberg states, and MoTe2 intralayer exciton. Supported by ab initio GW plus Bethe-Salpeter equation (GW-BSE) calculations, we identify the hybridizing states and establish optical selection rules based on the effective angular momentum of the exciton states. These findings highlight the role of excitonic binding in the observed hybridization, rather than that of simple band-mixing models, and provide a new pathway for brightening high-energy dark states.

Yao, Helen [Department of Materials Science and En↗

DOE OSTI2025

LCLS RF Station Phase Anomaly Candidate Dataset

A public anomaly detection dataset constructed from RF station faults for phase at SLAC's LCLS (Linac Coherent Light Source). We have compiled a dataset of the RF station diagnostic phase data and the beam-position monitor (BPM) signals, alongside the hand labels, for a labeled study period. The dataset consists of two HDF5 files (one for train and one for test) containing the raw data, two CSV files containing information about the candidates. The CSV file for the test dataset also contains the label.

Liang, Jia [Stanford Univ., CA (United States). In↗

NASA NTRS2017

Thermochemistry of CaO-MgO-Al2O3-SiO2 (CMAS) and Advanced Thermal and Environmental Barrier Coating Systems

CaO-MgO-Al2O3-SiO2 (CMAS) oxides are constituents in a broad number of materials and minerals which have recently inferred to discussions in materials science, planetary science, geochemistry and cosmochemistry communities. In materials science, there is increasing interest in the degradation studies of thermal (TBC) and environmental (EBC) barrier coatings of gas turbines by molten CMAS. CMAS minerals usually are carried by the intake air into gas turbines, e.g. in aircraft engines, and their deposits react at high temperatures (1000C) with the coating materials. This causes degradation and accelerated failure of the static and rotating components of the turbine engines. We discuss some preliminary results of the reactions between CMAS and Rare-Earth (RE Y, Yb, Dy, Gd, Nd and Sm) oxide stabilized ZrO2 or HfO2 systems, and the stability of the resulting oxides and silicates. Plasma sprayed hollow tube samples ( 2.2 mm and 26 mm height) were half filled with CMAS powder, wrapped and sealed with platinum foil, and heat treated at 1310 C for 5h. Samples were characterized by differential scanning calorimetry, X-ray diffraction and cross section electron microscopy analysis.

degradation↗

NASA NTRS1992

Electric propulsion system technology

The work performed in fiscal year (FY) 1991 under the Propulsion Technology Program RTOP (Research and Technology Objectives and Plans) No. (55) 506-42-31 for Low-Thrust Primary and Auxiliary Propulsion technology development is described. The objectives of this work fall under two broad categories. The first of these deals with the development of ion engines for primary propulsion in support of solar system exploration. The second with the advancement of steady-state magnetoplasmadynamic (MPD) thruster technology at 100 kW to multimegawatt input power levels. The major technology issues for ion propulsion are demonstration of adequate engine life at the 5 to 10 kW power level and scaling ion engines to power levels of tens to hundreds of kilowatts. Tests of a new technique in which the decelerator grid of a three-grid ion accelerator system is biased negative of neutralizer common potential in order to collect facility induced charge-exchange ions are described. These tests indicate that this SAND (Screen, Accelerator, Negative Decelerator) configuration may enable long duration ion engine endurance tests to be performed at vacuum chamber pressures an order of magnitude higher than previously possible. The corresponding reduction in pumping speed requirements enables endurance tests of 10 kW class ion engines to be performed within the resources of existing technology programs. The results of a successful 5,000-hr endurance of a xenon hollow cathode operating at an emission current of 25 A are described, as well as the initial tests of hollow cathodes operating on a mixture of argon and 3 percent nitrogen. Work performed on the development of carbon/carbon grids, a multi-orifice hollow cathode, and discharge chamber erosion reduction through the addition of nitrogen are also described. Critical applied-field MPD thruster technical issues remain to be resolved, including demonstration of reliable steady-state operation at input powers of hundreds to thousands of kilowatts, achievement of thruster efficiency and specific impulse levels required for missions of interest, and demonstration of adequate engine life at these input power, efficiency, and specific impulse levels. To address these issues we have designed, built, and tested a 100 kW class, radiation-cooled applied-field MPD thruster and a unique dual-beam thrust stand that enables separate measurements of the applied- and self-field thrust components. We have also initiated the development of cathode thermal and plasma sheath models that will eventually be used to guide the experimental program. In conjunction with the cathode modeling, a new cathode test facility is being constructed. This facility will support the study of cathode thermal behavior and erosion mechanisms, the diagnosis of the near-cathode plasma and the development and endurance testing of new, high-current cathode designs. To facilitate understanding of electrode surface phenomenon, we have implemented a telephoto technique to obtain photographs of the electrodes during engine operation. In order to reduce the background vacuum tank pressure during steady-state engine operation in order to obtain high fidelity anode thermal data, we have developed and are evaluating a gas-dynamic diffuser. A review of experience with alkali metal propellants for MPD thrusters led to the conclusion that alkali metals, particularly lithium, offer the potential for significant engine performance and lifetime improvements. These propellants are also condensible at room temperature, substantially reducing test facility pumping requirements. The most significant systems-level issue is the potential for spacecraft contamination. Subsequent experimental and theoretical efforts should be directed toward verifying the performance and lifetime gains and characterizing the thruster flow field to assess its impact on spacecraft surfaces. Consequently, we have begun the design and development of a new facility to study engine operation with alkali metal propellants.

Brophy, John R.↗

NASA NTRSDate not supplied

Building Sustainable Capacity within Under-Represented Communities Through A Deep Partnership Model

Despite varied programmatic inducements and the documented benefits of Diversity Equity & Inclusion (DE&I), participation rates of underrepresented communities within NASA’s planetary sciences activities have remained low and nearly unchanged over the last decade. The lack of success of various efforts may be attributable to factors identified in social science research. First, the proportionality of under-represented groups has been shown to be critical to achieving the positive impacts of DE&I. When under-represented groups make up less than ~30%, group dynamics such as assimilation or tokenism routinely appear, with destructive and counter-productive results. Additionally, if participation only occurs within limited segments of an organization, benefits may be limited. Proportionality must extend across all levels or layers of the organization for the benefits of DE&I to accrue. Second, the inclusion of “Third Spaces” in the planning and support of DE&I efforts is critical to the long-term success or “stickiness” of DE&I activities. Third Spaces are those beyond home (First Space) and work (Second Space) where informal, community-building activities occur. Examples include conferences, after-work activities, and weekend social engagements. Without explicitly acknowledging and including “Third Space” interactions, DE&I efforts can fall short of their long-term goals. In 2014, the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder began a partnership with the United Arab Emirates to develop and fly a space mission to Mars. The scientific mission had an explicit goal of training scientists and engineers, and creating a sustainable ecosystem that would spark and accelerate the UAE’s space economy. To accomplish this, LASP and the UAE set up a program that matched scientists and engineers in one-on-one mentorship relationships, at all levels of the organization. Over the course of the roughly 4-year project, those partnering relationships fostered not only strong professional relationships and knowledge transfer, but also personal friendships that extended into “Third Spaces.” The UAE/LASP partnership now continues through the co-development of an asteroid mission currently in definition phase. In collaboration with NASA Ames Research Center, LASP is developing the conceptual frame work to extend this deep partnership model to domestic opportunities. By implementing a planetary science mission that employs an analogous one-on-one partnership model across all elements of the organization, this project will demonstrate how proportionality and Third Space relationships can enable the development of localized, sustainable communities that are explicitly and deeply engaged with the NASA ecosystem.

Capacity Building↗

NASA NTRSDate not supplied

The Emphasis of Design Patterns in Expressing Expert Knowledge From A Technical Solution – A Framework for Continued Research

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting expert knowledge from proven systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. Motivated by performance gains observed during a multi-year, sequential development activity, this survey reviews knowledge, architecture, and pattern literature to establish a framework for research of architectural methods for expert knowledge identification and description using Model Based System Engineering. The multi-year sequential development activity is offered as the experimental system of interest for this research. This work aims to enable a digital engineering strategy that improves concept phase decision making, accelerates knowledge acquisition from lessons learned repositories, and eases the burden of generational knowledge loss.

Lithium Ion↗

NASA NTRS1992

Ion engine endurance testing at high background pressures

Ion engine endurance testing at vacuum chamber pressures in the low 10 exp -3 Pa range is enabled through the use of a three-grid accelerator system with the decelerator grid biased 50 to 100 volts negative of neutralizer cathode potential. The negative decelerator grid serves to collect the facility induced charge exchange ion current which normally results in rapid erosion of the accelerator grid during testing at elevated vacuum chamber pressures. This screen, accelerator, negative decelerator (SAND) grid configuration enables an order of magnitude reduction in vacuum chamber pumping speeds relative to that required for endurance testing of ion engines with conventional two-grid accelerator systems. A 900-hr test of a 30-cm diameter engine at 6.5 kW and a tank pressure of 3.7 x 10 exp -3 Pa was performed to test the feasibility of the three-grid SAND accelerator system technology. Grid erosion rates from this test are compared to those from a 200-hr test performed with the same discharge chamber, in the same test facility, and at the same background pressure with a conventional two grid accelerator system. The SAND optics resulted in greater than a factor of 100 reduction in accelerator grid erosion rate relative to the two-grid system.

Brophy, John R.↗

NASA NTRS2018

C++ Resource Intelligent Compilation for GPU Enabled Applications

We are nearing the limits of Moore's Law with current computing technology. As industries push for more performance from smaller systems, alternate methods of computation such as Graphics Processing Units (GPUs) should be considered. Many of these systems utilize the Compute Unified Device Architecture (CUDA) to give programmers access to individual compute elements of the GPU for general purpose computing tasks. Direct access to the GPU's parallel multi-core architecture enables highly efficient computation and can drastically reduce the time required for complex algorithms or data analysis. Of course not all systems have a CUDA-enabled device to leverage, and so applications must consider optional support for users with these devices. Resource Intelligent Compilation (RIC) addresses this situation by enabling GPU-based acceleration of existing applications without affecting users without GPUs. Resource Intelligent Compilation (RIC) creates C/C++ modules that can be compiled to create a standard CPU version or GPU accelerated version of a program, depending on hardware availability. This is accomplished through a toolbox of programming strategies based on features of the CUDA API. Using this toolbox, existing applications can be modified with ease to support GPU acceleration, and new applications can be generated with just a few simple modifications. All of this culminates in an accelerated application for users with the appropriate hardware, with no performance impact to standard systems. This memorandum presents all the important features involved in supporting and implementing RIC and an example of using RIC to accelerate an existing mathematical model, without removing support for standard users. Through this memorandum, NASA engineers can acquire a set of guidelines to follow for RIC-compliant development, seamlessly accelerating C/C++ applications.

GPU↗