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ExaGO is a high-performance computing power systems modeling suite providing models for different power flow analyses. It supports forward AC power flow, multiperiod AC and DC optimal power flow analyses, contingency analysis, as well as stochastic optimal power flow analysis. ExaGO can use HiOp and Ipopt optimization engines. It supports Matpower and PSS/E input file formats. ExaGO v2 includes code from ExaGO 1.6.0.
Human activities involving subsurface reservoirs—resource extraction, carbon and nuclear waste storage—alter thermal, mechanical, and chemical steady-state conditions in these systems. Because these systems exist at lithostatic pressures, even minor chemical changes can cause chemically assisted deformation. Therefore, understanding how chemical effects control geomechanical properties is critical to optimizing engineering activities. The grand challenge in predicting the effect of chemical processes on mechanical properties lays in the fact that these phenomena take place at molecular scales, while they manifest all the way to reservoir scales. To address this fundamental challenge, we investigated chemical effects on deformation in model and real systems spanning molecular- to centimeter scales. We used theory, experiment, molecular dynamics simulation, and statistical analysis to (1) identify the effect of simple reactions, such as hydrolysis, on molecular structures in interfacial regions of stressed geomaterials; (2) quantify chemical effects on the bulk mechanical properties, fracture and displacement for granular rocks and single crystals; (3) develop initial understanding of universal scaling for individual displacement events in layered geomaterials; and (4) develop analytic approximations for the single-chain mechanical response utilizing asymptotically correct statistical thermodynamic theory. Taken together, these findings advance the challenging field of chemo-mechanics.
The updated study plan for the Space Transportation System orbit transfer vehicle (OTV) engine study is presented. The study program consists of engine system, programmatic, cost, and risk analyses of OTV engine concepts. Detailed task descriptions for the advanced expander cycle engine optimization, alternate low thrust capability, and safety, reliability, and cost comparisons are given.
Solution techniques for handling large scale engineering optimization problems are reviewed. Potentials for practical applications as well as their limited capabilities are discussed. A new solution algorithm for design sensitivity is proposed. The algorithm is based upon the multilevel substructuring concept to be coupled with the adjoint method of sensitivity analysis. There are no approximations involved in the present algorithm except the usual approximations introduced due to the discretization of the finite element model. Results from the six- and thirty-bar planar truss problems show that the proposed multilevel scheme for sensitivity analysis is more effective (in terms of computer incore memory and the total CPU time) than a conventional (one level) scheme even on small problems. The new algorithm is expected to perform better for larger problems and its applications on the new generation of computer hardwares with 'parallel processing' capability is very promising.
Estimation of the sensitivity of problem functions with respect to problem variables forms the basis for many of our modern day algorithms for engineering optimization. The most common application of problem sensitivities has been in the calculation of objective function and constraint partial derivatives for determining search directions and optimality conditions. A second form of sensitivity analysis, parameter sensitivity, has also become an important topic in recent years. By parameter sensitivity, researchers refer to the estimation of changes in the modeling functions and current design point due to small changes in the fixed parameters of the formulation. Methods for calculating these derivatives have been proposed by several authors (Armacost and Fiacco 1974, Sobieski et al 1981, Schmit and Chang 1984, and Vanderplaats and Yoshida 1985). Two drawbacks to estimating parameter sensitivities by current methods have been: (1) the need for second order information about the Lagrangian at the current point, and (2) the estimates assume no change in the active set of constraints. The first of these two problems is addressed here and a new algorithm is proposed that does not require explicit calculation of second order information.
The mathematical formulation of the engineering optimization problem is given. Evaluation of the objective function and constraint equations can be very expensive in a computational sense. Thus, it is desirable to use as few evaluations as possible in obtaining its solution. In solving the equation, one approach is to develop approximations to the objective function and/or restraint equations and then to solve the equation using the approximations in place of the original functions. These approximations are referred to as response surfaces. The desirability of using response surfaces depends upon the number of functional evaluations required to build the response surfaces compared to the number required in the direct solution of the equation without approximations. The present study is concerned with evaluating the performance of response surfaces so that a decision can be made as to their effectiveness in optimization applications. In particular, this study focuses on how the quality of approximations is effected by design selection. Polynomial approximations and neural net approximations are considered.
The fundamentals of control integration for propulsion are reviewed giving practical illustrations of its use to demonstrate the advantages of integration. Attention is given to the first integration propulsion-control systems (IPCSs) which was developed for the F-111E, and the integrated controller design is described that NASA developed for the YF-12C aircraft. The integrated control systems incorporate a range of aircraft components including the engine, inlet controls, autopilot, autothrottle, airdata, navigation, and/or stability-augmentation systems. Also described are emergency-control systems, onboard engine optimization, and thrust-vectoring control technologies developed for the F-18A and the F-15. Integrated flight-propulsion control systems are shown to enhance the thrust, range, and survivability of the aircraft while reducing fuel consumption and maintenance.
The Conference Proceedings contains 42 papers presented at the Propulsion and Energetics Panel 85th Symposium on Loss Mechanisms and Unsteady Flows in Turbomachines which was held from 8-12 May 1995, in Derby, UK. Sessions: Cascade Steady Flow Mechanisms and Losses (9 papers); Steady Flow Clearance and Injection Flow Mechanisms and Losses (6); Steady Secondary Flows and Shock Boundary Layer Interaction (3); Blade Section-Wake Boundary layer Interaction (6); Management of Unsteady Flows (10); Blade Interactions (8). The Symposium contributes to improving the efficiency and operation of turbomachinery also in off-design conditions by application of experimental and computational fluid dynamics methods. Multi-stage methods and positive loss management in the design stage have been identified as next steps. This will yield optimized engines of high efficiency for expanded flight envelopes including active control of the plane movement at high reliability levels.
Topics covered include: Software Tool Integrating Data Flow Diagrams and Petri Nets; Adaptive Nulling for Interferometric Detection of Planets; Reducing the Volume of NASA Earth-Science Data; Reception of Multiple Telemetry Signals via One Dish Antenna; Space-Qualified Traveling-Wave Tube; Smart Power Supply for Battery-Powered Systems; Parallel Processing of Broad-Band PPM Signals; Inexpensive Implementation of Many Strain Gauges; Constant-Differential-Pressure Two-Fluid Accumulator; Inflatable Tubular Structures Rigidized with Foams; Power Generator with Thermo-Differential Modules; Mechanical Extraction of Power From Ocean Currents and Tides; Nitrous Oxide/Paraffin Hybrid Rocket Engines; Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents; Probabilistic Multi-Factor Interaction Model for Complex Material Behavior; Foldable Instrumented Bits for Ultrasonic/Sonic Penetrators; Compact Rare Earth Emitter Hollow Cathode; High-Precision Shape Control of In-Space Deployable Large Membrane/Thin-Shell Reflectors; Rapid Active Sampling Package; Miniature Lightweight Ion Pump; Cryogenic Transport of High-Pressure-System Recharge Gas; Water-Vapor Raman Lidar System Reaches Higher Altitude; Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes; Wide-Field-of-View, High-Resolution, Stereoscopic Imager; Electrical Capacitance Volume Tomography with High-Contrast Dielectrics; Wavefront Control and Image Restoration with Less Computing; Polarization Imaging Apparatus; Stereoscopic Machine-Vision System Using Projected Circles; Metal Vapor Arcing Risk Assessment Tool; Performance Bounds on Two Concatenated, Interleaved Codes; Parameterizing Coefficients of a POD-Based Dynamical System; Confidence-Based Feature Acquisition; Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery; Universal Decoder for PPM of any Order; Algorithm for Stabilizing a POD-Based Dynamical System; Mission Reliability Estimation for Repairable Robot Teams; Processing AIRS Scientific Data Through Level 3; Web-Based Requesting and Scheduling Use of Facilities; AutoGen Version 5.0; Time-Tag Generation Script; PPM Receiver Implemented in Software; Tropospheric Emission Spectrometer Product File Readers; Reporting Differences Between Spacecraft Sequence Files; Coordinating "Execute" Data for ISS and Space Shuttle; Database for Safety-Oriented Tracking of Chemicals; Apparatus for Cold, Pressurized Biogeochemical Experiments; Growing B Lymphocytes in a Three-Dimensional Culture System; Tissue-like 3D Assemblies of Human Broncho-Epithelial Cells; Isolation of Resistance-Bearing Microorganisms; Oscillating Cell Culture Bioreactor; and Liquid Cooling/Warming Garment.
Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.
Propulsion technology development efforts at the NASA Johnson Space Center continue to advance the understanding of the quantum vacuum plasma thruster (QThruster), a form of electric propulsion. Through the use of electric and magnetic fields, a Q-thruster pushes quantum particles (electrons/positrons) in one direction, while the Qthruster recoils to conserve momentum. This principle is similar to how a submarine uses its propeller to push water in one direction, while the submarine recoils to conserve momentum. Based on laboratory results, it appears that continuous specific thrust levels of 0.4 - 4.0 N/kWe are achievable with essentially no onboard propellant consumption. To evaluate the potential of this technology, a mission analysis tool was developed utilizing the Generalized Reduced Gradient non-linear parameter optimization engine contained in the Microsoft Excel® platform. This tool allowed very rapid assessments of "Q-Ship" minimum time transfers from earth to the outer planets and back utilizing parametric variations in thrust acceleration while enforcing constraints on planetary phase angles and minimum heliocentric distances. A conservative Q-Thruster specific thrust assumption (0.4 N/kWe) combined with "moderate" levels of space nuclear power (1 - 2 MWe) and vehicle specific mass (45 - 55 kg/kWe) results in continuous milli-g thrust acceleration, opening up realms of human spaceflight performance completely unattainable by any current systems or near-term proposed technologies. Minimum flight times to Mars are predicted to be as low as 75 days, but perhaps more importantly new "retro-phase" and "gravity-augmented" trajectory shaping techniques were revealed which overcome adverse planetary phasing and allow virtually unrestricted departure and return opportunities. Even more impressively, the Jovian and Saturnian systems would be opened up to human exploration with round-trip times of 21 and 32 months respectively including 6 to 12 months of exploration at the destinations. Finally, interstellar trip times are assessed at milli-g acceleration levels.
Motivated by the need to reduce noise pollution from aircraft engines, NASA has continued to design, manufacture and test recently patented structures that mimic the geometry and the broadband and low frequency acoustic absorption of assemblies of natural reeds. This report documents a screening test, which is a precursor to more controlled modelling experiments. The purpose of this experiment was to identify variables and prototype design features that might play a dominant role in the acoustic performance of these structures. To date, twenty-four prototypes, each with an overall shape of a cube (nominally 50 mm x 50 mm x 50 mm), were designed and additively manufactured from thermoplastics using a Fused Filament Fabrication technique. The prototypes were tested in the NASA Glenn and Langley Normal Incidence Tubes to experimentally determine the acoustic absorption as a function of frequency from 400 Hz to 3000 Hz. Results indicate that a variety of structures exhibit substantial acoustic absorption in that frequency range, with an average absorption coefficient greater than 0.6, especially in the frequency range of 400 Hz to 1000 Hz. Six basic prototype designs were chosen to inform future modeling research. Results of these experiments can be used to evaluate existing physics-based models of the interaction of sound waves with these structures or to develop new models. Validated physics-based models of these structures can help engineers optimize the designs for different commercial noise control applications.
Increased electrification of aircraft systems, a growing trend in the aircraft industry, affects subsystems that have historically been pneumatically driven by the engine. Optimized design of propulsion and power systems must account for the requirements of these subsystems. One such subsystem, the wing ice protection system, is the focus of this paper. A preliminary computational icing analysis has been conducted using the LEWICE and ANSYS FENSAP-ICE software to characterize the requirements of a thermal ice protection system for three More Electric Aircraft concepts. This paper summarizes the methodology, simulation execution, and icing conditions used for the analysis as well as discusses the results, observed trends, and impacts to system design. This initial analysis indicates that the computed heat requirements for the wing ice protection systems are not within the capabilities of known traditional systems. A discussion of potential methods for reducing the heat flow requirement by the ice protection system is included. Potential refinements to the analysis to improve the accuracy are also discussed.
The growing interest in developing high-voltage-, high-power-capable electrical components for electric aircraft propulsion requires a more in-depth understanding of their electrical characteristics, critical material responses, and their synergistic influence on the overall performance of the system. A model that can accurately replicate the electrical, magnetic, thermal, and mechanical operating stresses and successfully predict the performance of the components will help engineers optimize the system design for a given airframe and powertrain.
A trade space exploration of a new NASA regional transport aircraft concept called the SUbsonic Single Aft eNgine (SUSAN) Electrofan is presented. The SUSAN concept uses a 20MW Electrified Aircraft Propulsion (EAP) system to enable advance Propulsion Airframe Integration (PAI) in transport category aircraft. Alternative fuels will be used to reduce the amount of emissions per energy used. By combining these features there is the potential to reduce aircraft emissions by 50% per passenger/mile while retaining the size, speed, and range of large regional jets. SUSAN is has a 750 mile economic mission, a 2500 mile design range and a maximum capacity of 180 passengers. The SUSAN configuration utilizes a single aft mounted engine and distributed electric wing-mounted thrusters on a tube and wing arrangement with a T-tail empennage. The SUSAN Electrofan employs a hybrid powertrain to enable: single turbofan operation on a large transport category aircraft; increased aerodynamic and propulsive efficiency through placement of electric engines; optimized turbofan sizing and efficiency through control and electric boosting, reduced control surface sizing through thrust augmentation. A single use battery is employed as the power source in case of turbofan failure. The design study also considers the constraints of operating within the current airport, airspace and economic constraints. This paper presents the status of the trade space exploration; however the concept definition is not finished. Forward work includes optimizing the overall aircraft configuration and including certain hard to model features like boundary layer ingestion or natural laminar flow across all appliable subsystems. Additional work forward work is a more extensive analysis of the configuration using alternative fuels.
The SUSAN concept uses a 20-megawatt Electrified Aircraft Propulsion system to enable advance Propulsion Airframe Integration in transport category aircraft. Alternative fuels will be used to reduce the amount of emissions per energy used. By combining these features there is the potential to reduce aircraft emissions by 50 percent per passenger/mile while retaining the size, speed, and range of large regional jets. The SUSAN is has a 750-mile economic mission, a 2500-mile design range and a maximum capacity of 180 passengers. The SUSAN configuration utilizes a single aft mounted engine and distributed electric wing-mounted thrusters on a tube and wing arrangement with a T-tail empennage. The SUSAN Electrofan employs a hybrid powertrain to enable: single turbofan operation on a large transport category aircraft; increased aerodynamic and propulsive efficiency through placement of electric engines; optimized turbofan sizing and efficiency through control and electric boosting, reduced control surface sizing through thrust augmentation. A single use battery is employed as the power source in case of turbofan failure. The design study also considers the constraints of operating within the current airport, airspace, and economic constraints. Forward work includes optimizing the overall aircraft configuration and including certain hard to model features like boundary layer ingestion or natural laminar flow across all appliable subsystems. Additional work forward work is a more extensive analysis of the configuration using alternative fuels.
Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.
The disclosure is directed to solving a full trajectory optimization problem in real-time for a hybrid electric vehicle (HEV) such that future driving conditions and energy usage may be fully considered in determining optimal engine energy usage and battery energy usage in real-time during a trip. An electronic control unit of the HEV may be configured to: receive route information for a route to be driven by the HEV; and after receiving the route information, iterating the operations of: measuring a current state of charge (SOC) of the battery; using at least the measured SOC and an initial co-state value stored in a memory, performing a process to iteratively update the co-state value to obtain an updated co-state value; using at least the updated co-state value, computing an updated control value; and applying the updated control value to control a usage of the battery and the internal combustion engine.