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At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

NASA NTRS2012

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

Mixed Integer Programming↗

NASA NTRS1980

Formulation and implementation of a practical algorithm for parameter estimation with process and measurement noise

A new formulation is proposed for the problem of parameter estimation of dynamic systems with both process and measurement noise. The formulation gives estimates that are maximum likelihood asymptotically in time. The means used to overcome the difficulties encountered by previous formulations are discussed. It is then shown how the proposed formulation can be efficiently implemented in a computer program. A computer program using the proposed formulation is available in a form suitable for routine application. Examples with simulated and real data are given to illustrate that the program works well.

Maine, R. E.↗

NASA NTRS1995

System identification methods for aircraft flight control development and validation

System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

Tischler, Mark B.↗

NASA NTRS1985

Probabilistic Finite Element: Variational Theory

The goal of this research is to provide techniques which are cost-effective and enable the engineer to evaluate the effect of uncertainties in complex finite element models. Embedding the probabilistic aspects in a variational formulation is a natural approach. In addition, a variational approach to probabilistic finite elements enables it to be incorporated within standard finite element methodologies. Therefore, once the procedures are developed, they can easily be adapted to existing general purpose programs. Furthermore, the variational basis for these methods enables them to be adapted to a wide variety of structural elements and to provide a consistent basis for incorporating probabilistic features in many aspects of the structural problem. Tasks concluded include the theoretical development of probabilistic variational equations for structural dynamics, the development of efficient numerical algorithms for probabilistic sensitivity displacement and stress analysis, and integration of methodologies into a pilot computer code.

Belytschko, T.↗

NASA NTRS1988

Optimization of organic Rankine cycles for space station applications

The purpose of the current program is to investigate the tradeoffs between solar dynamic and nuclear powered systems for the space station. This research is based on a typical Rankine cycle using toluene as the working fluid. The first objective is to produce an adequate thermodynamic cycle model and calculate its efficiency. The next step is to implement a sizing algorithm that calculates the capacity of the various elements of the system, such as the radiator and regenerator, for a given electrical output. Then, the mass of each component must be calculated to give the overall total system mass. Likewise, the space for each component can be determined, giving an estimate of what volume must be available to place the system into orbit.

Eubanks, Dana L.↗

NASA NTRS1981

Longitudinal stability and control derivatives obtained from flight data of a PA-30 aircraft

In order to obtain reliable and accurate values of the stability and control derivatives, the Dryden Fligh Research Center (DFRC) developed a technique for extracting the derivatives from flight data. This technique is implemented by a set of FORTRAN computer programs that is based on a modified maximum likelihood estimator that uses the Newton-Raphson algorithm to perform the required minimization of the derivatives. Data was obtained with a PA-30, light twin-engine general aviation aircraft in zero, half, and full flap configuration in level unaccelerated flight with the landing gear retracted. The derivatives were plotted as functions of angle of attack using various graphical arrangements to show variations of wind tunnel and flight determined values at zero flap settings. Also, data was displayed to show the effects of flap deflection and thrust variation on the longitudinal stability derivatives. The angle of attack and angle of sideslip were measured. The dynamic pressure, velocity, and altitude were calculated, using a FORTRAN computer program, from the static and dynamic pressures. The control deflections of the stabilator, ailerons, and rudder also were recorded along with left throttle position, engine rpm, and manifold pressure.

Turley, D. R.↗

NASA NTRS1976

Flight test of a stall sensor and evaluation of its application to an aircraft stall deterrent system using the NASA LRC general aviation simulator

A series of flight maneuvers were developed to cover the range of flight conditions and to define the repeatability and hysteresis of the sensors. Initial flights were made with two sensors at the + or - 68 percent span and 60 percent and 70 percent chord stations. The primary effort in simulation program development was to modify the LRC General Aviation Simulator (GAS) Fortran programs to allow execution on the MSU UNIVAC 1106. A simple model of the sensor-servo stall deterrent system was developed. A one degree of freedom model of pitch dynamics of the airplane and stall deterrent system was developed to make initial estimates of the control system gains. A position error plus rate damping control algorithm was found to have acceptable characteristics.

Bennett, G.↗

NASA NTRS1979

Application of a ground based minicomputer system for real time, closed loop control of remotely piloted aircraft models used in stall/spin research

The paper describes a minicomputer-based, real-time closed loop remote control system at NASA Langley outdoor facility which is used to determine the stall/departure/spin characteristics of high-performance aircraft. The experiments are conducted with 15% dynamically scaled, unpowered models that are dropped from 3000 m and ground controlled. The effects of time delays and sampling rates on the stability of the control system and the selection of digital algorithms to meet frequency response and real time constraints are examined. Also described is the implementation of the modular software for the flexible programming of multi-axis control laws.

Montoya, R. J.↗

NASA NTRS1997

Dynamic Flow Management Problems in Air Transportation

In 1995, over six hundred thousand licensed pilots flew nearly thirty-five million flights into over eighteen thousand U.S. airports, logging more than 519 billion passenger miles. Since demand for air travel has increased by more than 50% in the last decade while capacity has stagnated, congestion is a problem of undeniable practical significance. In this thesis, we will develop optimization techniques that reduce the impact of congestion on the national airspace. We start by determining the optimal release times for flights into the airspace and the optimal speed adjustment while airborne taking into account the capacitated airspace. This is called the Air Traffic Flow Management Problem (TFMP). We address the complexity, showing that it is NP-hard. We build an integer programming formulation that is quite strong as some of the proposed inequalities are facet defining for the convex hull of solutions. For practical problems, the solutions of the LP relaxation of the TFMP are very often integral. In essence, we reduce the problem to efficiently solving large scale linear programming problems. Thus, the computation times are reasonably small for large scale, practical problems involving thousands of flights. Next, we address the problem of determining how to reroute aircraft in the airspace system when faced with dynamically changing weather conditions. This is called the Air Traffic Flow Management Rerouting Problem (TFMRP) We present an integrated mathematical programming approach for the TFMRP, which utilizes several methodologies, in order to minimize delay costs. In order to address the high dimensionality, we present an aggregate model, in which we formulate the TFMRP as a multicommodity, integer, dynamic network flow problem with certain side constraints. Using Lagrangian relaxation, we generate aggregate flows that are decomposed into a collection of flight paths using a randomized rounding heuristic. This collection of paths is used in a packing integer programming formulation, the solution of which generates feasible and near-optimal routes for individual flights. The algorithm, termed the Lagrangian Generation Algorithm, is used to solve practical problems in the southwestern portion of United States in which the solutions are within 1% of the corresponding lower bounds.

Patterson, Sarah Stock↗

DOE OSTI2024

Approximate Dynamic Programming With Enhanced Off-Policy Learning for Coordinating Distributed Energy Resources

Herein this paper proposes an innovative approximate dynamic programming (ADP) method for distributed energy resource coordination with the loss of life of battery energy storage system (BESS) explicitly modeled. The dispatch policy is designed to account for both calendrical and cyclical aging effects on BESS, explicitly modeling the impacts of ambient temperature on BESS lifespan. The proposed ADP employs an adaptive critic method and enhanced off-policy deterministic policy gradient (DPG) strategy, addressing the limitations of the on-policy gradient-based ADP approaches, including inadequate exploration, low data usage, and computational complexity. In particular, a customized policy is proposed to guide the algorithm to explore some promising decisions and thereby improve exploration capability and learning efficiency compared to conventional DPG-based learning approaches, which may struggle to find a global optimum due to random noisy action-based exploration or require expert demonstration with extra effort. The proposed method is illustrated using the IEEE 123-node system and compared with the existing ADP methods to prove solution accuracy and demonstrate the effects of incorporating degradation models into control design. Case studies showed that the proposed ADP effectively coordinates DERs with a 10 times smaller optimization gap compared to existing methods, and the incorporation of the BESS life loss model ensures the expected lifespan and results in significant cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

A Constrained Data Assimilation Algorithm Based on GSI Hybrid 3D-EnVar and Its Application

Abstract Data assimilation (DA) at mesoscales is important for severe weather forecasts, yet the techniques of data assimilation at this scale remain a challenge. This study introduces dynamical constraints in the Gridpoint Statistical Interpolation (GSI) three-dimensional ensemble variational (3D-EnVar) data assimilation algorithm to enable the use of high-resolution surface observations of precipitation to improve atmospheric analysis at mesoscales. The constraints use the conservations of mass and moisture. Mass constraint suppresses the unphysical high-frequency oscillation, while moisture conservation constrains the atmospheric states to conform with the observed high-resolution precipitation. We show that the constrained data assimilation (CDA) algorithm significantly reduced the spurious residuals of the mass and moisture budgets compared to the original data assimilation (ODA). A case study is presented for a squall line over the Southern Great Plains on 20 May 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E) of the Atmospheric Radiation Measurement (ARM) program by using ODA or CDA analysis as initial condition of forecasts. The state variables, and the location and intensity of the squall line are better simulated in the CDA experiment. Results show how surface observation of precipitation can be used to improve atmospheric analysis through data assimilation by using the dynamical constraints of mass and moisture conservations.

Wang, Jia↗

DOE OSTI2020

Hydration Mechanisms in Nanoparticle Interaction and Surface Energetics

Work on the project advanced molecular level understanding, prediction and control of nanoscale hydration in salt solutions under electric stimuli or ionic patterning. Permeation of nanoporous electrodes at preset voltage underlies the function of ultracapacitors. Transitory regulation of wetting in nanoporous media by electric field spans an array of applications in materials, energy storage, and separation sciences. The physically related modulation of nanoparticle solubility by surface charges can significantly extend the range of the nanomaterial applications, improve processing techniques, and potentially alleviate environmental concerns. Pore/solution equilibria, and activated kinetics of liquid gating by nanoconfined electrolytes are challenging problems at the forefront of experimental and theoretical research. Addressing these problems from a molecular perspective required the development of state-of-the-art simulation algorithms in statistical mechanics to capture complex processes in open systems under electric control. Parallel studies of wetting and dispersibility of polar and ionizing particles aim to uncover predictive relations between electrowetting, chemical functionalization, and geometry of nanomaterial particles. By nonequilibrium dynamic modeling, we elucidated electrolyte flow in nanochanels and associated electrokinetic energy conversion. Research on the program provided training opportunities for the next generation of scientists in computational chemistry. Insights, and methods from the project implicate broad segment of researchers in energy and nanosciences, materials and surface chemistry.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1982

Aerothermal modeling

The objectives, approach, and status of a program to develop the computational fluid dynamics tools needed to improve combustor design and analysis are outlined. The calculation procedure selected consists of a finite difference solution of the time averaged, steady state, primitive variable, elliptic form of the Reynolds equations. Standard TEACH type numerics are used to solve the resulting equations. These include hybrid differencing, SIMPLE algorithm for the pressure field, line by line iterative solution using the ADI method and the tridiagonal matrix algorithm (TDMA). Convergence is facilitated by using under relaxation. The physical processes are modeled by a two equation eddy viscosity model for turbulence; combustion is represented by a simple, irreversible, one step chemical reaction whose rate is influenced only by the time scale of the turbulence. The model evaluation procedure is also described.

Sturgess, G. J.↗

NASA NTRS1987

Structural tailoring using the SSME/STAEBL code

Space Shuttle Main Engine/Structural Tailoring of Engine Blades (SSME/STAEBL) was developed by systematically modifying and enhancing the STAEBL code developed by Pratt and Whitney under contract to NASA Lewis Research Center. STAEBL was designed for application to gas turbine blade design. Typical design variables include blade thickness distribution and root chord. Typical constraints include resonance margins, root stress, and root to chord ratios. In this program, the blade is loaded by centrifugal forces only. Additions and modifications of STAEBL included in SSME/STAEBL include (1) thermal stress analysis; (2) gas dynamic (pressure) loads; (3) temperature dependent material and thermal properties; (4) forced vibrations; (5) tip displacement constraints; (6) single crystal material analysis; (7) blade cross section stacking offsets; and (8) direct time integration algorithm for transient dynamic response. Capabilities are also included which permit data transfer from finite element models and stand-alone analysis.

Rubinstein, Robert↗

NASA NTRS1990

Ascent guidance algorithm using lidar wind measurements

The formulation of a general nonlinear programming guidance algorithm that incorporates wind measurements in the computation of ascent guidance steering commands is discussed. A nonlinear programming (NLP) algorithm that is designed to solve a very general problem has the potential to address the diversity demanded by future launch systems. Using B-splines for the command functional form allows the NLP algorithm to adjust the shape of the command profile to achieve optimal performance. The algorithm flexibility is demonstrated by simulation of ascent with dynamic loading constraints through a set of random wind profiles with and without wind sensing capability.

Cramer, Evin J.↗

NASA NTRS1987

General purpose algorithms for characterization of slow and fast phase nystagmus

In the overall aim for a better understanding of the vestibular and optokinetic systems and their roles in space motion sickness, the eye movement responses to various dynamic stimuli are measured. The vestibulo-ocular reflex (VOR) and the optokinetic response, as the eye movement responses are known, consist of slow phase and fast phase nystagmus. The specific objective is to develop software programs necessary to characterize the vestibulo-ocular and optokinetic responses by distinguishing between the two phases of nystagmus. The overall program is to handle large volumes of highly variable data with minimum operator interaction. The programs include digital filters, differentiation, identification of fast phases, and reconstruction of the slow phase with a least squares fit such that sinusoidal or psuedorandom data may be processed with accurate results. The resultant waveform, slow phase velocity eye movements, serves as input data to the spectral analysis programs previously developed for NASA to analyze nystagmus responses to pseudorandom angular velocity inputs.

Lessard, Charles S.↗

DOE OSTI2025

Optimization of an aerostructural machining process using physics-guided Bayesian stability modelling

Existing algorithms for predicting milling chatter have not been widely adopted in industry since they require specialized instruments to measure the stability inputs. This study describes how the machining process for a meter-scale aluminum aerostructure was optimized using a physics-guided Bayesian stability model. The study was performed in collaboration with an industrial partner on production machines to evaluate the practicality of the proposed method under real-world conditions. For each cutting tool, the Bayesian approach automatically selected a small number of cutting tests, which were monitored using a microphone to observe the chatter frequency. The algorithm learned the system dynamics, cutting forces, and stability map from these test results. A novel algorithm for predicting tool bending stress was incorporated into the test selection algorithm to avoid tool breakage. On average, each set of optimized cutting parameters required less than six tests to identify and were 97% more productive than baseline parameters from the cutting tool manufacturer. The machining program was then further optimized using commercial feedrate scheduling software to remove cutting force spikes and reduce air cutting time. Five components were machined using the optimized process. These results demonstrate the potential for physics-guided Bayesian models to improve productivity in industrial settings.

Cornelius, Aaron [UT Knoxville]↗

NASA NTRS1986

HYTESS 2: A Hypothetical Turbofan Engine Simplified Simulation with multivariable control and sensor analytical redundancy

A hypothetical turbofan engine simplified simulation with a multivariable control and sensor failure detection, isolation, and accommodation logic (HYTESS II) is presented. The digital program, written in FORTRAN, is self-contained, efficient, realistic and easily used. Simulated engine dynamics were developed from linearized operating point models. However, essential nonlinear effects are retained. The simulation is representative of the hypothetical, low bypass ratio turbofan engine with an advanced control and failure detection logic. Included is a description of the engine dynamics, the control algorithm, and the sensor failure detection logic. Details of the simulation including block diagrams, variable descriptions, common block definitions, subroutine descriptions, and input requirements are given. Example simulation results are also presented.

Merrill, W. C.↗