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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Static structural finite element models of an aluminum-framed crystalline silicon (c-Si) photovoltaic (PV) module and a glass-glass thin film PV module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Parametric analyses using Latin Hypercube Sampling (LHS) were performed to propagate simulation input uncertainties related to module material properties, dimensions, and manufacturing tolerances into expected uncertainties in simulated deflection predictions. This exercise verifies the applicability and validity of finite element modeling for predicting mechanical behavior of solar modules across architectures and enables computational models to be used with greater confidence in assessment of module mechanical stressors and design for reliability. Sensitivity analyses were also performed on the uncertainty quantification data sets using linear correlation coefficients to elucidate the key parameters influencing module deformation. This information has implications on which materials or parameters may be optimized to best increase module stiffness and reliability, whether the key optimization parameters change with module architecture or loading magnitudes, and whether parameters such as frame design and racking must be replicated in reduced-scale reliability studies to adequately capture full module mechanical behavior.

14 SOLAR ENERGY↗
NASA NTRS2004

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.

Williams, Peggy S.↗
DOE OSTI2026

GP Cosmology Surrogate v1.0

GP Cosmology Surrogate is a Python library for building and training a generalized multi-output Gaussian process (GP) framework of @takhtaganov2021cosmic. In this approach, the surrogate is constructed sequentially, guided by a Bayesian optimization acquisition function that targets reduction of emulation error in the regions most consistent with the observational data. This adaptive design concentrates computational resources where they have the greatest impact on inference accuracy. The library supports efficient training for separable GP kernels, which allows the use of Kronecker algebra to handle high-dimensional input spaces and large numbers of correlated outputs. This makes it well suited for applications such as modeling cosmological power spectra, large-scale physical simulations, and multi-output hyperparameter tuning. By combining scalable multi-output GP modeling with data-driven adaptive sampling, GPsurrogate enables parameter inference and optimization with substantially fewer simulations than conventional space-filling designs.

Lukic, Zarija [Lawrence Berkeley National Laborato↗
DOE OSTI2024

Beam Dynamics simulations for ERDC project -- SRF linac for industrial use

Compact conductively cooled SRF industrial linacs can provide unique parameters of the electron beam for industrial applications. (up to 10MeV, 1MW). For ERDC project we designed normal conducting RF injector with thermal RF gridded gun integrated in first cell of multi-cell cavities. For design of the RF gun we used MICHELLE software to simulate and optimize parameters of the beam. Output file was converted to ASTRA format and most beam dynamic simulations in multi-cell normal conducting cavity and cryomodule were performed by using ASTRA software. For cross-checking we compare results of MICHELLE and AS-TRA in first few cells. At the end of injector beam reach ~250keV energy which allow to trap bunch in acceleration regime without losses in TESLA like 1.3 GHz cavity. Short solenoid at the end of injector allow to regulate transverse beam size in cryomodule to match beam to extraction system and also reduce charge losses in accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Low-Cost Heliostat for High-Flux Small-Area Receivers (Final Technical Report)

This project analyzed a two-stage heliostat concept consisting of a tracking stage and a concentrating stage. The tracking stage uses mirrors mounted on a common drive that move to track the sun. The concentrating stage consists of stationary mirrors that each have a unique angle to direct rays towards a small-area, high-flux, point-focused receiver. By splitting the collection and concentrating process into two stages, multiple small, inexpensive mirrors can share a structure and be controlled by a single drive in the tracking stage. The project effort developed modeling techniques that were specifically relevant to this two-stage heliostat concept. Both field-level and unit-level models were developed. The field-level model does not explicitly consider unit-level losses which are predicted by the unit-level model and then integrated into the field-level model through a correlation referred to as an efficiency modifier. This approach is referred to as the two-model approach; the development and demonstration of this two-model approach for a multi-stage heliostat technology is a key outcome of this work. The field-level model is used to design a field that hits a specific design day power given a set of heliostat design parameters. An oversized field is simulated and then heliostat units are removed based on their annual energy production in order to generate the highest performing field. The field reduction procedure fits a smooth curve fit to annual energy production as a function of position in the field which has the effect of reducing the noise that is otherwise caused by the Monte Carlo ray tracing technique. This approach is referred to as the annual energy fit method and substantially reduces computational run time for a given field level modeling accuracy. The annual energy fit approach enables the selection of a properly sized, high-performing field using orders of magnitude fewer rays than would otherwise be possible and the development of this approach is a second key outcome of this work. These models are used within a genetic optimization algorithm in order to optimize the geometric parameters associated with a heliostat in order to achieve the lowest cost per unit of collected design day power. The cost modeling that underlies the optimization is a simple, scaling type analysis backed up by a much more detailed Design for Manufacture and Assembly (DFMA) analysis. Although the figure of merit used for optimization was not cost per mirror area, this metric is reasonable to use as a means of comparison. The optimally designed 500 kW design has a tracking mirror specific cost of $181.85/m 2 , which is significantly larger than the target value and also larger than the current state of the art. The cost of the torque-tube type linkages contributed substantially to the overall cost. Based on this observation, potentially attractive alternative design configuration utilizing a capstan type actuation system should be investigated. Finally, NREL compared the performance of the two-stage heliostat to the performance of a focused and different sized flat conventional heliostats and showed that, as expected, additional losses versus the convention heliostat caused by a worse cosine efficiency, two stages of reflection, and interstage interactions. The two-stage heliostat requires around 75% more reflective area than a flat 1x1 meter conventional heliostat (similar to a focused heliostat) and 40% more than a flat 2x2 meter conventional heliostat.

14 SOLAR ENERGY↗
NASA NTRS2011

Achievable Performance and Effective Interrogator Design for SAW RFID Sensor Tags

For many NASA missions, remote sensing is a critical application that supports activities such as environmental monitoring, planetary science, structural shape and health monitoring, non-destructive evaluation, etc. The utility of the remote sensing devices themselves is greatly increased if they are passive that is, they do not require any on-board power supply such as batteries and if they can be identified uniquely during the sensor interrogation process. Additional passive sensor characteristics that enable greater utilization in space applications are small size and weight, long read ranges with low interrogator power, ruggedness, and operability in extreme environments (vacuum, extreme high/low temperature, high radiation, etc.) In this paper, we consider one very promising passive sensor technology, called surface acoustic wave (SAW) radio-frequency identification (RFID), that satisfies all of these criteria. Although SAW RFID tags have great potential for use in numerous space-based remote sensing applications, the limited collision resolution capability of current generation tags limits the performance in a cluttered sensing environment. That is, as more SAW-based sensors are added to the environment, numerous tag responses are superimposed at the receiver and decoding all or even a subset of the telemetry becomes increasingly difficult. Background clutter generated by reflectors other than the sensors themselves is also a problem, as is multipath interference and signal distortion, but the limiting factor in many remote sensing applications can be expected to be tag mutual interference. This problem may be greatly mitigated by proper design of the SAW tag waveform, but that remains an open research problem, and in the meantime, several other related questions remain to be answered including: What are the fundamental relationships between tag parameters such as bit-rate, time-bandwidth-product, SNR, and achievable collision resolution? What are the differences in optimal or near-optimal interrogator designs between noise-limited environments and interference-limited environments? What are the performance characteristics of different interrogator designs in term of parameters such as transmitter power level, range, and number of interfering tags? In this paper, we present the results of a research effort aimed at providing at least partial answers to all of these questions.

Barton, Richard J.↗
NASA NTRS1971

The optimization of complex systems with respect to multiple criteria.

A difficult aspect of system optimization is the choice of a single cost function relating system parameters to the quality of the design; there are generally conflicting criteria by which the system can be evaluated. This paper discusses the problem of optimization with respect to multiple criteria, i.e., with a vector-valued cost function, without prespecifying constraints or the weighting of the criteria. The paper discusses theoretical results concerning the set of non-inferior solutions so generated and a computational algorithm for obtaining a characteristic set of non-inferior solutions.

Beeson, R. M.↗
NASA NTRS1975

Adaptive control laws for F-8 flight tests

An adaptive flight-control-system design for NASA's F-8 Digital Fly-by-Wire research aircraft is described. This design implements an explicit parallel maximum likelihood identification algorithm to estimate key aircraft parameters. The estimates are used to compute gains in simplified quadratic-optimal command augmentation control laws. Design details for the control laws and identifier are presented, and performance evaluation results from NASA Langley's F-8 simulator are summarized.

Stein, G.↗
NASA NTRS1977

Adaptive control laws for F-8 flight test

This paper describes an adaptive flight control system design for NASA's F-8 digital fly-by-wire research aircraft. This design implements an explicit parallel maximum likelihood identification algorithm to estimate key aircraft parameters. The estimates are used to compute gains in simplified quadratic-optimal command augmentation control laws. Design details for the control laws and identifier are presented, and performance evaluation results from NASA Langley's F-8 Simulator are summarized.

Stein, G.↗
NASA NTRS1979

Combined strength and aeroelastic wing synthesis via constraint approximation

A numerical optimization program using constraint approximations for preliminary sizing of wing structural design parameters to satisfy simultaneous strength and aeroelastic requirements is described. The effects of wing flexibility on loads and flutter are included. The iterative procedure approximates wing internal load distributions and flutter response in generating design constraints. Though a linear Taylor series approximation to the variation of flutter speed is made, constraints in general are formulated as nonlinear and solved in a minimum weight problem using a feasible directions search. The technique is demonstrated for the determination of the optimal ply orientations and for simultaneous sizing for strength and flutter with simple constraint approximations.

Mullen, J., Jr.↗
NASA NTRS2001

Discrete-State Simulated Annealing For Traveling-Wave Tube Slow-Wave Circuit Optimization

Algorithms based on the global optimization technique of simulated annealing (SA) have proven useful in designing traveling-wave tube (TWT) slow-wave circuits for high RF power efficiency. The characteristic of SA that enables it to determine a globally optimized solution is its ability to accept non-improving moves in a controlled manner. In the initial stages of the optimization, the algorithm moves freely through configuration space, accepting most of the proposed designs. This freedom of movement allows non-intuitive designs to be explored rather than restricting the optimization to local improvement upon the initial configuration. As the optimization proceeds, the rate of acceptance of non-improving moves is gradually reduced until the algorithm converges to the optimized solution. The rate at which the freedom of movement is decreased is known as the annealing or cooling schedule of the SA algorithm. The main disadvantage of SA is that there is not a rigorous theoretical foundation for determining the parameters of the cooling schedule. The choice of these parameters is highly problem dependent and the designer needs to experiment in order to determine values that will provide a good optimization in a reasonable amount of computational time. This experimentation can absorb a large amount of time especially when the algorithm is being applied to a new type of design. In order to eliminate this disadvantage, a variation of SA known as discrete-state simulated annealing (DSSA), was recently developed. DSSA provides the theoretical foundation for a generic cooling schedule which is problem independent, Results of similar quality to SA can be obtained, but without the extra computational time required to tune the cooling parameters. Two algorithm variations based on DSSA were developed and programmed into a Microsoft Excel spreadsheet graphical user interface (GUI) to the two-dimensional nonlinear multisignal helix traveling-wave amplifier analysis program TWA3. The algorithms were used to optimize the computed RF efficiency of a TWT by determining the phase velocity profile of the slow-wave circuit. The mathematical theory and computational details of the DSSA algorithms will be presented and results will be compared to those obtained with a SA algorithm.

Wilson, Jeffrey D.↗
NASA NTRS1986

Integrated aeroservoelastic tailoring of lifting surfaces

An approach to the integration of two design activities, structural design and active control design, for a highly idealized aeroservoelastic system is presented. The particular design goal for this study is the maximization of the stable airspeed envelope of an idealized model of an aeroservoelastic system through rational and systematic variation of structural and control design parameters. The steady-state linear quadratic regulator is used to model the control subsystem; the structural subsystem is assigned characteristic design parameters, such as shear center position. The application of the procedure described here produces optimally controlled structures with stability characteristics superior to those of open-loop and initial closed-loop designs.

Zeiler, T. A.↗
NASA NTRS1989

Euler procedure for three-dimensional transonic wall interference

Based on an optimization formulation, a procedure has been developed to evaluate Mach number and angle-of-attack corrections. The Euler equations are assumed to be the flow governing equations. To obtain efficient solutions for the optimization problem, the iterative solutions for the flow variables and the design parameters are simultaneously updated. In addition to the model lift and geometry, the procedure requires pressure measurements near the tunnel walls. The tunnel boundary conditions are based on the introduction of Reimann invariants for a one-dimensional flow normal to the boundary. Computations are performed to verify that the errors introduced by this approximate boundary-condition formulation are acceptably small. The correction scheme is applied to an aircraft configuration in an open jet. The results indicate that the optimization scheme is highly efficient with the rate of convergence of the flow solution nearly equal to the corresponding rate of a regular analysis problem.

Rizk, Magdi H.↗
NASA NTRS1991

Progress in multirate digital control system design

A new methodology for multirate sampled-data control design based on a new generalized control law structure, two new parameter-optimization-based control law synthesis methods, and a new singular-value-based robustness analysis method are described. The control law structure can represent multirate sampled-data control laws of arbitrary structure and dynamic order, with arbitrarily prescribed sampling rates for all sensors and update rates for all processor states and actuators. The two control law synthesis methods employ numerical optimization to determine values for the control law parameters. The robustness analysis method is based on the multivariable Nyquist criterion applied to the loop transfer function for the sampling period equal to the period of repetition of the system's complete sampling/update schedule. The complete methodology is demonstrated by application to the design of a combination yaw damper and modal suppression system for a commercial aircraft.

Berg, Martin C.↗
NASA NTRS1974

A unified approach to aircraft parameter identification

The most accurate identification results are obtained when all three elements of the identification process - the identification algorithm, the control input, and the instrumentation system - are considered in a unified approach. This type of approach for the design of optimal control inputs and for determining the effect of the instrumentation system, in each case with respect to the identification process is discussed. Design of control inputs which optimize the sensitivity of the system output to the unknown parameters is given. Results using these inputs in an extensive simulation of the identification process indicate they perform measurably better than doublet type inputs. A technique is then presented for specifying an optimal instrumentation system or for determining the effect, the instrumentation system has on the accuracy of the parameter estimates.

Stepner, D. E.↗
NASA NTRS1993

Natural Environmental Service Support to NASA Vehicle, Technology, and Sensor Development Programs

The research performed under this contract involved definition of the natural environmental parameters affecting the design, development, and operation of space and launch vehicles. The Universities Space Research Association (USRA) provided the manpower and resources to accomplish the following tasks: defining environmental parameters critical for design, development, and operation of launch vehicles; defining environmental forecasts required to assure optimal utilization of launch vehicles; and defining orbital environments of operation and developing models on environmental parameters affecting launch vehicle operations.

Source record↗
DOE OSTI2024

A hierarchal model for bacterial cell inactivation in solution by direct and indirect treatment using cold atmospheric plasmas

Cold atmospheric plasma devices have shown promise for a variety of plasma medical applications, including wound healing and bacterial inactivation often performed in liquids. In the latter application, plasma-produced reactive oxygen and nitrogen species (RONS) interact with and damage bacterial cells, though the exact mechanism by which cell damage occurs is unclear. Computational models can help elucidate relationships between plasma-produced RONS and cell killing by enabling direct comparison between dissimilar plasma devices and by examining the effects of changing operating parameters in these devices. In biological applications, computational models of plasma-liquid interactions would be most effective in design and optimization of plasma devices if there is a corresponding prediction of the biological outcome. In this work, we propose a hierarchal model for planktonic bacterial cell inactivation by plasma produced RONS in liquid. A previously developed reaction mechanism for plasma induced modification of cysteine was extended to provide a basis for cell killing by plasma-produced RONS. Results from the model are compared to literature values to provide proof of concept. Differences in time to bacterial inactivation as a function of plasma operating parameters including gas composition and plasma source configuration are discussed. Results indicate that optimizing gas-phase reactive nitrogen species production may be key in the design of plasma devices for disinfection.

59 BASIC BIOLOGICAL SCIENCES↗