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At least 811 records · Page 45

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NASA NTRS1991

Maximized gust loads for a nonlinear airplane using matched filter theory and constrained optimization

This paper describes and illustrates two matched-filter-theory based schemes for obtaining maximized and time-correlated gust-loads for a nonlinear airplane. The first scheme is computationally fast because it uses a simple one-dimensional search procedure to obtain its answers. The second scheme is computationally slow because it uses a more complex multidimensional search procedure to obtain its answers, but it consistently provides slightly higher maximum loads than the first scheme. Both schemes are illustrated with numerical examples involving a nonlinear control system.

Scott, Robert C.↗

DOE OSTI2022

Mild hybridisation of turboprop engine with high-power-density integrated electric drives

Here this paper shares with the aerospace community a case study of turboprop mild hybridisation using a recently developed integrated drive system in the University of Nottingham, UK, within the ACHIEVE project under EU H2020 CleanSky 2 program (project No. 737814). The developed drive system enables green taxiing of a turboprop aircraft while on the ground with its engine off, and as an electrical generator when the turboprop is in the air. The entire system is designed to be able to integrate within the power auxiliary gear box (PAGB) of a turboprop aircraft. Some of the key features of the developed system include a high-speed permanent magnet machine (up to 14,200rpm) with dual three-phase design, SiC-based high power density (11.8kW/L for the power converter, 35.3kW/L and 7.2kW/kg for the machine active parts), integrated cooling design for high-temperature operation (>130°C ambient temperature), fault tolerance consideration with dual channel operation capabilities and sensorless control for entire operational conditions. This paper is giving an overview of the design process of the electrical machine, power converters, and its cooling of the entire drive. Numerical analysis (FEM and CFD) and some experimental results are presented to demonstrate the effectiveness and the desired performance of the developed integrated drive system.

42 ENGINEERING↗

DOE OSTI2023

A hybrid analytical and numerical model for cross-over and performance decay in a unit cell vanadium redox flow battery

Developing an accurate and efficient model for cross-over is critical for improving the long-term performance of redox flow batteries (RFBs). Here, this work presents a hybrid analytical and numerical model that combines a two-dimensional analytical solution to the active species, a one-dimensional analytical model for cross-over mechanisms, and a zero-dimensional numerical model for outlet concentrations of reactants. By comparing with experiment over 41 cycles (ca. 144 h), the model reported a mean voltage difference of 0.0089 V, mean time difference of 14 s per cycle (of 3.5 h), maximum relative difference for capacity and energy of 1.34% and 1.63%, respectively. The predicted mean concentrations for V 2+ , V 3+ , and VO$_{2}^{+}$ in membrane are 65%~77% of measured values from the literature. Upon validation, the model reproduced behaviors in electrolyte imbalance similar to those observed in experiments and numerical models, and revealed the control of cross-over, self-discharge, stoichiometry of side reactions, and Coulombic efficiency on electrolyte imbalance. The model also demonstrates excellent computational efficiency for simulating 41 cycles (around 37,000 points) within 3~4 s. The demonstrated efficiency and accuracy for predicting cross-over and its impacts on voltage, capacity&energy decay, membrane concentrations, and electrolyte imbalance makes it a reliable tool for optimizing RFBs’ long-term performance.

25 ENERGY STORAGE↗

DOE OSTI2026

Safe Deep Reinforcement Learning for Robust Frequency and Voltage-Constrained Networked Microgrid Restoration

Here, this paper proposes a safe soft actor-critic reinforcement learning (RL) algorithm–based controller for networked microgrid restoration. It formulates the post black-start start as a finite-horizon constrained Markov decision process. The RL agent co-optimizes real and reactive power set-points for both grid-forming and grid-following inverters under explicit voltage and frequency constraints, while enforcing proper power sharing via the Mean Active Power Sharing Index (MPSI) and Mean Reactive Power Sharing Index (MQSI). Numerical results obtained on the IEEE 123-bus distribution system show that the proposed method achieves a mean voltage build-up time of 0.01 s without breaching the 5% sharing-violation budget under various load scenarios, considering MPSI and MQSI indices. These findings demonstrate that the proposed method yields fast and safe black-start schedules without resorting to heuristic penalties.

Selim, Alaa [Dartmouth College, Hanover, NH (Unite↗

NASA NTRS1990

Optimal helicopter trajectory planning for terrain following flight

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Menon, P. K. A.↗

DOE OSTI2026

Effects of plasma squareness on RMP response in MAST-U

The effect of the squareness of the plasma boundary shape on the plasma response to the applied n = 2 (n is the toroidal mode number) resonant magnetic perturbation, and consequently on controlling the edge-localized mode (ELM) in MAST-U in the double-null configuration, is numerically systematically investigated. The modeling is performed utilizing three different plasma response models: the single-fluid model, the two-fluid model and the magnetohydrodynamic-kinetic hybrid model. The effect of the plasma squareness on ELM control is found to depend on the equilbrium kinetic profiles. Fixing the equilibrium radial profiles to that from a recent MAST-U discharge, the experimental plasma shape is found to be close to optimal for ELM control in terms of squareness. The optimal coil phasing does not significantly vary with varying plasma squareness. These findings robustly hold with (i) two figures of merit (FoMs) defined for predicting the ELM control feasibility, and (ii) three plasma response models employed for evaluating these FoMs.

MAST-U↗

DOE OSTI2025

Challenges in Continuous In-Field Critical Current Testing of High-Temperature Superconducting Tapes: Thermal and Mechanical Perspectives

High-temperature superconductors (HTS) are essential for ultra-high-field applications requiring exceptional current-carrying capacity under extreme conditions. However, systematic characterization of critical current in long-length conductors remains challenging due to complex thermal, electromag netic, and mechanical interactions during continuous testing. This study reports the development of a continuous in-field magnetization testing system for position-dependent critical current measurement in HTS tapes at 20 K under 7.5 T fields applied normal to the tape plane, enabling identification of performance-limiting regions that could compromise magnet stability. Here, the system addresses two fundamental challenges inherent to cryogenic reel to-reel testing. First, thermal management requires continuous cooling of a moving conductor to 20 K, achieved through liquid nitrogen precooling combined with a 100 W@20 K Gifford McMahon cryocooler. Second, screening currents in high fields generate Lorentz forces that induce twisting, bowing, and potential delamination. To mitigate these risks, we propose mechanical reinforcement and active current density suppression strategies. Numerical simulations using the stream function formulation reveal four primary failure modes: frictional heating at guide interfaces, unstable equilibria causing deformation, transverse current-induced stresses at guide transitions, and unsupported forces in vertical spans. Our mitigation strategies include PTFE coated guides to minimize friction, spring-loaded stabilization mechanisms to maintain tape alignment, controlled pre-heating using the liquid nitrogen thermal jacket to suppress critical current at stress points, and optimized guide positioning to minimize force accumulation. The experimental system is nearing completion, with testing planned to commence within two months. Preliminary validation at 65 K under 0.5 T demonstrates strong correlation between simulation-predicted mechanical instabilities and observed critical current variations during conductor tran sitions through the measurement region. These findings establish a robust foundation for quality assurance protocols essential to next-generation superconducting magnet applications.

Chen, Siwei [Princeton Plasma Physics Laboratory (↗

NASA NTRS1971

Optimum impulsive midcourse guidance with control dependent errors.

The problem of determining the optimum guidance policy for an interplanetary spacecraft is treated as a stochastic optimal control problem. An algorithm for computing the optimum velocity correction and the optimum execution time (with allowance for correction-dependent errors) is derived in the case of a single midcourse correction. The performance index was chosen to be an upper bound for the probability that the mission fails, and it is defined as a function of the maximum allowable velocity correction and the maximum allowable deviation of the terminal state. Numerical results obtained for a Jupiter fly-by mission indicate that the execution errors have a significant influence on the performance index, but an acceptably small upper bound on the probability of mission failure can be obtained for sufficiently small execution errors.

Tapley, B. D.↗

NASA NTRS1991

Vibration suppression using a constrained rate-feedback-threshold control strategy

A finite time, minimum force rate-feedback-threshold controller is developed to bring a system with or without known external disturbances back into an 'allowable' state bound in finite time. The disturbances are assumed to be expandable in terms of Fourier series. The optimal control is defined by a two-point boundary value problem coupled to a set of definite integral constraints. Quasi-closed form solutions are derived which replace the solution of the two-point boundary value problem and definite integral constraints with the solution of algebraic equations and the calculation of matrix exponentials. Examples are provided which demonstrate the threshold control technique and compare the quasi-closed form solutions with numerical and MACSYMA generated exact solutions.

Zimmerman, D. C.↗

DOE OSTI2022

Optimal Control of Biomass Feedstock Processing System Under Uncertainty in Biomass Quality

Planning of biorefinery operations is complicated by the stochastic nature of physical and chemical characteristics of biomass feedstock, such as, moisture level and carbohydrate content. Biomass characteristics affect the performance of the equipment which feed the reactor and the efficiency of the conversion process in a biorefinery. We propose a stochastic optimization model to identify a blend of feedstocks, inventory levels, and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor while meeting the requirements of the biochemical conversion process. We propose a sample average approximation (SAA) of the model, and develop an efficient algorithm to solve the SAA model. A feedstock preprocessing process consists of two-stage grinding and pelleting is used to develop a case study. Extensive numerical analysis are conducted which lead to a number of observations. Our main observation is that sequencing bales based on moisture level and carbohydrate content leads to robust solutions that improve processing time and processing rate of the reactor. We provide a number of managerial insights that facilitate the implementation of the model proposed. Note to Practitioners—This paper is motivated by the challenges faced in the bioenergy industry. The focus of this paper is on plants which use the biochemical conversion process to generate liquid fuels. It has been observed that variations in biomass characteristics, such as moisture content, cause variations in feeding of the system which lead to under-utilization of equipment. A requirement of biochemical conversion process is to maintain the carbohydrate content of biomass processed by the reactor, larger than a threshold. We propose a model that identifies the inventory levels and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor. The goal is to improve equipment utilization while satisfying the requirements of the conversion process. The model is tested using real-life data. We found out that by sequencing bales based on moisture level and carbohydrate content, a plant can reduce variability in the system leading to improved system reliability, higher processing rates of the reactor, and higher throughput.

09 BIOMASS FUELS↗

DOE OSTI2020

Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming

In this report, we study the sensitivity of discrete-time dynamic programs with nonlinear dynamics and objective to perturbations in the initial conditions and reference parameters. Under uniform controllability and boundedness assumptions for the problem data, we prove that the directional derivative of the optimal state and control at time $k$, $x^*_k$, and $u^*_k$, with respect to the reference signal at time $i$, $d_i$, will have exponential decay in terms of $|k-i|$ with a decay rate $\rho$ independent of the temporal horizon length. The key technical step is to prove that a version of the convexification approach proposed by Verschueren et al. can be applied to the KKT conditions and results in a convex quadratic program with uniformly bounded data. In turn, Riccati techniques can be further employed to obtain the sensitivity result, borne from the observation that the directional derivatives are solutions of quadratic programs with structure similar to the KKT conditions themselves. We validate our findings with numerical experiments on a small nonlinear, nonconvex, dynamic program.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

A first-order Lyapunov robustness method for linear systems with uncertain parameters

A method for stability-robustness analysis based on a quadratic Liapunov function that varies linearly with uncertainty parameters is derived. Linear time-invariant systems with structured uncertainties are discussed. The Liapunov function is optimized numerically to maximize the robustness region in parameter space. Numerical results are given for four examples in which the first-order method is compared to previous Liapunov methods. While the zero-order method is slightly better than the first-order method for one example, the first-order method is clearly superior in the other three (more realistic) examples. The first-order method is especially superior for the active control of flexible structures, where robustness with respect to (1) unmodeled coupling between modeled modes and (2) unmodeled modes is important. For such applications, the first-order method is much better at detecting the increased robustness associated with increased separation between frequencies.

Leal, M. A.↗

NASA NTRS2004

OTIS 3.2 Software Released

Trajectory, mission, and vehicle engineers concern themselves with finding the best way for an object to get from one place to another. These engineers rely upon special software to assist them in this. For a number of years, many engineers have used the OTIS program for this assistance. With OTIS, an engineer can fully optimize trajectories for airplanes, launch vehicles like the space shuttle, interplanetary spacecraft, and orbital transfer vehicles. OTIS provides four modes of operation, with each mode providing successively stronger optimization capability. The most powerful mode uses a mathematical method called implicit integration to solve what engineers and mathematicians call the optimal control problem. OTIS 3.2, which was developed at the NASA Glenn Research Center, is the latest release of this industry workhorse and features new capabilities for parameter optimization and mission design. OTIS stands for Optimal Control by Implicit Simulation, and it is implicit integration that makes OTIS so powerful at solving trajectory optimization problems. Why is this so important? The optimization process not only determines how to get from point A to point B, but it can also determine how to do this with the least amount of propellant, with the lightest starting weight, or in the fastest time possible while avoiding certain obstacles along the way. There are numerous conditions that engineers can use to define optimal, or best. OTIS provides a framework for defining the starting and ending points of the trajectory (point A and point B), the constraints on the trajectory (requirements like "avoid these regions where obstacles occur"), and what is being optimized (e.g., minimize propellant). The implicit integration method can find solutions to very complicated problems when there is not a lot of information available about what the optimal trajectory might be. The method was first developed for solving two-point boundary value problems and was adapted for use in OTIS. Implicit integration usually allows OTIS to find solutions to problems much faster than programs that use explicit integration and parametric methods. Consequently, OTIS is best suited to solving very complicated and highly constrained problems.

Riehl, John P.↗

NASA NTRSDate not supplied

Study of a Plug Nozzle for Supersonic Aircraft Concepts

Nozzles with external plugs are candidates for the exhaust system of supersonic aircraft concepts in an ongoing research effort at NASA. As part of that effort a fundamental study is being conducted at NASA Glenn Research Center (GRC). Experimental and limited numerical simulation results from this study, for a plug nozzle with a convergent nozzle (cowl),have been reported in recent publications[1,2]. Conventional method-of-characteristics (MoC) design for the plug requires that the flow is choked at the nozzle exit. This is why a sharp convergence of the cowl is invoked in such a design in most previous studies [3-5], leading to the earlier choice of the convergent cowl. Such a nozzle, however, is not suitable for supersonic flights because of large boat tail drag suffered by its outer surface. The boat tail drag consideration dictates that the cowl be more or less cylindrical in shape. While various other shapes have been studied in the past [6], essentially a cylindrical shape is adopted in the larger research program at NASA. The cylindrical shape has certain advantages. With the plug crown located somewhat inside the nozzle, the flow experiences convergence and divergence as with a C-D nozzle. By translating the plug, different throat-to-exit area ratio could be achieved to obtain fully expanded condition at different values of NPR. This offers a relatively easy active control strategy for the nozzle geometry throughout the flight regime from landing and takeoff (LTO) to cruise conditions. A plug nozzle model mimicking the geometry being considered in the NASA program, i.e., having a cylindrical exit, have been fabricated recently for continued fundamental studies. Some of the plugs used with the earlier convergent cowl [1] are readily adopted to this model. In addition, a few other plugs have been obtained following a numerical optimization study [7]. The various configurations are to be investigated for thrust, noise and flow fields, with complementing numerical simulations. Thrust data for a variety of configurations as well as limited noise data are in hand. Further explorations including schlieren visualization are to be conducted in the near future. The proposed paper is to summarize all these results. In the following, a few key results obtained so far are described.

jets↗

NASA NTRS1993

Optimal feedback control of turbulent channel flow

Feedback control equations were developed and tested for computing wall normal control velocities to control turbulent flow in a channel with the objective of reducing drag. The technique used is the minimization of a 'cost functional' which is constructed to represent some balance of the drag integrated over the wall and the net control effort. A distribution of wall velocities is found which minimizes this cost functional some time shortly in the future based on current observations of the flow near the wall. Preliminary direct numerical simulations of the scheme applied to turbulent channel flow indicates it provides approximately 17 percent drag reduction. The mechanism apparent when the scheme is applied to a simplified flow situation is also discussed.

Bewley, Thomas↗

DOE OSTI2021

Multi-objective Bayesian optimization of ferroelectric materials with interfacial control for memory and energy storage applications

Optimization of materials’ performance for specific applications often requires balancing multiple aspects of materials’ functionality. Even for the cases where a generative physical model of material behavior is known and reliable, this often requires search over multidimensional function space to identify low-dimensional manifold corresponding to the required Pareto front. In this work, we introduce the multi-objective Bayesian optimization (MOBO) workflow for the ferroelectric/antiferroelectric performance optimization for memory and energy storage applications based on the numerical solution of the Ginzburg–Landau equation with electrochemical or semiconducting boundary conditions. MOBO is a low computational cost optimization tool for expensive multi-objective functions, where we update posterior surrogate Gaussian process models from prior evaluations and then select future evaluations from maximizing an acquisition function. Using the parameters for a prototype bulk antiferroelectric (PbZrO 3 ), we first develop a physics-driven decision tree of target functions from the loop structures. We further develop a physics-driven MOBO architecture to explore multidimensional parameter space and build Pareto-frontiers by maximizing two target functions jointly—energy storage and loss. This approach allows for rapid initial materials and device parameter selection for a given application and can be further expanded toward the active experiment setting. The associated notebooks provide both the tutorial on MOBO and allow us to reproduce the reported analyses and apply them to other systems (https://github.com/arpanbiswas52/MOBO_AFI_Supplements).

36 MATERIALS SCIENCE↗

NASA NTRS2017

A PCR Based Microbial Monitoring Alternative Method of Detection and Identification of Microbes Aboard ISS

Previous research has shown that microorganisms and potential human pathogens have been detected on the International Space Station (ISS) with additional introduction of new microflora occurring with every exchange of crew or addition of equipment and supplies. These microbes are readily transferred between crew and subsystems (i.e. ECLSS, environmental control and life support systems). As this can be detrimental to astronaut health and optimal performance of ISS systems, monitoring of systems such as ECLSS to include identification of microbial contaminants could prevent adverse effects on human health and life support systems. Current monitoring on ISS is laborious and utilizes culture based methods followed by sample return to Earth for complete analysis. Future, long-distance spaceflight missions will require real-time monitoring capabilities that enable efficient and rapid assessments of the microbial environment allowing for expedited decisions and more targeted response to cope with anomalies. Polymerase chain reaction (PCR), a molecular microbial monitoring method was chosen and numerous PCR instruments investigated for their potential to perform in microgravity conditions. Using ISS as a test bed for PCR verification in microgravity will enable NASA to assess whether molecular based microbiological sensors may be components of reliable, closed-loop life support and habitation systems in spacecraft, enhancing infrastructure capabilities through increased efficiency, reliability, and time savings by enabling sample analysis on orbit. NASA selected the Water Monitoring Suite as one of the rapid spaceflight hardware demonstration activities utilizing a streamlined process to minimize the time required to fly experimental flight hardware. The RAZOR EX (BioFire Defense, Salt Lake City, UT) system was part of the water monitoring suite and is a commercial off-the-shelf (COTS) real-time PCR instrument designed for field work. The RAZOR EX was originally designed for Department of Defense (DoD) under a small business innovative research (SBIR) grant and is ruggedized, compact and provides a rapid, sample to answer in less than an hour. PCR assays using a fluorescent probe were optimized and spiked with known concentrations of DNA (Pseudomonas aeruginosa) ranging from 0.002 to 20 ng. PCR reagents were lyophilized and configured in customized pouches and tested for flight readiness. Three types of water were used to rehydrate the reagents and demonstrate the fidelity of the PCR reaction in microgravity. Molecular grade deionized water served as a control while filtered and unfiltered ISS potable water served to test for chemical or biological inhibitors. All three types were compared to parallel ground test results. Nine tests were run on ISS (3 of each water type) and the critical threshold cycle (Ct) was compared to parallel ground tests completed at Kennedy Space Center, FL and Johnson Space Center, TX. All concentrations of Pseudomonas aeruginosa DNA were detected. A comparison of the Ct produced in real time PCR indicated similarity between flight and ground samples. There appeared to be no significant difference between flight or ground PCR reactions or between any of the three water types. This testing demonstrated the ability to perform molecular testing during spaceflight operations with similar sensitivity. It will allow for future ground development of molecular protocols and minimize the need for spaceflight testing. Future testing will include development of additional targets including environmental and health related organisms.

Christina Khodadad↗

DOE OSTI2023

Efficient Optimization of Energy Recovery From Geothermal Reservoirs With Recurrent Neural Network Predictive Models

Improving the long-term energy production performance of geothermal reservoirs can be accomplished by optimizing field development and management plans. Reliable prediction models, however, are needed to evaluate and optimize the performance of the underlying reservoirs under various operation and development strategies. In traditional frameworks, physics-based simulation models are used to predict the energy production performance of geothermal reservoirs. However, detailed simulation models are not trivial to construct, require a reliable description of the reservoir conditions and properties, and entail high computational complexity. Data-driven predictive models can offer an efficient alternative for use in optimization workflows. This paper presents an optimization framework for net power generation in geothermal reservoirs using a variant of the recurrent neural network (RNN) as a data-driven predictive model. The RNN architecture is developed and trained to replace the simulation model for computationally efficient prediction of the objective function and its gradients with respect to the well control variables. The net power generation performance of the field is optimized by automatically adjusting the mass flow rate of production and injection wells over 12 years, using a gradient-based local search algorithm. Two field-scale examples are presented to investigate the performance of the developed data-driven prediction and optimization framework. Furthermore, the prediction and optimization results from the RNN model are evaluated through comparison with the results obtained by using a numerical simulation model of a real geothermal reservoir.

15 GEOTHERMAL ENERGY↗