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Results for “Inverse Optimization”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The Effects of Extravehicular Activity (EVA) Glove Pressure on Tactility

The purpose of the current study was to quantify finger tactility, while wearing a Phase VI Extravehicular Activity (EVA) glove. Subjects were fully suited in an Extravehicular Mobility Unit (EMU) suit. Data was collected under three conditions: bare-handed, gloved at 0 psi, and gloved at 4.3 psi. In order to test tactility, a series of 30 tactile stimuli (bumps) were created that varied in both height and width. With the hand obscured, subjects applied pressure to each bump until detected tactilely. The amount of force needed to detect each bump was recorded using load cells located under a force-plate. The amount of force needed to detect a bump was positively related to width, but inversely related to height. In addition, as the psi of the glove increased, more force was needed to detect the bump. In terms of application, it was possible to determine the optimal width and height a bump needs to be for a specific amount of force applied for tactility.

Thompson, Shelby↗
NASA NTRS1989

Real-time neuromorphic algorithms for inverse kinematics of redundant manipulators

The paper presents an efficient neuromorphic formulation to accurately solve the inverse kinematics problem for redundant manipulators. The approach involves a dynamical learning procedure based on a novel formalism in neural network theory: the concept of 'terminal' attractors. Topographically mapped terminal attractors are used to define a neural network whose synaptic elements can rapidly encapture the inverse kinematics transformations, and, subsequently generalize to compute joint-space coordinates required to achieve arbitrary end-effector configurations. Unlike prior neuromorphic implementations, this technique can also systematically exploit redundancy to optimize kinematic criteria, e.g., torque optimization. Simulations on 3-DOF and 7-DOF redundant manipulators, are used to validate the theoretical framework and illustrate its computational efficacy.

Barhen, Jacob↗
NASA NTRS1990

Plasma puff initiation of high Coulomb transfer switches

The plasma-puff triggering mechanism based on a hypocycloidal pinch geometry was investigated to determine the optimal operating conditions for the azimuthally uniform surface flashover which initiates plasma-puff under wide range of fill gas pressure of Ar, He and N2. The optimal fill gas pressure for the azimuthally uniform plasma-puff was about 120 mTorr and 450 Torr for He and N2, and between 120 mTorr and 5 Torr for Ar. The inverse pinch switch was triggered with the plasma-puff and the switching capability under various electrical parameters and working gas pressures of Ar, He and N2 was determined. It was also shown that the azimuthally uniform switching discharges were dependent on the type of fill gas and its fill pressure. A new concept of plasma-focus driven plasma-puff was also discussed in comparison with the hypocycloidal pinch plasma-puff triggering. The main discharge of inverse pinch switch with plasma-focus driven plasma-puff trigger is found to be more azimuthally uniform than that with hypocycloidal pinch plasma-puff trigger in a gas pressure region between 80 mTorr and 1 Torr.

Venable, D. D.↗
DOE OSTI2025

Improved Bayesian regularization of inverse problems in vibrations and acoustics using noise-only measurements

Here, this paper studies Tikhonov regularization (ridge regression) parameter selection for problems in vibrations and acoustics. The selection method is based on a popular Bayesian method, but it incorporates measurements of sensor noise. The regularization parameter is closely related to the ratio of system input energy to noise energy, so noise measurements inform the inference procedure and improve parameter identification. In cases where standard Bayesian regularization identifies zero as the optimal regularization parameter, noise measurements guarantee a unique nonzero optimum. Sufficient theoretical criteria are developed for this guarantee. The method is verified in even-determined and under-determined configurations in an acoustic source localization simulation and a vibration load identification experiment. It is shown to yield significant improvements over existing empirical Bayesian regularization. Improvements are larger in the even-determined case and smaller in the under-determined case, wherein the inverse solution is less sensitive to the regularization parameter.

42 ENGINEERING↗
DOE OSTI2026

Machine learning inversion of interatomic force constants from single-crystal inelastic neutron scattering

Atomic vibrations govern many macroscopic properties of materials, but experiments to comprehensively probe them remain challenging. Inelastic neutron scattering (INS) is a powerful technique to map phonon dispersions in crystals, especially when leveraging modern time-of-flight (ToF) spectrometers with large detectors. However, efficiently and robustly extracting interatomic force constants (FCs) parameterizing phonon dynamics from experimental spectra remains a bottleneck due to the complexity and high dimensionality of ToF INS datasets. Here, we present a machine learning approach for the direct inversion of FCs from single-crystal INS measurements. The framework leverages synthetic training data generated using universal machine-learned force fields and an efficient physics-based forward model. We benchmark two neural architectures–one emphasizing structured latent representation learning and the other direct, supervised spectral regression–across simulated datasets for two materials under idealized and noisy conditions. The latent-representation model is subsequently applied to experimental single-crystal INS data on germanium. The model is shown to reproduce FCs derived from both first-principles simulations and from iterative optimization, and furthermore achieves reliable inference even from sparse, single-orientation measurements representing short data acquisitions. Analysis of the learned latent space reveals semantically continuous and physically interpretable encodings that support strong cross-domain generalization. By bridging theoretical and experimental domains, we establish a path toward rapid inversion of experimental spectra and data-driven interpretation of temperature-dependent lattice dynamics.

42 ENGINEERING↗
DOE OSTI2024

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗
DOE OSTI2024

Co-optimization of nuclear reactor flexible power operation and maintenance scheduling

As flexible power operation of nuclear power plants becomes more attractive due to the reduction in fossil-fueled dispatchable generation on energy grids, finding optimal power production strategies that balance revenue generation with operational concerns becomes more complex. This article presents a general framework to aid operators in designing economically optimal long term dispatch strategies for nuclear power plants. The principal novelty is the linking of estimated system remaining useable life (RUL) to strategic operational decisions. It is shown that, depending on the relationship between the fixed costs from maintenance and the associated lost revenue from an outage, it can be economically optimal in the long term to delay a maintenance outage and not perform this alongside refueling. For a given relationship between power ramping and degradation, optimal strategies were found that discouraged load following in some situations while minimizing unnecessary maintenance. It is shown that heavy load following can cause maintenance and refueling outages to diverge due to their inverse relationships with respect to load following, potentially leading to a significant loss in capacity factor. As a result, this general framework can be applied to specific reactor dispatch allowing operators to adapt operational strategies as future grid conditions change.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Engineering Antifreeze Proteins to Optimally Resist Engulfment by Ice

Antifreeze proteins (AFPs) facilitate the survival of organisms in cold climates by inhibiting the growth and/or recrystallization of ice. To function, AFPs must first bind to ice crystals; bound AFPs must then resist engulfment by using their nonbinding side (NBS) to pin the ice–water interface. Here, we seek to understand how the molecular characteristics of an NBS, such as its ice-phobicity or shape, influence its ability to resist engulfment. By characterizing the free energy barriers that impede the engulfment of model AFPs, we find that the critical supercooling ΔT*, above which an AFP is engulfed, is dictated by an optimal pinning site on the NBS. We further find that the optimal pinning site is determined by an interplay between the contact line perimeter P and a pinning efficiency η, with ΔT* ∝ ηP at the optimal pinning site. For a hemispherical AFP, which displays progressively inward tapering, we find that η increases during engulfment, whereas P decreases; conversely, an NBS with outward tapering can achieve high P, but it suffers from low η. Because the product of η and P determines ΔT*, the inverse correlation between them limits ΔT. To circumvent such limiting behavior, we propose an NBS shape with an outward bulge; by initially tapering outward, a bulged NBS permits higher P, and by subsequently tapering inward, it promotes high η as well. Importantly, we find that ΔT* is enhanced by more than a factor of 2 with an outward bulge of only 1 nm. We also find that the more ice-phobic an NBS is, the more efficiently it pins the ice–water interface, resulting in a higher ΔT. Furthermore, our findings shed light on how the NBS molecular characteristics influence ΔT* and suggest strategies for engineering the NBS to optimally resist engulfment by ice.

Antifreeze↗
DOE OSTI2026

High-Efficiency Solar-To-Fuel Photoelectrochemistry in Disordered Photonic Glass Electrodes (Final Technical Report)

This project investigated how photonic glass (PG) photoelectrodes—disordered arrangements of dielectric scatterers—can serve as scalable, tunable platforms for light trapping in photoelectrochemical (PEC) solar-to-fuel systems. By leveraging disorder-driven optical phenomena such as multiple scattering resonances and light localization, PG structures offer an alternative to conventional photonic crystals and inverse opals that require high structural precision. The scientific goals were to twofold: (1) develop approaches to predictive models for high performance PG electrodes based on light absorption simulations, and (2) fabricate, characterize, and optimize PG-based photoelectrodes for solar-to-hydrogen and solar-to-fuel photoelectrochemical applications. To overcome the complexity of ensemble optical simulations for disordered materials, the researchers developed a machine-learning-accelerated emulation of all configurations in the design space. With this approach, PG photoelectrodes based on a TiO2 semiconductor were designed to enhance PEC currents of up to one hundred times higher than the equivalent ultra-thin film photoanodes and several times higher than the equivalent photonic crystal. The research also explored integrated systems for electrochemical hydrogen production based on replacing water oxidation with the specific glycerol oxidation electrocatalysis. Overall, the project outlined an approach to a simple-to-fabricate photoelectrode system to drive photoelectrochemical reactions relevant to solar photochemical energy conversion.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Feasibility Study of a Multi Tilt-rotor Aircraft as the Artemis Lunar Training Vehicle

The Lunar Landing Research Vehicles (LLRVs) and the Lunar Landing Training Vehicles (LLTVs) provided astronaut candidates for the Apollo program with essential experience and confidence required to complete the missions, and contributed to six successful manned landings on the moon. The primary challenge in terrestrial training was being able to replicate the ratio of bank angle to linear acceleration that a pilot would experience in lunar gravity. Presently, as the Artemis program seeks to return humans to the Moon by 2025, engineers are evaluating suitable platforms to serve as an In-Flight Trainer (IFT) or Artemis Lunar Training Vehicle (ALTV) for astronauts training in the task of manual landing. The program is investigating the viability of current technology in the field of electric vertical takeoff and landing (eVTOL) vehicles and is evaluating using a multi tilt-rotor aircraft platform as a candidate platform for a preliminary ALTV. The tilt-rotor capability enables the vehicle attitude to be decoupled from its flight path, which is a crucial requirement in realistically simulating lunar gravity on Earth. Other key considerations include compensating for a lack of aerodynamic forces while flying through the atmosphere of Earth, as well as the ability to simulate the dynamics of multiple different lander designs for the Human Landing System (HLS) program. This paper details the feasibility study and presents a preliminary flight control architecture for an IFT based on a notional multi tilt-rotor platform. The modeling-following control law, based on nonlinear dynamic inversion (NDI), removes the need for gain scheduling because the vehicle operates across a wide range of flight conditions. The inner-loop dynamic control allocation strategy consists of a static portion that is optimized offline for trim while compensating for the difference in gravity and a dynamic portion that is computed in real time. The reference model consists of the full closed-loop dynamics of a generic HLS design. The modularity of the flight control architecture enables evaluation of multiple HLS concepts with minimal modifications to the control law. Simulation results of the multi tilt-rotor configuration following the final portion of the Apollo 11 descent trajectory are shown.

Jing Pei↗
NASA NTRS1991

Recent progress in inverse methods in France

Given the current level of jet engine performance, improvement of the various turbomachinery components requires the use of advanced methods in aerodynamics, heat transfer, and aeromechanics. In particular, successful blade design can only be achieved via numerical design methods which make it possible to reach optimized solutions in a much shorter time than ever before. Two design methods which are currently being used throughout the French turbomachinery industry to obtain optimized blade geometries are presented. Examples are presented for compressor and turbine applications. The status of these methods as far as improvement and extension to new fields of applications is also reported.

Bry, Pierre-Francois↗
DOE OSTI2026

Spatiotemporal control of laser intensity using differentiable programming

Optical techniques for spatiotemporal control can produce laser pulses with custom amplitude, phase, or polarization structure. In nonlinear optics and plasma physics, the use of structured pulses typically follows a forward design approach, in which the efficacy of a known structure is analyzed for a particular application. Inverse approaches, in contrast, enable the discovery of new structures with the potential for superior performance. Here, an implementation of the unidirectional pulse propagation equation that supports automatic differentiation is combined with gradient-based optimization to design structured pulses with features that are advantageous for a range of nonlinear optical and plasma-based applications: (1) a longitudinally uniform intensity over an extended region, (2) a superluminal intensity peak that travels many Rayleigh ranges with constant duration, spot size, and amplitude, and (3) a laser pulse that ionizes a gas to form a uniform column of plasma. In the final case, optimizing the full spatiotemporal structure improves the performance by a factor of 15 compared to optimizing only spatial or only temporal structure, highlighting the advantage of spatiotemporal control.

automatic differentiation↗
NASA NTRS1981

Iterative optical vector-matrix processors (survey of selected achievable operations)

An iterative optical vector-matrix multiplier with a microprocessor-controlled feedback loop capable of performing a wealth of diverse operations was described. A survey and description of many of its operations demonstrates the versatility and flexibility of this class of optical processor and its use in diverse applications. General operations described include: linear difference and differential equations, linear algebraic equations, matrix equations, matrix inversion, nonlinear matrix equations, deconvolution and eigenvalue and eigenvector computations. Engineering applications being addressed for these different operations and for the IOP are: adaptive phased-array radar, time-dependent system modeling, deconvolution and optimal control.

Casasent, D.↗
NASA NTRS1998

A Framework for a Supervisory Expert System for Robotic Manipulators with Joint-Position Limits and Joint-Rate Limits

This report addresses the problem of path planning and control of robotic manipulators which have joint-position limits and joint-rate limits. The manipulators move autonomously and carry out variable tasks in a dynamic, unstructured and cluttered environment. The issue considered is whether the robotic manipulator can achieve all its tasks, and if it cannot, the objective is to identify the closest achievable goal. This problem is formalized and systematically solved for generic manipulators by using inverse kinematics and forward kinematics. Inverse kinematics are employed to define the subspace, workspace and constrained workspace, which are then used to identify when a task is not achievable. The closest achievable goal is obtained by determining weights for an optimal control redistribution scheme. These weights are quantified by using forward kinematics. Conditions leading to joint rate limits are identified, in particular it is established that all generic manipulators have singularities at the boundary of their workspace, while some have loci of singularities inside their workspace. Once the manipulator singularity is identified the command redistribution scheme is used to compute the closest achievable Cartesian velocities. Two examples are used to illustrate the use of the algorithm: A three link planar manipulator and the Unimation Puma 560. Implementation of the derived algorithm is effected by using a supervisory expert system to check whether the desired goal lies in the constrained workspace and if not, to evoke the redistribution scheme which determines the constraint relaxation between end effector position and orientation, and then computes optimal gains.

Mutambara, Arthur G. O.↗
DOE OSTI2024

Analysis and Optimization of the Recompression Cycle with High Temperature Recuperator Bypass for Concentrating Solar Power Applications

This work analyzes the sCO2 recompression with high temperature recuperator (HTR) bypass power cycle for use in concentrating solar power (CSP) systems. CSP operation differs from other thermal power plants in that CSP must balance between maximizing the heat transfer fluid (HTF) temperature difference and maximizing the cycle thermal efficiency, which typically are inversely related. Large HTF temperature differences reduce the size and cost of thermal energy storage (TES), improve the solar receiver efficiency, and require lower mass flow rates that reduce pumping power required to elevate the HTF to the receiver. The recompression cycle with HTR bypass potentially offers improved thermal efficiency with larger HTF temperature differences as compared to the recompression cycle, and it has fewer turbomachinery components than the partial cooling cycle. The recompression with HTR bypass cycle adds a second lower temperature primary heat exchanger which transfers heat from the HTF to the fraction of sCO2 flow that bypasses the HTR. We developed a model to compare the recompression with HTR bypass cycle to the recompression and partial cooling cycles. A sweep of design parameters including bypass fraction, recompression fraction, recuperator conductance, and pressure ratio is used to form a pareto-optimal front with the cycle thermal efficiency and HTF temperature difference as objectives. An optimization routine has also been developed to find optimal design point parameters for a target HTF temperature difference. The performance of the recompression with HTR bypass cycle is compared with recompression and partial cooling cycles.

concentrating solar power↗
NASA NTRS1985

Optimal Sensor Locations for Structural Identification

The optimum sensor location problem, OSLP, may be thought of in terms of the set of systems, S, the class of input time functions, I, and the identification algorithm (estimator) used, E. Thus, for a given time history of input, the technique of determining the OSL requires, in general, the solution of the optimization and the identification problems simultaneously. A technique which uncouples the two problems is introduced. This is done by means of the concept of an efficient estimator for which the covariance of the parameter estimates is inversely proportional to the Fisher Information Matrix.

Udwadia, F. E.↗
NASA NTRS1986

A methodology for designing robust multivariable nonlinear control systems

A new methodology is described for the design of nonlinear dynamic controllers for nonlinear multivariable systems providing guarantees of closed-loop stability, performance, and robustness. The methodology is an extension of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery (LQG/LTR) methodology for linear systems, thus hinging upon the idea of constructing an approximate inverse operator for the plant. A major feature of the methodology is a unification of both the state-space and input-output formulations. In addition, new results on stability theory, nonlinear state estimation, and optimal nonlinear regulator theory are presented, including the guaranteed global properties of the extended Kalman filter and optimal nonlinear regulators.

Grunberg, D. B.↗
NASA NTRS1988

Viscous induced drag

A fundamentally new approach to the aircraft minimum induced drag problem is presented. The method, a 'viscous lifting line', is based on the minimum entropy production principle and does not require the planar wake assumption. An approximate, closed form solution is obtained and compared with several classical results. In addition, the problem of optimizing in-plane wing sweep with constant wing root bending moment is considered. Like the classical lifting line theory, this theory predicts that induced drag is proportional to the square of the lift coefficient and inversely proportional to the wing aspect ratio. Unlike the classical theory, it predicts that in-plane wing sweep may significantly reduce induced drag, that induced drag is Reynolds number dependent, and that the optimum spanwise circulation distribution is non-elliptic.

Greene, George C.↗