Search NASA⌕ Search

SEARCH · Search NASA

Results for “derivative free 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

Microbial production of fuels, commodity chemicals, and materials from sustainable sources of carbon and energy

Anthropogenic carbon emissions are driving rapid changes to the earth's climate, disrupting whole ecosystems and endangering the stability of human society. Innovations in engineered microbial fermentation enable the fossil resource-free production of fuels, commodity chemicals, and materials, thereby reducing the carbon emissions associated with these products. Microorganisms have been engineered to catabolize sustainable sources of carbon and energy (i.e., plant biomass, plastic waste, and one-carbon feedstocks) and biosynthesize carbon-neutral or carbon-negative products. These engineering efforts exploit and optimize natural biological pathways or generate unnatural pathways which can biosynthesize chemicals that have not yet been accessed using synthetic chemistry. Further, recent advances in microbial fermentation seek not only to maximize the titer, rate, and yield of desired products, but also to tailor microbial catabolism to utilize inexpensive feedstocks. Ultimately, these advances aim to lower the cost of bioproduction so that microorganism-derived chemicals can be economically competitive with fossil-derived chemicals.

09 BIOMASS FUELS↗

Engineering acid-base active sites on an N-doped biochar catalyst for microwave-assisted biodiesel production from waste cooking oil

Acid-base bifunctional catalysts play a crucial role in converting high-free fatty acid (FFA) feedstocks into biodiesel by enabling the simultaneous esterification and transesterification of triglycerides in a single step, thereby minimizing saponification and streamlining the process. In this study, we report the design and development of a novel N-doped acid-base bifunctional biochar catalyst synthesized from renewable biomass precursors- glucose and chitosan. The catalyst’s acidic sites were introduced via surface functionalization with o-sulfobenzoic acid cyclic anhydride, grafting -SO₃H groups onto the carbon framework, while basic sites were generated from amine functionalities (-NH) derived from chitosan, yielding a robust and truly bifunctional surface. The catalyst was characterized and used for the microwave-assisted transesterification of waste cooking oil, and process optimization using response surface methodology (RSM-CCD) yielding a maximum biodiesel yield of 98.8 ± 0.4% under optimal conditions (methanol-to-oil molar ratio 20:1, catalyst loading 5.7 wt%, temperature 99 °C, and reaction time 46.6 min). The catalyst demonstrated good stability, maintaining a yield of 92.2 ± 0.4% after eight reuse cycles. A Life Cycle Assessment (LCA) conducted for 1 kg of biodiesel production revealed a global warming potential of 0.85 kg CO 2 eq and human toxicity potential of 1.59 kg 1,4-DB eq, with the largest environmental contributions arising from catalyst preparation and reuse. In conclusion, this work highlights a green and circular approach to biodiesel production, combining renewable catalyst design, waste feedstock utilization, and quantitative sustainability assessment to guide future developments in sustainable catalysis and biofuel engineering.

Bifunctional catalyst↗

Understanding the Influence of Water-Soluble Compounds from Unpretreated Corn Stover Pellets on Enzymatic Hydrolysis of Cellulose

Aqueous extractives are minor and non-structural compounds in biomass that can be extracted using solvents, while contributing significantly to lignocellulose characteristics. Yet their roles in enzyme-mediated processing of lignocellulosic biomass remain elusive. Here, we examine the composition and features of extractives derived from untreated pelleted corn stover as well as their effects on enzymatic hydrolysis. Unlike the observations described in previous reports, we find that water extractable material improves the enzymatic hydrolysis of extractive-free stover by 67% with a glucose yield increase from 12% to 20% with 6 FPU cellulase per g glucan, whereas the enzyme activities are diminished when using microcrystalline cellulose as a substrate. The different behavior of corn stover and microcrystalline cellulose is likely attributed to the presence of lignin, which may interact with inhibitory compounds such as phenolics, mitigating the detrimental impacts of soluble inhibitors or insoluble lignin or both. These findings advance our fundamental understanding of the intrinsic behavior of extractives and help to optimize the schemes for efficient and cost-competitive enzymatic conversion of lignocellulose.

09 BIOMASS FUELS↗

Benchmarking Adaptive Variational Quantum Eigensolvers

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is indirectly assessed by the value of the associated energy. Novel adaptive derivative-assembled pseudo-trotter (ADAPT) ansatz approaches and recent formal advances now establish a clear connection between the theory of quantum chemistry and the quantum state ansatz used to solve the electronic structure problem. Here we benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves for a few selected diatomic molecules, namely H 2 , NaH, and KH. Using numerical simulation, we find both methods provide good estimates of the energy and ground state, but only ADAPT-VQE proves to be robust to particularities in optimization methods. Another relevant finding is that gradient-based optimization is overall more economical and delivers superior performance than analogous simulations carried out with gradient-free optimizers. The results also identify small errors in the prepared state fidelity which show an increasing trend with molecular size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure, Morphology, and Photovoltaic Implications of Halide Alloying in Lead-Free Cs 3 Sb 2 Cl x I 9-x 2D-Layered Perovskites

Compositional tuning has been a major driving force behind the excellent optoelectronic properties observed in typical Pb-based perovskites. For lead-free perovskite derivatives, a challenge to understanding the connection between compositional tuning and intrinsic optoelectronic properties, hence a barrier towards boosting their performance, comes from the fact that multiple crystalline substructures can form based on composition, film processing, or both. Especially with lower dimensional (0D, 1D, 2D) substructures, the particular polymorph present in the film can be a greater determinant of optoelectronic properties than the composition itself. Herein, we report a simple method to alloy the halide site in all-inorganic lead-free Cs 3 Sb 2 I 9 films while maintaining a consistent 2D-layered substructure, as a means to independently study the photovoltaic implications of halide substitution. We use a broad suite of spectroscopy and device measurements to identify an optimal stoichiometric substitution of chloride for iodide (~ 8 mol%, measured) that balances both intrinsic and bulk optoelectronic properties to achieve a top power conversion efficiency of 2.2%. This work underscores the importance of controlling substructure while investigating the impacts of compositional tuning for the development of lead-free perovskites, and more broadly validates the approach towards realizing lead-free alternative perovskite solar technologies.

14 SOLAR ENERGY↗

GVIPS Models and Software

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Arnold, Steven M.↗

Cell-free Scaled Production and Adjuvant Addition to a Recombinant Major Outer Membrane Protein from Chlamydia muridarum for Vaccine Development

Subunit vaccines offer advantages over more traditional inactivated or attenuated whole-cell-derived vaccines in safety, stability, and standard manufacturing. To achieve an effective protein-based subunit vaccine, the protein antigen often needs to adopt a native-like conformation. This is particularly important for pathogensurface antigens that are membrane-bound proteins. Cell-free methods have been successfully used to produce correctly folded functional membrane protein through the co-translation of nanolipoprotein particles (NLPs), commonly known as nanodiscs. This strategy can be used to produce subunit vaccines consisting of membrane proteins in a lipid-bound environment. However, cell-free protein production is often limited to small scale (<1 mL). The amount of protein produced in small-scale production runs is usually sufficient for biochemical and biophysical studies. However, the cell-free process needs to be scaled up, optimized, and carefully tested to obtain enough protein for vaccine studies in animal models. Other processes involved in vaccine production, such as purification, adjuvant addition, and lyophilization, need to be optimized in parallel. This paper reports the development of a scaled-up protocol to express, purify, and formulate a membrane-bound protein subunit vaccine

59 BASIC BIOLOGICAL SCIENCES↗

A capacitive accelerometer suitable for telemetry

The design and development of a miniature 0.635 cm (0.25 in.) diameter capacitive accelerometer for use in free flight wind tunnel telemetry are presented. Instruments with full scale ranges from + or - 1 to + or - 200 g were constructed, calibrated, and used in several wind tunnel telemetry projects. Flat, high frequency response from 0 to 1000 Hz or more was obtained by employing the inherent damping and stiffness in the air film surrounding the diaphragm-type spring that supports the inertial mass of the accelerometer. Design features to achieve minimum off-axis sensitivity and temperature stability are discussed, and the design requirements for use of the transducer with telemetry systems are derived. A transducer capacitance change of 0.16 pF full scale gave excellent resolution and provided a frequency deviation of 0.75 MHz for a 100 MHz FM oscillator. Although the present design of the capacitive accelerometer was optimized by using units of 0.635 cm diameter, construction of experimental accelerometers as small as 0.36 cm (0.14 in.) diameter has demonstrated the feasibility of further miniaturization.

Coon, G. W.↗

Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees

We present differentiable predictive control (DPC), a method for offline learning of constrained neural control policies for nonlinear dynamical systems with performance guarantees. We show that the sensitivities of the parametric optimal control problem can be used to obtain direct policy gradients. Specifically, we employ automatic differentiation (AD) to efficiently compute the sensitivities of the model predictive control (MPC) objective function and constraints penalties. To guarantee safety upon deployment, we derive probabilistic guarantees on closed-loop stability and constraint satisfaction based on indicator functions and Hoeffding’s inequality. We empirically demonstrate that the proposed method can learn neural control policies for various parametric optimal control tasks. In particular, we show that the proposed DPC method can stabilize systems with unstable dynamics, track time-varying references, and satisfy nonlinear state and input constraints. Our DPC method has practical time savings compared to alternative approaches for fast and memory-efficient controller design. Specifically, DPC does not depend on a supervisory controller as opposed to approximate MPC based on imitation learning. We demonstrate that, without losing performance, DPC is scalable with greatly reduced demands on memory and computation compared to implicit and explicit MPC while being more sample efficient than model-free reinforcement learning (RL) algorithms.

97 MATHEMATICS AND COMPUTING↗

Electron Affinity and Electronic Structure of Hexafluoroacetone (HFA) Revealed by Photodetaching the [HFA] •– Radical Anion

A great deal of effort has been focused on developing a metal-free catalytic system for epoxidation of unreactive alkenes. Fluoroketones are thought as remarkably promising catalysts for epoxidation reactions. The combination of fluorinated alcohols and catalytic amounts of hexafluoroacetone (HFA) gives a versatile and effective medium for epoxidation of various olefins with hydrogen peroxide. However, the fundamental physicochemical properties of HFA remained largely unclear, although they were very important to understand the related interactions. Here, in this study, we performed a joint study on the electron affinity and electronic structure of HFA employing negative ion photoelectron (NIPE) spectroscopy and quantum chemistry calculations. Two distinct bands with complicated vibrational progressions were observed in the 193 nm NIPE spectrum. The adiabatic/vertical detachment energies (ADE/VDE) were derived to be 1.42/2.06 and 4.43/4.86 eV for the ground singlet state and excited triplet state, respectively. Using the optimized geometries and vibrational frequencies of the anion and the neutral, the Franck–Condon factors were calculated for electron detachments to produce HFA in its lowest singlet and triplet states. Good agreements are obtained hereby for both bands between the experimental and calculated NIPE spectra, when taking into account combination vibrational excitations, unequivocally revealing that HFA possesses a singlet ground state with a giant singlet–triplet energy difference (ΔE ST ). The electron affinity (EA) and ΔE ST of HFA were therefore determined to be EA = 1.42 ± 0.02 eV and ΔE ST = −3.01 eV.

Wang, Lei↗

Rapid quantification of whole seed fatty acid amount, composition, and shape phenotypes from diverse oilseed species with large differences in seed size

Seed oils are widely used in the food, biofuel, and industrial feedstock industries, with their utility and value determined by total oil content and fatty acid composition. Current high throughput seed oil analysis methods either lack accuracy in total fatty acid profiling or require extensive labor for lipid extraction prior to derivatization to fatty acid methyl esters (FAME) and quantification by gas chromatography (GC). Alternatively, direct whole seed FAME production methods have been developed for the very small seeds in the model species Arabidopsis thaliana but these have generally not been adapted to larger seeds of most oilseed crops. High-throughput direct whole seed FAME production methods were optimized for seeds up to 5 mg each utilizing acid-catalyzed esterification. For the oilseed species Camelina sativa, Thlaspi avernse (pennycress), Cuphea viscosissima, and Brassica napus (var. Canola), the total seed fatty acid content and composition from direct seed esterification to FAME matched that of lipid extract derivatization demonstrating the accuracy of the methods. In combination with seed phenotyping using GridFree, this approach enabled the development of a rapid pipeline for simultaneous seed weight, count, size/shape phenotyping, and oil analysis. For the larger and tougher seeds produced by Limnanthes alba (Meadowfoam) and Cannabis sativa L. (hemp) the whole seed acid-based method proved insufficient, and prior laborious homogenization of seeds was required. Therefore, a rapid one-tube bead homogenization and base catalyzed-esterification method was developed. Base-derived fatty acid esterification cannot derivatize free fatty acids leading to slightly lower total seed fatty acid than acid-catalyzed methods, however the seed oil content and fatty acid composition that is valuable for screening large numbers of samples in research populations was accurately measured. New rapid whole seed fatty acid esterification and phenotyping protocols were developed to accurately assess oilseed lipid content. These methods are particularly valuable in oilseed research, breeding, and engineering applications where efficient analysis of large numbers of samples and accurate oil fatty acid profiling is essential. While having been developed for current and emerging oilseed crops, these methods also provide a foundation from which protocols might be established for new and emerging crop species.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of the weighted shifted boundary method for the Poisson and Stokes problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods, and relies on reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by properly shifting the location and values of the boundary conditions. This avoids integration over cut cells and the associated implementation issues. Recently, the Weighted SBM (WSBM) was proposed for the Navier-Stokes equations with free surfaces and the Stokes flow with moving boundaries. The attribute “weighted” in the name WSBM stems from the fact that its variational form is weighted with the elemental volume fraction of active fluid. The motivation for the development of the WSBM was the preservation of the volume of active fluid to a higher degree of accuracy, which in turn resulted in improved stability and robustness characteristics in moving-boundary, time-dependent simulations. In this article, we present the numerical analysis of the WSBM formulations for the Poisson and Stokes problems. We give mathematical conditions under which the bilinear forms defining the discrete variational formulations are uniformly coercive (Poisson problem) or inf-sup stable (Stokes problem). By these results, stability and optimal convergence is proven in the natural norm; L2-error estimates can also be derived.

Approximate domain boundaries↗

MIDAS-DC-AC Tool: Fully Automating the Acquisition of AC Power Flow Solution (MIDAS-DC2AC)

MIDAS DC2AC is an automated tool for achieving a converged AC power flow solution from any dispatch, e.g., determined using DC power flow model based optimal power flow. The entire process is free of human interference. It is usually encountered in practice that, even with a DC power flow solution, acquiring the solved AC power flow solution, if exists, sometimes could be a challenging task, especially during the planning stage. It is also difficult to distinguish the unsolvable cases from diverging iterations. Manual adjustments to approach the desired power flow condition has been largely relied on in the past using lots of engineering heuristics. This tool provides a systematic way to first achieve a solvable AC power flow case by modifying the power flow condition, and then try to track the AC power flow solution while gradually removing the adopted changes. If all adopted changes can be completely removed, then the original AC power flow solution is obtained. Otherwise, insights for actionable controls are derived to help operation and planning. Currently, this tool has been implemented in Python using SIEMENS PTI PSS/E as power flow solver, where only adjusting generator terminal voltage set point is considered as an available means to try to turn an unsolved power flow to a solved one. In future, more means should be considered, including the operation of tap-changing transformers, switched shunts and redispatch of active power.

Tan, Jin↗

DC-AC Tool: Fully Automating the Acquisition of AC Power Flow Solution

DC2AC is an automated tool for achieving a converged AC power flow solution from any dispatch, e.g., determined using DC power flow model based optimal power flow. The entire process is free of human interference. It is usually encountered in practice that, even with a DC power flow solution, acquiring the solved AC power flow solution, if exists, sometimes could be a challenging task, especially during the planning stage. It is also difficult to distinguish the unsolvable cases from diverging iterations. Manual adjustments to approach the desired power flow condition has been largely relied on in the past using lots of engineering heuristics. This tool provides a systematic way to first achieve a solvable AC power flow case by modifying the power flow condition, and then try to track the AC power flow solution while gradually removing the adopted changes. If all adopted changes can be completely removed, then the original AC power flow solution is obtained. Otherwise, insights for actionable controls are derived to help operation and planning. Currently, this tool has been implemented in Python using SIEMENS PTI PSS/E as power flow solver, where only adjusting generator terminal voltage set point is considered as an available means to try to turn an unsolved power flow to a solved one. In future, more means should be considered, including the operation of tap-changing transformers, switched shunts and redispatch of active power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal trajectories for the Aeroassisted Flight Experiment. Part 1: Equations of motion in an Earth-fixed system

The determination of optimal trajectories for the aeroassisted flight experiment (AFE) is discussed. The AFE refers to the study of the free flight of an autonomous spacecraft, shuttle-launched and shuttle-recovered. Its purpose is to gather atmospheric entry environmental data for use in designing aeroassisted orbital transfer vehicles (AOTV). It is assumed that: (1) the spacecraft is a particle of constant mass; (2) the Earth is rotating with constant angular velocity; (3) the Earth is an oblate planet, and the gravitational potential depends on both the radial distance and the latitude (harmonics of order higher than four are ignored); and (4) the atmosphere is at rest with respect to the Earth. Under these assumptions, the equations of motion for hypervelocity atmospheric flight (which can be used not only for AFE problems, but also for AOT problems and space shuttle problems) are derived in an Earth-fixed system. Transformation relations are supplied which allow one to pass from quantities computed in an Earth-fixed system to quantities computed in an inertial system, and vice versa.

Miele, A.↗

Optimal trajectories for the Aeroassisted Flight Experiment. Part 2: Equations of motion in an inertial system

The determination of optimal trajectories for the aeroassisted flight experiment (AFE) is discussed. The AFE refers to the study of the free flight of an autonomous spacecraft, shuttle-launched and shuttle-recovered. Its purpose is to gather atmospheric entry environmental data for use in designing aeroassisted orbital transfer vehicles (AOTV). It is assumed that: (1) the spacecraft is a particle of constant mass; (2) the Earth is rotating with constant angular velocity; (3) the Earth is an oblate planet, and the gravitational potential depends on both the radial distance and the latitude (harmonics of order higher than four are ignored); and (4) the atmosphere is at rest with respect to the Earth. Under these assumptions, the equations of motion for hypervelocity atmospheric flight (which can be used not only for AFE problems, but also for AOT problems and space shuttle problems) are derived in an inertial system. Transformation relations are supplied which allow one to pass from quantities computed in an inertial system to quantities computed in an Earth-fixed system and vice versa.

Miele, A.↗

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Performance Impacts to the NASA Artemis II Trajectory Correction Burn Placement

As NASA embarks to return humans to the lunar vicinity with the upcoming Artemis II mission, the selected free return trajectory taking the crew to the Moon in the Orion spacecraft is impacted by the execution of small trajectory correction burns to ensure the spacecraft stays on course for a successful return to Earth. The placement of these nominally zero translational maneuvers must account for the crew schedule, navigation tracking constraints, spacecraft venting, thermal and communication requirements, and a host of other programmatic factors. Understanding the influence the placement of these periodic burn corrections have on the integrated GN\&C performance can provide valuable insight to mission controllers and trajectory planning processes to untangle the complex trade space considered for both baseline and contingency scenarios. This sensitivity information can also be utilized to facilitate the optimized placement of these burns. This paper utilizes several techniques to systematically generate the performance impacts to the NASA Artemis II trajectory correction burn placement and demonstrate how to derive optimized locations that make the system robust to crew activity, maneuver execution errors, navigation uncertainty, orbit insertion errors, disturbance accelerations, and other system limitations.

GN&C↗