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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

ReMU: regional minimal updating for model-based derivative-free optimization

Derivative-free optimization (DFO) problems are optimization problems where derivative information is unavailable or extremely difficult to obtain. Model-based DFO solvers have been applied extensively in scientific computing. Powell's NEWUOA (2004) [Powell, The NEWUOA software for unconstrained optimization without derivatives, in Large-Scale Nonlinear Optimization, Nonconvex Optimization and its Applications Vol. 83, G. Di Pillo and M. Roma, eds., Springer, 2006, pp. 255–297] and Wild's POUNDerS (2014) [Wild, Solving derivative-free nonlinear least squares problems with POUNDERS, in Advances and Trends in Optimization with Engineering Applications, T. Terlaky, M.F. Anjos, and S. Ahmed, eds., SIAM, 2017, pp. 529–540] explore the numerical power of the minimal norm Hessian (MNH) model for DFO and contributed to the open discussion on building better models with fewer data to achieve faster numerical convergence. Another decade later, we propose the regional minimal updating (ReMU) models, and extend the previous models into a broader class, including the H 2 norm models [Xie and Yuan, Least H 2 norm updating of quadratic interpolation models for derivative-free trust-region algorithms, IMA J. Numer. Anal. 46 (2025), pp. 21–50]. This paper shows motivation behind ReMU models, computational details, theoretical and numerical results on particular extreme points and the barycentre of ReMU's weight coefficient region, and the associated KKT matrix error and distance. Novel metrics, such as the truncated Newton step error, are proposed to numerically understand the new models' properties. A new algorithmic strategy, based on iteratively adjusting the ReMU model type, is also proposed, and shows numerical advantages by combining and switching between the barycentric model and the classic least Frobenius norm model in an online fashion.

derivative-free trust-region methods↗
DOE OSTI2025

Dynamic Model Development of a Wind Power Plant Using Neural Net Method to Forecast Wind Power Output (CRADA Final Report)

This project is intended to model wind power plant based on monitored data at the wind power plant. This project will promote the university research in Renewable Energy area and trains the future highly qualified engineers. The dynamic model will be based on neural net model with the input from the two met towers (12 inputs), and the number of turbines in operation (one input). The overall input will be 13 inputs to drive the simulations. The output power at the point of interconnection will be used to tune the neural net weight coefficients. Two neural net concepts will be investigated (the back propagation neural net and the dynamic recurrent neural net with feedback).

17 WIND ENERGY↗
DOE OSTI2020

Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures

Increased data acquisition by uncalibrated, heterogeneous digital sensor systems such as smartphones present new challenges. Binary metrics are proposed for the quantification of cyber-physical signal characteristics and features, and a standardized constant-Q variation of the Gabor atom is developed for use with wavelet transforms. Two different continuous wavelet transform (CWT) reconstruction formulas are presented and tested under different signal to noise ratio (SNR) conditions. A sparse superposition of Nth order Gabor atoms worked well against a synthetic blast transient using the wavelet entropy and an entropy-like parametrization of the SNR as the CWT coefficient-weighting functions. The proposed methods should be well suited for sparse feature extraction and dictionary-based machine learning across multiple sensor modalities.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2022

Non-destructive measurement and real-time monitoring of apple hardness during ultrasonic contact drying via portable NIR spectroscopy and machine learning

Portable near-infrared spectrometer in the spectral range of 900–1700 nm was evaluated for the first time to assess and monitor apple hardness in real-time during ultrasonic drying. Calibration models were developed using PLS and ANN, and their performances were evaluated by internal leave-one-out cross-validation and an external dataset. Several pre-treatments including standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first and second derivatives were employed to examine the effects of spectral variations in hardness prediction. Seven important wavelengths were selected using weighted regression coefficients to develop a simple MLR model to facilitate the model interpretation and circumvent noise. The models using PLS, MLR, and ANN with selected wavelengths predicted the apple hardness with R 2 p of 0.91, 0.91, 0.95, and RMSEP of 14.78, 14.85, and 12.46 N, respectively. Finally, the results indicate that portable NIR spectrometers are quite promising for real-time monitoring of apple hardness during ultrasonic drying.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Developing and Implementing New Waste Chemistry Controls for Hanford's Double-Shell Tanks - 20041

Waste chemistry controls for the Hanford double-shell tanks (DSTs) were established in the 1980's in response to tank failures caused by stress corrosion cracking (SCC) at the Savannah River Site (SRS). The controls were established based on a combination of SRS chemistry limits and corrosion testing results. Conditions in the Hanford DSTs have changed over time, with the temperature in the majority of the DSTs dropping below 50 deg. C. Testing indicated that the original chemistry control specification and SCC testing performed in 2010 did not protect against pitting corrosion mechanisms - what is believed to have caused the failure of tank 241-AY-102. New waste chemistry controls are necessary to protect the DSTs from both SCC and pitting corrosion. Savannah River National Laboratory (SRNL), with input from the Tank Integrity Expert Panel (TIEP) Corrosion Subgroup (CSG), performed a statistically based investigation of nitrate and halide ion induced pitting corrosion. The investigation was intended to develop a comprehensive waste chemistry envelope that minimizes the risk of both SCC and pitting caused by halide and nitrate ions. The waste chemistry envelope needed to be robust enough to address future waste retrieval and process changes which could significantly change the waste composition of the DSTs. The experimental design allowed the statistically significant ions and their effect on pitting corrosion to be determined. SRNL developed the 'pitting factor' which is an empirical relationship between the statistically significant inhibitive species (hydroxide, and nitrite), and pitting inducing species (nitrate, chloride, and fluoride). The coefficients are weighted factors that show the degree of influence the species have on the propensity for pitting. New waste chemistry control limits were recommended by SRNL, and concurred with by the TIEP CSG, that incorporated the pitting factor along with other limits. The controls developed to reduce the risk of pitting corrosion were evaluated to determine if they also protected against SCC. Hundreds of test results were reviewed and compared against the proposed limits. With the exception of one test result, instances where cracking was observed corresponded to chemistry that was outside of the proposed limits - indicating that the chemistry controls developed for pitting also adequately addressed SCC concerns. Existing tank composition estimates were evaluated against the new chemistry controls - three current tank chemistries are suspect, and may not meet the new chemistry control requirements. These included the interstitial liquid (liquid associated with solids) of DSTs 241-AN-102, 241-AN-106, 241-AN-107, and 241-AY-101. Measures are ongoing to evaluate the tanks with the suspect chemistry. These include varying combinations of: performing additional evaluations (history of use, modeling); DST specific laboratory testing; and, pursuing core samples of the DSTs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Transport across interfaces in symmetric orbifolds

We examine how conformal boundaries encode energy transport coefficients — namely transmission and reflection probabilities — of corresponding conformal interfaces in symmetric orbifold theories. These constitute a large class of irrational theories and are closely related to holographic setups. Our central goal is to compare such coefficients at the orbifold point (a field theory calculation) against their values when the orbifold is highly deformed (a gravity calculation) — an approach akin to past AdS/CFT-guided comparisons of physical quantities at strong versus weak coupling. At the orbifold point, we find that the (weighted-average) transport coefficients are simply averages of coefficients in the underlying seed theory. We then focus on the symmetric orbifold of the T 4 sigma model interface CFT dual to type IIB supergravity on the 3d Janus solution. We compare the holographic transmission coefficient, which was found by [1], to that of the orbifold point. We find that the profile of the transmission coefficient substantially increases with the coupling, in contrast to boundary entropy. We also present some related ideas about twisted-sector data encoded by boundary states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

In‐mold rheology and automated process control for injection molding of recycled polypropylene

Abstract Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.

Krantz, Joshua↗
DOE OSTI2023

Proper orthogonal descriptors for efficient and accurate interatomic potentials

Here, we present the proper orthogonal descriptors for efficient and accuracy representation of the potential energy surface. The potential energy surface is represented as a many-body expansion of parametrized potentials in which the potentials are functions of atom positions and parameters. The proper orthogonal decomposition is employed to decompose the parametrized potentials into a set of proper orthogonal descriptors (PODs). Because of the rapid convergence of the proper orthogonal decomposition, relevant snapshots can be sampled exhaustively to represent the atomic neighborhood environment accurately with a small number of descriptors. The proper orthogonal descriptors are used to develop interatomic potentials by using a linear expansion of the descriptors and determining the expansion coefficients from a weighted least-squares regression against a density functional theory (DFT) training set. We present a comprehensive evaluation of the POD potentials on previously published DFT data sets comprising Li, Mo, Cu, Ni, Si, Ge, and Ta elements. The data sets represent a diverse pool of metals, transition metals, and semiconductors. The accuracy of the POD potentials are comparable to that of state-of-the-art machine learning potentials such as the spectral neighbor analysis potential (SNAP) and the atomic cluster expansion (ACE).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Solar thermal aerogel receiver and materials therefor

A silica aerogel having a mean pore size less than 5 nm with a standard deviation of 3 nm. The silica aerogel may have greater than 95% solar-weighted transmittance at a thickness of 8 mm for wavelengths in the range of 250 nm to 2500 nm, and a 400° C. black-body weighted specific extinction coefficient of greater than 8 m 2 /kg for wavelengths of 1.5 μm to 15 μm. Silica aerogel synthesis methods are described. A solar thermal aerogel receiver (STAR) may include an opaque frame defining an opening, an aerogel layer disposed in the opaque frame, with at least a portion of the aerogel layer being proximate the opening, and a heat transfer fluid pipe in thermal contact with and proximate the aerogel layer. A concentrating solar energy system may include a STAR and at least one reflector to direct sunlight to an opening in the STAR.

Chen, Gang↗
DOE OSTI2023

Solar thermal aerogel receiver and materials therefor

A silica aerogel having a mean pore size less than 5 nm with a standard deviation of 3 nm. The silica aerogel may have greater than 95% solar-weighted transmittance at a thickness of 8 mm for wavelengths in the range of 250 nm to 2500 nm, and a 400° C. black-body weighted specific extinction coefficient of greater than 8 m2/kg for wavelengths of 1.5 μm to 15 μm. Silica aerogel synthesis methods are described. A solar thermal aerogel receiver (STAR) may include an opaque frame defining an opening, an aerogel layer disposed in the opaque frame, with at least a portion of the aerogel layer being proximate the opening, and a heat transfer fluid pipe in thermal contact with and proximate the aerogel layer. A concentrating solar energy system may include a STAR and at least one reflector to direct sunlight to an opening in the STAR.

Chen, Gang↗
DOE OSTI2026

Optimal Methods for Estimating Cactus Pear Biomass Using Cladode Dimensions of Morphologically Diverse Accessions

Current allometric methods for photosynthetic-stem (cladode) plants, such as cactus pear (Opuntia spp.), require refinement to be used in field settings in which diverse accessions are grown. We analysed cladode dimensional data using 14 accessions representing four species and two hybrids to quantify statistically significant morphological differences among accessions and derived cross-accession models to approximate cladode fresh weight. A Box model using cladode dimensions (e.g., length, width, thickness and diameter) and factorial combinations of these measures (e.g., length*width*thickness*diameter vs. fresh weight) resulted in the highest coefficient of determination (R 2 = 0.95 general fit) across all accessions for estimating fresh weight along with parsimony estimates using the Schwarz–Bayes Criterion (SBC), which assesses the most consistent performance on individual accessions. A Fitting-box modelling approach used the measured cladode area captured using ImageJ (R 2 = 0.93 general fit). Lastly, an Elliptical model used an elliptical approximation for the measured area and performed well over all accessions (R 2 = 0.94 general fit) while avoiding extensive manual measurements. These models meet or exceed the performance of previously published approaches when applied across morphologically diverse accessions, providing efficient tools for nondestructive estimation of cactus pear biomass under the conditions tested.

Opuntia↗
DOE OSTI2024

Experimental analysis of conductive drying of paper and board

The primary heat transfer source in the conventional multi-cylinder drying of paper and board is conduction. Conduction is facilitated by high-tension contact with steam-heated cylinders, while convective drying, the main mass transfer source, operates as heated air flows over the paper web in the pockets. This conduction process occurs at elevated temperatures and contact pressures to ensure effective contact between the wet paper web and the heated cylinders. The contact pressures and temperatures of the hot surface significantly influence the conductive drying characteristics. This research paper presents an experimental study that involves designing a simple lab-scale setup with in-situ and continuous sensing capabilities for various commercially available grades of paper and board. Embedded thermocouples measure the temperatures of the heated platen and the sheet, allowing the collection of flux data to determine heat transfer characteristics. Here, the goal of this study is to ascertain the instantaneous contact coefficients for different basis weights as a function of moisture content. The acquired data will provide valuable insights and information towards process development, design and simulation of the paper drying process.

42 ENGINEERING↗
DOE OSTI2024

A MPET 2 -mPBPK model for subcutaneous injection of biotherapeutics with different molecular weights: From local scale to whole-body scale

Subcutaneous injection of biotherapeutics has attracted considerable attention in the pharmaceutical industry. However, there is limited understanding of the mechanisms underlying the absorption of drugs with different molecular weights and the delivery of drugs from the injection site to the targeted tissue. Here, we propose the MPET 2 -mPBPK model to address this issue. This multiscale model couples the MPET 2 model, which describes subcutaneous injection at the local tissue scale from a biomechanical view, with a post-injection absorption model at injection site and a minimal physiologically-based pharmacokinetic (mPBPK) model at whole-body scale. Utilizing the principles of tissue biomechanics and fluid dynamics, the local MPET 2 model provides solutions that account for tissue deformation and drug absorption in local blood vessels and initial lymphatic vessels during injection. Additionally, we introduce a model accounting for the molecular weight effect on the absorption by blood vessels, and a nonlinear model accounting for the absorption in lymphatic vessels. The post-injection model predicts drug absorption in local blood vessels and initial lymphatic vessels, which are integrated into the whole-body mPBPK model to describe the pharmacokinetic behaviors of the absorbed drug in the circulatory and lymphatic system. We establish a numerical model which links the biomechanical process of subcutaneous injection at local tissue scale and the pharmacokinetic behaviors of injected biotherapeutics at whole-body scale. With the help of the model, we propose an explicit relationship between the reflection coefficient and the molecular weight and predict the bioavalibility of biotherapeutics with varying molecular weights via subcutaneous injection. The considered drug absorption mechanisms enable us to study the differences in local drug absorption and whole-body drug distribution with varying molecular weights. This model enhances the understanding of drug absorption mechanisms and transport routes in the circulatory system for drugs of different molecular weights, and holds the potential to facilitate the application of computational modeling to drug formulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Optimization of the artificial viscosity in Lagrangian staggered discretization codes. Modeling 1D stand-alone shock - case study

We have developed new measures of errors for numerical shock. The new approach is based on analysis of the structure function, and separation of the errors related to oscillations and shock width, which also include error in the position of the ”center” of the numerical shock. We have demonstrated that those measures correctly characterize the numerical solution. We introduced an objective function in, which both types of errors are weighted, and presented optimal values of the coefficients of the linear and quadratic viscosity for different weights and different Mach numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DESI luminous red galaxy samples for cross-correlations

We present two galaxy samples, selected from DESI Legacy Imaging Surveys (LS) DR9, with approximately 20,000 square degrees of coverage and spectroscopic redshift distributions designed for cross-correlations such as with CMB lensing, galaxy lensing, and the Sunyaev-Zel'dovich effect. The first sample is identical to the DESI Luminous Red Galaxy (LRG) sample, and the second sample is an extended LRG sample with 2–3 times the DESI LRG density. We present the improved photometric redshifts, tomographic binning and their spectroscopic redshift distributions and imaging systematics weights, and magnification bias coefficients. The catalogs and related data products will be made publicly available. The cosmological constraints using this sample and Planck lensing maps are presented in a companion paper. Here, we also make public the new set of general-purpose photometric redshifts trained using DESI spectroscopic redshifts, which are used in this work, for all galaxies in LS DR9.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Isoscalar and Isovector Giant Resonances in Closed Shells Nuclei and Bulk Properties of Nuclear Matter

Centroid energies, E CEN , of the isoscalar (T = 0) and isovector (T = 1) giant resonances of multipolarities L = 0 – 3 in 40,48 Ca, 68 Ni, 90 Zr, 116 Sn, 144 Sm and 208 Pb, were calculated within the fully self-consistent spherical Hartree-Fock (HF)-based random phase approximation (RPA) theory, using 33 different energy density functionals associated with Skyrme-type effective nucleon-nucleon interactions of the standard form commonly employed in the literature. Here, we also calculate the Pearson linear correlation coefficients between each E CEN and each bulk property of nuclear matter (NM), associated with the Skyrme interactions used in the calculations, and determine the sensitivity of E CEN to bulk properties of NM. By comparing the calculated values of E CEN to the experimental data, we constrain the values of the bulk NM properties. We find that interactions associated with the values of the NM effective mass, m* / m = 0.70 to 0.90, incompressibility coefficient, K NM = 210 to 240 MeV, and the enhancement coefficient of the energy weighted sum rule of the isovector giant dipole resonance, κ = 0.25 to 0.70, best reproduce the experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A phase-field diffraction model for thermo-hydro-mechanical propagating fractures

This paper introduces a novel diffraction based thermo-hydraulic–mechanical (THM) model for fracture propagation using a phase-field fracture (PFF) approach. The key innovation of the THM-PFF model lies in its integrated treatment of four solution variables—displacements, phase-field, pressure, and temperature—each governed by a combination of conservation of momentum (mechanics problem), a variational inequality (constrained minimization problem), mass conservation (pressure problem), and energy conservation (temperature problem). This leads to a new formulation of a coupled variational inequality system. A major advancement is the development of an extended fixed-stress algorithm, where displacements, phase-field, pressures, and temperatures are solved in a staggered sequence. An important aspect of this work is the global coupling of pressures and temperatures across the domain using diffraction systems, with diffraction coefficients defined by material parameters weighted by the diffusive phase-field variable. To ensure robust local mass conservation, we employ enriched Galerkin finite elements (EG) for both pressure and temperature diffraction equations. By enriching the continuous Galerkin basis functions with discontinuous piecewise constants, EG accurately represents solution and parameter discontinuities while preserving local mass and energy conservation—crucial aspects for THM problems and realistic behavior. Moreover, the use of a predictor–corrector local mesh adaptivity scheme is employed, allowing the model to handle small phase-field length-scale parameters while maintaining high numerical accuracy and reasonable computational cost. Furthermore, these new model and algorithmic developments represent significant advances in the field and have been substantiated through rigorous numerical tests.

Diffraction systems↗