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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Scattering properties of Venus' surface

Radar backscatter functions Sigma-(carat)(sub 0)(phi) for incidence angles between 0 less than or equal to phi less than or equal to 4-10 deg were derived from Magellan altimetry radar echoes. The procedure includes constrained solution of a system of simultaneous equations for which the echo-spectrum and echo time profile are inputs. A practical and workable set of constraints was applied; optimization and improved results are expected as the analysis matures. The scattering functions yield information on small-scale surface structures (tens of centimeters to tens of meters) but averaged over hundreds of sq km. RMS surface slopes derived from fits of analytic functions to the Sigma-(carat)(sub 0)(phi) results were converted to map form and show patterns similar to those reported using other techniques. While all three forms are found on Venus, fit residuals imply that an exponential scattering function matches data better than either the Hagfors or Gaussian form in most areas, although the Hagfors function may be a better descriptor at some sites. Limited study of image data indicates that average backscatter cross section, and possibly its slope, can be derived at oblique angles (17 deg less than or equal to phi less than or equal to 45 deg). Offsets of the echo peak in altimetry spectra are surprisingly common and are loosely correlated with Venus topography, but no cause for this phenomenon was identified.

Tyler, G. L.↗
NASA NTRS1990

Large scale nonlinear numerical optimal control for finite element models of flexible structures

This paper discusses the development of large scale numerical optimal control algorithms for nonlinear systems and their application to finite element models of structures. This work is based on our expansion of the optimal control algorithm (DDP) in the following steps: improvement of convergence for initial policies in non-convex regions, development of a numerically accurate penalty function method approach for constrained DDP problems, and parallel processing on supercomputers. The expanded constrained DDP algorithm was applied to the control of a four-bay, two dimensional truss with 12 soft members, which generates geometric nonlinearities. Using an explicit finite element model to describe the structural system requires 32 state variables and 10,000 time steps. Our numerical results indicate that for constrained or unconstrained structural problems with nonlinear dynamics, the results obtained by our expanded constrained DDP are significantly better than those obtained using linear-quadratic feedback control.

Shoemaker, Christine A.↗
DOE OSTI2025

Challenges and Optimization of Mu2e Proton Target Design with Radiative Cooling

Mu2e, the Muon-to-Electron Conversion Experiment, aims to identify physics beyond the Standard Model, namely, the conversion of muons to electrons without the emission of neutrinos. The muons are produced from pions generated in a production target when it is hit by an 8 GeV proton beam from the Fermilab Booster/Main Injector. The proton target design space is strongly constrained by a one-year operating lifetime and the need for radiative cooling in a vacuum environment. Uncertainties in the lifetime of the existing baseline design – a monolithic, segmented tungsten target – are large, particularly due to unknown impacts of radiation damage at the very high proton fluences expected in the experiment. We have begun evaluation of a new design utilizing Inconel 718 over the WL10 used in the existing target design. As a result, the structural design of the target has evolved significantly. This evolution focuses on lowering the target temperature, minimizing obstruction to muons, increasing structural stability, maximizing fatigue lifetime, simplifying the fabrication process, and more. The thermal management, structural stability and fatigue lifetime are emphasized here. These optimizations have led to a promising new target design for the Mu2e experiment.

Liu, Z. [Fermilab]↗
DOE OSTI2025

Unravelling the origins of shale nanoporosity using small-angle neutron scattering (SANS)

Hydrocarbon production from tight rocks is constrained by slow diffusion within the shale matrix, limited by small pore sizes and low permeability. The nanopore proportion and size distribution significantly influence matrix permeability, a key property for optimizing hydrocarbon recovery and supporting hydrogen production while minimizing environmental impacts. Small-angle neutron scattering (SANS) has been an important tool for exploring the characteristics and structure of shale nanopores. This study used SANS to analyze nanoporosity and pore size distribution (<100 nm) in tight rocks with varying compositions to determine the influence of rock heterogeneity on SANS measurements. Results showed that nanoporosity correlates with clay content, with the highest clay-rich shale (52.48 wt% clay) exhibiting 8.8 % nanoporosity. SANS also revealed more nanopores than traditional nitrogen adsorption measurements, affirming its ability to reflect bulk mineralogy and upholding the relevance of experimental findings using this technique to optimize field operational approaches.

03 NATURAL GAS↗
DOE OSTI2025

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗
DOE OSTI2025

Hybrid Energy Resources Bidding Model (HERB) v1.0

The HERB Model provides a stochastic optimization framework for hybrid power plants (Storage plus Renewables) participating in day-ahead electricity markets. It considers uncertainty in market prices and renewable energy generation and generated risk-constrained price-quantity bid curves with limited, non-decreasing price steps.

Heleno, Miguel [Lawrence Berkeley National Laborat↗
DOE OSTI2024

Testing the ΛCDM Cosmological Model with Forthcoming Measurements of the Cosmic Microwave Background with SPT-3G

We forecast constraints on cosmological parameters enabled by three surveys conducted with SPT-3G, the third-generation camera on the South Pole Telescope. The surveys cover separate regions of 1500, 2650, and 6000 deg$^{2}$ to different depths, in total observing 25% of the sky. These regions will be measured to white noise levels of roughly 2.5, 9, and 12μK-armin, respectively, in cosmic microwave background (CMB) temperature units at 150 GHz by the end of 2024. The survey also includes measurements at 95 and 220 GHz, which have noise levels a factor of ∼1.2 and 3.5 times higher than 150 GHz, respectively, with each band having a polarization noise level ∼2times higher than the temperature noise. We use a novel approach to obtain the covariance matrices for jointly and optimally estimated gravitational lensing potential band powers and unlensed CMB temperature and polarization band powers. We demonstrate the ability to test the ΛCDM model via the consistency of cosmological parameters constrained independently from SPT-3G and Planck data, and consider the improvement in constraints on ΛCDM extension parameters from a joint analysis of SPT-3G and Planck data. The ΛCDM cosmological parameters are typically constrained with uncertainties up to ∼2 times smaller with SPT-3G data, compared to Planck, with the two data sets measuring significantly different angular scales and polarization levels, providing additional tests of the standard cosmological model.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

Modified SUMT for structural synthesis

The concepts of the singular perturbation theory are employed to modify the SUMT (Sequential Unconstrained Minimization Technique) algorithm of Fiacco-McCormick (1968) in order to make it more robust and reliable. The algorithm, which uses a sequence of penalty parameters to convert a constrained problem into a sequence of unconstrained problems, suffers from the need to minimize an ill-conditioned penalty function. By using the modified SUMT algorithm on two different structural optimization problems, it is shown that the singular perturbation SUMT easily converges to accurate solutions.

Kamat, M. P.↗
NASA NTRS1993

Space Shuttle Main Engine performance analysis

For a number of years, NASA has relied primarily upon periodically updated versions of Rocketdyne's power balance model (PBM) to provide space shuttle main engine (SSME) steady-state performance prediction. A recent computational study indicated that PBM predictions do not satisfy fundamental energy conservation principles. More recently, SSME test results provided by the Technology Test Bed (TTB) program have indicated significant discrepancies between PBM flow and temperature predictions and TTB observations. Results of these investigations have diminished confidence in the predictions provided by PBM, and motivated the development of new computational tools for supporting SSME performance analysis. A multivariate least squares regression algorithm was developed and implemented during this effort in order to efficiently characterize TTB data. This procedure, called the 'gains model,' was used to approximate the variation of SSME performance parameters such as flow rate, pressure, temperature, speed, and assorted hardware characteristics in terms of six assumed independent influences. These six influences were engine power level, mixture ratio, fuel inlet pressure and temperature, and oxidizer inlet pressure and temperature. A BFGS optimization algorithm provided the base procedure for determining regression coefficients for both linear and full quadratic approximations of parameter variation. Statistical information relative to data deviation from regression derived relations was also computed. A new strategy for integrating test data with theoretical performance prediction was also investigated. The current integration procedure employed by PBM treats test data as pristine and adjusts hardware characteristics in a heuristic manner to achieve engine balance. Within PBM, this integration procedure is called 'data reduction.' By contrast, the new data integration procedure, termed 'reconciliation,' uses mathematical optimization techniques, and requires both measurement and balance uncertainty estimates. The reconciler attempts to select operational parameters that minimize the difference between theoretical prediction and observation. Selected values are further constrained to fall within measurement uncertainty limits and to satisfy fundamental physical relations (mass conservation, energy conservation, pressure drop relations, etc.) within uncertainty estimates for all SSME subsystems. The parameter selection problem described above is a traditional nonlinear programming problem. The reconciler employs a mixed penalty method to determine optimum values of SSME operating parameters associated with this problem formulation.

Santi, L. Michael↗
NASA NTRS2018

The WFIRST Coronagraph Instrument: A Major Step in the Exploration of Sun-Like Planetary Systems Via Direct Imaging

The Wide Field Infrared Survey Telescope (WFIRST) Coronagraph Instrument (CGI) will be the first high-performance stellar coronagraph using active wavefront control for deep starlight suppression in space, providing unprecedented levels of contrast and spatial resolution for astronomical observations in the optical. One science case enabled by the CGI will be taking visible images and (R~50) spectra of faint interplanetary dust structures present in the habitable zone of nearby sunlike stars (~10 pc) and within the snow-line of more distant ones (~20 pc), down to dust brightness levels commensurate with that of the solar system zodiacal cloud. Reaching contrast levels below 10-7 at sub-arcsecond angular scales for the first time, CGI will cross an important threshold in debris disks physics, accessing disks with low enough optical depths that their structure is dominated by transport mechanisms rather than collisions. Hence, CGI will help us understand how exozodiacal dust grains are produced and transported in low-density disks around mature stars. Additionally, CGI will be able to measure the brightness level and constrain the degree of asymmetry of exozodiacal clouds around individual nearby sunlike stars in the optical, at the ~3x solar zodiacal emission level. This information will be extremely valuable for optimizing the observational strategy of possible future exo-Earth direct imaging missions, especially those planning to operate at optical wavelengths as well, such as the Habitable Exoplanet Observatory (HabEx) and the Large Ultraviolet/Optical/Infrared Surveyor (LUVOIR).

Demers, R.↗
DOE OSTI2022

Single-stage gradient-based stellarator coil design: Optimization for near-axis quasi-symmetry

Here we present a new coil design paradigm for magnetic confinement in stellarators. Our approach directly optimizes coil shapes and coil currents to produce a vacuum quasi-symmetric magnetic field with a target rotational transform on the magnetic axis. This approach differs from the traditional two-stage approach in which first a magnetic configuration with desirable physics properties is found, and then coils to approximately realize this magnetic configuration are designed. The proposed single-stage approach allows us to find a compromise between confinement and engineering requirements, i.e., find easy-to-build coils with good confinement properties. Using forward and adjoint sensitivities, we derive derivatives of the physical quantities in the objective, which is constrained by a nonlinear periodic differential equation. In two numerical examples, we compare different gradient-based descent algorithms and find that incorporating approximate second-order derivative information through a quasi-Newton method is crucial for convergence. We also explore the optimization landscape in the neighborhood of a minimizer and find many directions in which the objective is mostly flat, indicating ample freedom to find simple and thus easy-to-build coils.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Optimizing Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy-Duty Fuel Cell Electric Vehicles

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen-based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This article introduces the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy-duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional-specific vehicle fuel economy and weight, vehicle origin and destination (O-D), and vehicle volume by class and infrastructure costs to characterize in-mission refueling requirements for a given freight corridor. The authors applied this framework to determine the ideal public access locations for hydrogen refueling (constrained by existing fueling stations), the minimal viable cost to deploy sufficient hydrogen fuel dispensers, and associated equipment, to accommodate a growing population of hydrogen fuel cell trucks. The framework discussed in this article can be expanded and applied to a larger interstate system, expanded regional corridor, or other transportation network. This article is the third in a series of papers that defined the model development to optimize a national hydrogen refueling infrastructure ecosystem for HD commercial vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Angular-spectral filtering of recoil protons for optimization of fast neutron imaging employing proton converters

Fast neutron imaging is an important capability for diverse applications such as inertial confinement fusion diagnostics, cargo security, nuclear nonproliferation and arms control, and industrial inspection. Traditional phosphor image plates can be enhanced for fast neutron imaging using hydrogenous plastic converters which allow fast neutrons to scatter off hydrogen nuclei to produce energetic protons that can be recorded by the image plate. However, protons emitted by image plates are not constrained in their emission angle, which contributes to the blur of the resulting image. Here, we investigate two methods that can alter the spatial extent of converted protons that deposit energy in the image plate: reducing the converter thickness, and introducing a proton filter between the plastic converter and image plate to reduce the contribution of lower-energy, off-axis protons to the image. Here we determine the optimal plastic converter thickness for maximizing the signal intensity to be 2–3 mm through Monte Carlo simulations, and we benchmark this result against experimental measurements with a deuterium-tritium (DT) neutron generator. Next, we evaluate the image smearing and signal loss for various converters to show that solely reducing the converter thickness has the expected effect of reducing the blur from proton image smearing of the sharpness of an edge recorded on the image plate at the cost of reducing the signal intensity. The use of a proton filter is shown to achieve a similar improvement of edge sharpness as reducing the converter thickness while also sacrificing the signal intensity. We conclude that the use of proton energy filtering can improve the sharpness of fast neutron images in situations where the converter thickness cannot be reduced below some practical minimum. For more intense neutron sources, the signal intensity is of less concern, and optimizing the resolution of the image plate and therefore of the imaging system could have greater value. In these applications, proton filters may allow for improved fast neutron imaging measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Constrained Block Nonlinear Neural Dynamical Models

Neural network modules conditioned by known priors can be effectively trained and combined to represent systems with nonlinear dynamics. This work explores a novel formulation for data-efficient learning of deep control-oriented nonlinear dynamical models by embedding local model structure and constraints. The proposed method consists of neural network blocks that represent input, state, and output dynamics with constraints placed on the network weights and system variables. For handling partially observable dynamical systems, we utilize a state observer neural network to estimate the states of the system's latent dynamics. We evaluate the performance of the proposed architecture and training methods on system identification tasks for three nonlinear systems: a continuous stirred tank reactor, a two tank interacting system, and an aerodynamics body. Models optimized with a few thousand system state observations accurately represent system dynamics in open loop simulation over thousands of time steps from a single set of initial conditions. Experimental results demonstrate an order of magnitude reduction in open-loop simulation mean squared error for our constrained, block-structured neural models when compared to traditional unstructured and unconstrained neural network models.

Skomski, Elliott↗
DOE OSTI2022

Versatile soil gas concentration and isotope monitoring: optimization and integration of novel soil gas probes with online trace gas detection

Abstract. Gas concentrations and isotopic signatures can unveil microbial metabolisms and their responses to environmental changes in soil. Currently, few methods measure in situ soil trace gases such as the products of nitrogen and carbon cycling or volatile organic compounds (VOCs) that constrain microbial biochemical processes like nitrification, methanogenesis, respiration, and microbial communication. Versatile trace gas sampling systems that integrate soil probes with sensitive trace gas analyzers could fill this gap with in situ soil gas measurements that resolve spatial (centimeters) and temporal (minutes) patterns. We developed a system that integrates new porous and hydrophobic sintered polytetrafluoroethylene (sPTFE) diffusive soil gas probes that non-disruptively collect soil gas samples with a transfer system to direct gas from multiple probes to one or more central gas analyzer(s) such as laser and mass spectrometers. Here, we demonstrate the feasibility and versatility of this automated multiprobe system for soil gas measurements of isotopic ratios of nitrous oxide (δ18O, δ15N, and the 15N site preference of N2O), methane, carbon dioxide (δ13C), and VOCs. First, we used an inert silica matrix to challenge probe measurements under controlled gas conditions. By changing and controlling system flow parameters, including the probe flow rate, we optimized recovery of representative soil gas samples while reducing sampling artifacts on subsurface concentrations. Second, we used this system to provide a real-time window into the impact of environmental manipulation of irrigation and soil redox conditions on in situ N2O and VOC concentrations. Moreover, to reveal the dynamics in the stable isotope ratios of N2O (i.e., 14N14N16O, 14N15N16O, 15N14N16O, and 14N14N18O), we developed a new high-precision laser spectrometer with a reduced sample volume demand. Our integrated system – a tunable infrared laser direct absorption spectrometry (TILDAS) in parallel with Vocus proton transfer reaction mass spectrometry (PTR-MS), in line with sPTFE soil gas probes – successfully quantified isotopic signatures for N2O, CO2, and VOCs in real time as responses to changes in the dry–wetting cycle and redox conditions. Broadening the collection of trace gases that can be monitored in the subsurface is critical for monitoring biogeochemical cycles, ecosystem health, and management practices at scales relevant to the soil system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Nuclear explosion monitoring network design considerations

Design of an efficient monitoring network requires information on the type and size of releases to be detected, the accuracy and reliability of the measuring equipment, and the desired network performance. This work provides a scientific basis for optimizing or minimizing networks of 133 Xe samplers to achieve a desired performance level for different levels of release. The approach of this work varies the density of sampling locations to find optimal location subsets, and to explore the properties of variations of those subsets – how crucial is a specific subset; are substitutions problematic? The choice of possible station locations is arbitrary but constrained to some extent by the location of islands, land masses, difficult topography (mountains, etc.) and the places where infrastructure exists to run and support a sampler. Performance is evaluated using hypothetical releases and atmospheric transport models that cover an entire year.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗