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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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NASA NTRS1975

Interpolation in numerical optimization

The present work discusses the generation of the cubic-spline interpolator in numerical optimization methods which use a variable-step integrator with step size control based on local relative truncation error. An algorithm for generating the cubic spline with successive over-relaxation is presented which represents an improvement over that given by Ralston and Wilf (1967). Rewriting the code reduces the number of N-vectors from eight to one. The algorithm is formulated in such a way that the solution of the linear system set up yields the first derivatives at the nodal points. This method is as accurate as other schemes but requires the minimum amount of storage.

Hall, K. R.↗

NASA NTRS1991

Design optimization of space structures

The topology-shape-size optimization of space structures is investigated through Kikuchi's homogenization method. The method starts from a 'design domain block,' which is a region of space into which the structure is to materialize. This domain is initially filled with a finite element mesh, typically regular. Force and displacement boundary conditions corresponding to applied loads and supports are applied at specific points in the domain. An optimal structure is to be 'carved out' of the design under two conditions: (1) a cost function is to be minimized, and (2) equality or inequality constraints are to be satisfied. The 'carving' process is accomplished by letting microstructure holes develop and grow in elements during the optimization process. These holes have a rectangular shape in two dimensions and a cubical shape in three dimensions, and may also rotate with respect to the reference axes. The properties of the perforated element are obtained through an homogenization procedure. Once a hole reaches the volume of the element, that element effectively disappears. The project has two phases. In the first phase the method was implemented as the combination of two computer programs: a finite element module, and an optimization driver. In the second part, focus is on the application of this technique to planetary structures. The finite element part of the method was programmed for the two-dimensional case using four-node quadrilateral elements to cover the design domain. An element homogenization technique different from that of Kikuchi and coworkers was implemented. The optimization driver is based on an augmented Lagrangian optimizer, with the volume constraint treated as a Courant penalty function. The optimizer has to be especially tuned to this type of optimization because the number of design variables can reach into the thousands. The driver is presently under development.

Felippa, Carlos↗

NASA NTRS2000

Nontangent, Developed Contour Bulkheads for a Single-Stage Launch Vehicle

Dry weights for single-stage launch vehicles that incorporate nontangent, developed contour bulkheads are estimated and compared to a baseline vehicle with 1.414 aspect ratio ellipsoidal bulkheads. Weights, volumes, and heights of optimized bulkhead designs are computed using a preliminary design bulkhead analysis code. The dry weights of vehicles that incorporate the optimized bulkheads are predicted using a vehicle weights and sizing code. Two optimization approaches are employed. A structural-level method, where the vehicle's three major bulkhead regions are optimized separately and then incorporated into a model for computation of the vehicle dry weight, predicts a reduction of4365 lb (2.2 %) from the 200,679-lb baseline vehicle dry weight. In the second, vehicle-level, approach, the vehicle dry weight is the objective function for the optimization. For the vehicle-level analysis, modified bulkhead designs are analyzed and incorporated into the weights model for computation of a dry weight. The optimizer simultaneously manipulates design variables for all three bulkheads to reduce the dry weight. The vehicle-level analysis predicts a dry weight reduction of 5129 lb, a 2.6% reduction from the baseline weight. Based on these results, nontangent, developed contour bulkheads may provide substantial weight savings for single stage vehicles.

Wu, K. Chauncey↗

NASA NTRS2000

Classification of the Gabon SAR Mosaic Using a Wavelet Based Rule Classifier

A method is developed for semi-automated classification of SAR images of the tropical forest. Information is extracted using the wavelet transform (WT). The transform allows for extraction of structural information in the image as a function of scale. In order to classify the SAR image, a Desicion Tree Classifier is used. The method of pruning is used to optimize classification rate versus tree size. The results give explicit insight on the type of information useful for a given class.

Simard, Marc↗

NASA NTRS1999

Nontangent, Developed Contour Bulkheads for a Wing-Body Single Stage Launch Vehicle

Dry weights for a SSTO vehicle which incorporates nontangent, developed contour bulkheads are estimated and compared to a baseline vehicle with 1.41 4 aspect ratio ellipsoidal bulkheads, Weights, volumes and heights of optimized bulkhead designs are computed using a preliminary design bulkhead analysis code. The dry weight of a vehicle which incorporates the optimized bulkheads is predicted using a vehicle weights and sizing code. Two optimization approaches are employed. A structural-level method, where the vehicle s three major bulkhead regions are optimized separately and then incorporated into a model for computation of the vehicle dry weight, predicts a reduction of 4365 Ib (2.2 percent) from the 200,679 Ib baseline vehicle dry weight. In the second, vehicle-level, approach, the vehicle dry weight is the objective function for the optimization. During the vehicle- level analysis, modified bulkhead designs are first analyzed, then incorporated into the weights model for computation of a dry weight. The optimizer simultaneously manipulates design variables for all three bulkheads to reduce the dry weight. The vehicle-level analysis predicts a dry weight reduction of 5129 Ib, a 2.6 percent reduction from the baseline value. These results suggest that nontangent, developed contour bulkheads may provide substantial weight savings for SSTO vehicles.

Wu, K. Chauncey↗

NASA NTRS2012

TPSAS-NF1676L-13638-DND

Dry weights for single-stage launch vehicles that incorporate nontangent, developed contour bulkheads are estimated and compared to a baseline vehicle with 1.414 aspect ratio ellipsoidal bulkheads. Weights, volumes, and heights of optimized bulkhead designs are computed using a preliminary design bulkhead analysis code. The dry weights of vehicles that incorporate the optimized bulkheads are predicted using a vehicle weights and sizing code. Two optimization approaches are employed. A structural-level method, where the vehicle's three major bulkhead regions are optimized separately and then incorporated into a model for computation of the vehicle dry weight, predicts a reduction of 4365 Ib (2.2%) from the 200,679-lb baseline vehicle dry weight. In the second, vehicle-level, approach, the vehicle dry weight is the objective function for the optimization. For the vehicle-level analysis, modified bulkhead designs are analyzed and incorporated into the weights model for computation of a dry weight. The optimizer simultaneously manipulates design variables for all three bulkheads to reduce the dry weight. The vehicle- level analysis predicts a dry weight reduction of 5129 Ib, a 2.6% reduction from the baseline weight. Based on these results, nontangent, developed contour bulkheads may provide substantial weight savings for single stage vehicles.

K Chauncey Wu↗

NASA NTRS2017

TPSAS-NF1676L-28149-DND

An Optimal Estimation (OE) inversion method has been developed to retrieve vertical profiles of aerosol size distributions, volume/surface concentrations, complex refractive indices, and single scattering albedos using the High Spectral Resolution Lidar (HSRL) and polarimeter measurements. By combining the active and passive remote sensing data, we can take advantages of the high vertical resolution of the lidar measurements and the high information content of the combined observations. There are three components to the new retrieval system: 1) simultaneous aerosol vertical profile retrieval using HSRL data, 2) standalone aerosol retrieval using Research Scanning Polarimeter (RSP), and 3) combined HSRL and RSP optimal estimation retrieval. For the LIDAR retrieval, we solve for number concentrations, mode fractions, aerosol size distributions, and real and imaginary part of refractive indices simultaneously. Based on this information, other parameters such as effective particle radius, surface and volume concentration, single scattering albedo can be derived. The combined HSRL-polarimeter algorithm will provide improved single scattering albedo and refractive index retrievals. The newly developed retrieval algorithm is very fast, and it provides an optimal estimation solution with associated error estimates. By solving for the aerosol vertical profiles using HSRL extinctions and backscattering coefficients from different layers, the new OE method can effectively reduce the impact of measurement noise on the retrieved aerosol microphysical properties. It also enables us to effectively combing HSRL and RSP data in the single OE retrieval system since the passive polarimeter instruments measure path-integrated intensity and polarizations. We have performed sensitivity studies using simulated data and applied the OE algorithms to NASA airborne field data measured by the HSRL-2 and the RSP instruments.

Xu Liu↗

NASA NTRS1992

Application of Newton modified barrier method (NMBM) to structural optimization

This paper presents the application of the NMBM to obtain a minimum weight structure with constraints on displacements and minimum sizes. The solution to the problem is obtained via minimizing the Modified Barrier Function (MBF) at each step by using the Newton Method and updating Lagrange multipliers. The Lagrange multipliers are updated by using the value of the constraints at the minimum of the MBF. Three truss problems with a different number of design variables are solved. The convergence to the minimum weight design was found to be monotonic and the algorithm is potentially robust for solving problems with a large number of design variables.

Khot, N. S.↗

NASA NTRS1977

DESAP 2: A structural design program with stress and buckling constraints. Volume 1: Theoretical and user's manual

DESAP 2 is described as a finite element program for computer-automated, minimum weight design of elastic structures with constraints on stresses (including local instability criteria) and buckling loads. No limits are placed on the number of load conditions for stress-constrained design, but only one of these load conditions can be chosen as the potential buckling load. A substantial portion of DESAP 2, particularly the analysis of the prebuckling state, is derived from the SOLID SAP finite element program. The stress-constrained design is based on the classical stress ratio method, which drives the design towards a fully stressed state. The constraints on the buckling load are handled by solving the appropriate optimality criterion by successive iterations. During each iteration, the element sizes determined by the stress ratio method are used as the minimum size constraints. The element subroutines are organized in a manner that permits the user to make additions and changes with a minimal programming effort. Consequently, DESAP 2 can readily be changed into a special-purpose program to handle the user's specific design requirements and failure criteria.

Kiusalaas, J.↗

NASA NTRSDate not supplied

Multifidelity Optimization with Transonic Flutter Constraints

This work considers static and dynamic aeroelastic optimization of a cantilevered platewing in transonic flow. Low- and high-fidelity aeroelastic predictions are fed into a standard trust region model management scheme in order to efficiently solve this expensive optimization problem with multifidelity methods. Differences in fidelity are entirely driven by different aerodynamic solvers: linear panel methods for the low-fidelity method, and inviscid CFD-based solvers for the high-fidelity response. The optimization problem utilizes shape, sizing, and trim variables to satisfy stress, trim, and flutter constraints, and is solved across a range of subsonic and transonic Mach numbers. The multifidelity method is able to provide a speed-up for all cases considered here, despite sizable inaccuracies in the low-fidelity response for transonic flows.

Bret K Stanford↗

DOE OSTI2024

Revealing Decision Conservativeness Through Inverse Distributionally Robust Optimization

This paper introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to infer the conservativeness level of a decision-maker, represented by the size of a Wasserstein metric-based ambiguity set, from the optimal decisions made using Forward Distributionally Robust Optimization (F-DRO). By leveraging the Karush-Kuhn-Tucker (KKT) conditions of the convex F-DRO model, we formulate I-DRO as a bi-linear program, which can be solved using off-the-shelf optimization solvers. Additionally, this formulation exhibits several advantageous properties. We demonstrate that I-DRO not only guarantees the existence and uniqueness of an optimal solution but also establishes the necessary and sufficient conditions for this optimal solution to accurately match the actual conservativeness level in F-DRO. Furthermore, we identify three extreme scenarios that may impact I-DRO effectiveness. Our case study applies F-DRO for power system scheduling under uncertainty and employs I-DRO to recover the conservativeness level of system operators. Numerical experiments based on an IEEE 5-bus system and a realistic NYISO 11-zone system demonstrate I-DRO performance in both normal and extreme scenarios. An extended version of this paper with additional analyses is available at li2024revealing.

distributionally robust optimization↗

NASA NTRS1987

Near Hartree-Fock quality GTO basis sets for the second-row atoms

Energy optimized, near Hartree-Fock quality Gaussian basis sets ranging in size from (17s12p) to (20s15p) are presented for the ground states of the second-row atoms for Na(2P), Na(+), Na(-), Mg(3P), P(-), S(-), and Cl(-). In addition, optimized supplementary functions are given for the ground state basis sets to describe the negative ions, and the excited Na(2P) and Mg(3P) atomic states. The ratios of successive orbital exponents describing the inner part of the 1s and 2p orbitals are found to be nearly independent of both nuclear charge and basis set size. This provides a method of obtaining good starting estimates for other basis set optimizations.

Partridge, Harry↗

NASA NTRS1987

Near Hartree-Fock quality GTO basis sets for the second-row atoms

Partridge, Harry↗

DOE OSTI2022

Transfer learning driven design optimization for inertial confinement fusion

Transfer learning is a promising approach to create predictive models that incorporate simulation and experimental data into a common framework. In this technique, a neural network is first trained on a large database of simulations and then partially retrained on sparse sets of experimental data to adjust predictions to be more consistent with reality. Previously, this technique has been used to create predictive models of Omega [Humbird et al., IEEE Trans. Plasma Sci. 48, 61–70 (2019)] and NIF [Humbird et al., Phys. Plasmas 28, 042709 (2021); Kustowski et al., Mach. Learn. 3, 015035 (2022)] inertial confinement fusion (ICF) experiments that are more accurate than simulations alone. Here, in this work, we conduct a transfer learning driven hypothetical ICF campaign in which the goal is to maximize experimental neutron yield via Bayesian optimization. The transfer learning model achieves yields within 5% of the maximum achievable yield in a modest-sized design space in fewer than 20 experiments. Furthermore, we demonstrate that this method is more efficient at optimizing designs than traditional model calibration techniques commonly employed in ICF design. Such an approach to ICF design could enable robust optimization of experimental performance under uncertainty.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Enhancing Building Energy Efficiency through Advanced Sizing and Dispatch Methods for Energy Storage

Energy storage and electrification of buildings hold great potential for future decarbonization. However, there are several technical and economic barriers that prevent large-scale adoption and integration of energy storage in buildings. These barriers include integration with building control systems, high capital costs, and the necessity to identify and quantify value streams for different stakeholders. To overcome these obstacles, it is crucial to develop advanced sizing and dispatch methods to assist planning and operational decision-making for integrating energy storage in buildings. This work develops simple and flexible optimal sizing and dispatch framework for thermal energy storage (TES) and battery energy storage (BES) systems in large-scale office building. The optimal sizes of TES, BES, as well as other building assets are determined in a joint manner instead of sequentially to avoid sub-optimal solutions. The interaction between the sizing at the planning stage and hourly or sub-hourly dispatch at the operating stage is explicitly modeled. The solution is determined considering both capital costs in optimal sizing and operational benefits in optimal dispatch. Comprehensive assessments are performed using simulation studies to quantify potential energy, economic, and emission benefits by different utility tariffs and climate locations, to improve our understanding of the techno-economic performance of different TES and BES systems, and to identify barriers for adopting energy storage for buildings. Finally, the proposed framework will provide guidance to a broad range of stakeholders to properly design energy storage in buildings and maximizes potential benefits, thereby advancing affordable building energy storage deployment and helping us accelerating the transition towards a cleaner and more equitable energy economy.

Yu, Mingyung↗

DOE OSTI2021

Improving the performance of first- and last-mile mobility services through transit coordination, real-time demand prediction, advanced reservations, and trip prioritization

Socio-demographic trends and recent economic development patterns have resulted in travel behavior changes that call for more flexible and accessible public transit options. Because flexible transit services vary in scope, size, and service type, new data-informed methods are useful to optimize services based on the specific needs of local communities and riders. In this study, real-world demand and vehicle trajectory data were used to evaluate and optimize system performance for an existing first-mile–last-mile (FMLM) service in Robinson Township, PA. A general FMLM model for arbitrary demand and service supply was then developed to quantify system performance—both travel time costs and day-to-day reliability—for various operational polices considering spatio-temporal demand variation and transportation network dynamics. Heuristics were used for optimal real-time vehicle routing in sizable real-world networks accommodating various service types and scopes. In this case study, total user costs were reduced by 18.6% when rides were coordinated with mainline fixed-route transit. Predictive routing strategies were shown to marginally improve system performance under sparse and variable spatio-temporal demand. The case study also highlights potentially large travel time and user reliability improvements—reductions of 51% and 53.8%, respectively—when trip requests were made in advance of their desired pickup time. Finally, we show that travel time reliability can be improved for time-inflexible trips with trip prioritization without increasing total user costs. These results were stable to changes in demand density.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1992

Development of the quasi-procedural method for use in aircraft configuration optimization

The performance of the quasi-procedural analysis system in optimization tasks is investigated. In particular, the quasi-procedural method is applied to the complete mission optimization of a medium-sized transport aircraft using a vortex-lattice aerodynamic model and finite element structural analysis of the wing and the tail. Some modifications and improvements to the system, required in order to complete this task, are described. The performance of the system is compared with that of the standard procedural system, and it is shown that the quasi-procedural approach reduces the analysis required to reach the optimum. The overall cost is shown to be strongly dependent on the analysis architecture and data structure.

Gage, P.↗

NASA NTRS2012

Deconvolution Methods and Systems for the Mapping of Acoustic Sources from Phased Microphone Arrays

Mapping coherent/incoherent acoustic sources as determined from a phased microphone array. A linear configuration of equations and unknowns are formed by accounting for a reciprocal influence of one or more cross-beamforming characteristics thereof at varying grid locations among the plurality of grid locations. An equation derived from the linear configuration of equations and unknowns can then be iteratively determined. The equation can be attained by the solution requirement of a constraint equivalent to the physical assumption that the coherent sources have only in phase coherence. The size of the problem may then be reduced using zoning methods. An optimized noise source distribution is then generated over an identified aeroacoustic source region associated with a phased microphone array (microphones arranged in an optimized grid pattern including a plurality of grid locations) in order to compile an output presentation thereof, thereby removing beamforming characteristics from the resulting output presentation.

Brooks, Thomas F.↗