Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Point 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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Sequential linear integer programming for integer optimal control with total variation regularization

We propose a trust-region method that solves a sequence of linear integer programs to tackle integer optimal control problems regularized with a total variation penalty. The total variation penalty implies that the considered integer control problems admit minimizers. We introduce a local optimality concept for the problem, which arises from the infinite-dimensional perspective. In the case of a one-dimensional domain of the control function, we prove convergence of the iterates produced by our algorithm to points that satisfy first-order stationarity conditions for local optimality. We demonstrate the theoretical findings on a computational example.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Aerodynamic shape optimization using sensitivity analysis on third-order Euler equations

Two major advancements of an aerodynamic optimization method with two design variables are described. The first is represnted by an improved flow prediction method that uses the third-order accurate discretization of the Euler equations. This method makes it possible to predict the flowfield of a perturbed shape which generates shocks and other large gradients without intermediate CFD analysis. The second advancement is the use of every surface grid point as a design variable in the aerodynamic shape optimization problem. The improved algorithm is demonstrated by optimizing the ramp shape of a scramjet-afterbody configuration for maximum axial thrust. It is concluded that the improved flow-field prediction method eliminates most of the flow analysis and a priori guessing of all possible shapes from which the optimum is to be selected.

Baysal, Oktay↗
NASA NTRS1990

Optimal helicopter trajectory planning for terrain following flight

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Menon, P. K. A.↗
NASA NTRS1996

Observations Regarding Use of Advanced CFD Analysis, Sensitivity Analysis, and Design Codes in MDO

Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect our perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conventional optimization (analysis - SA codes) and simultaneous analysis and design optimization (design code) using both Euler and Navier-Stokes flow approximations. The amount of computational resources required for aerodynamic design using CFD via analysis - SA codes is greater than that required for design codes. Thus, an MDO formulation that utilizes the more efficient design codes where possible is desired. However, in the aerovehicle MDO problem, the various disciplines that are involved have different design points in the flight envelope; therefore, CFD analysis - SA codes are required at the aerodynamic 'off design' points. The suggested MDO formulation is a hybrid multilevel optimization procedure that consists of both multipoint CFD analysis - SA codes and multipoint CFD design codes that perform suboptimizations.

Newman, Perry A.↗
NASA NTRS1988

An Experimental and Analytical Evaluation of a Biaxial Test for Determining Shear Properties of Composite Materials

The results of an experimental and analytical investigation of a biaxial tension/compression test for determining shear properties of composite materials are reported. Using finite element models of isotropic and orthotropic laminates, a specimen geometry was optimized. A kinematic fixture was designed to introduce an equal and opposite pair of forces into a specimen with a one inch square test section. Aluminum and several composite laminates with the optimized geometry and a configuration with large stress gradients were tested in the fixture. The specimens were instrumented with strain gages in the center of the test section for shear stiffness measurements. Pure shear strain was measured. The results from the experiments correlated well with finite element results. Failure of the specimens occurred through the center of the test section and appeared to have initiated at the high stress points. The results lead to the conclusion that the optimized specimen is suitable for determining shear modulus for composite materials. Further revisions to the specimen geometry are necessary if the method is to give shear strength data.

Kennedy, John M.↗
NASA NTRSDate not supplied

Adaptive Learning for Reliability Analysis using Support Vector Machines

A novel algorithm is presented for adaptive learning of an unknown function that separates two regions of a domain.In the context of reliability analysis these two regions represent the failure domain, where a set of constraints or requirements are violated, and a safe domain where they are satisfied. The Limit State Function (LSF) separates these two regions. Evaluating the constraints for a given parameter point requires the evaluation of a computational model that may well be expensive. For this reason we wish to construct a meta-model that can estimate the LSFas accurately as possible, using only a limited amount of training data. This work presents an adaptive strategy employing a Support Vector Machine (SVM) as a meta-model to provide a semi-algebraic approximation of the LSF.We describe an optimization process that is used to select informative parameter points to add to training data at each iteration to improve the accuracy of this approximation. A formulation is introduced for bounding the predictions of the meta-model; in this way we seek to incorporate this aspect of Gaussian Process Models (GPMs) within anSVM meta-model. Finally, we apply our algorithm to two benchmark test cases, demonstrating performance that is comparable with, if not superior, to a standard technique for reliability analysis that employs GPMs

Adaptive learning↗
NASA NTRS1997

Feedback Implementation of Zermelo's Optimal Control by Sugeno Approximation

This paper proposes an approach to implement optimal control laws of nonlinear systems in real time. Our methodology does not require solving two-point boundary value problems online and may not require it off-line either. The optimal control law is learned using the original Sugeno controller (OSC) from a family of optimal trajectories. We compare the trajectories generated by the OSC and the trajectories yielded by the optimal feedback control law when applied to Zermelo's ship steering problem.

Clifton, C.↗
DOE OSTI2020

PyCDFT: A Python package for constrained density functional theory

In this paper, we present PyCDFT, a Python package to compute diabatic states using constrained density functional theory (CDFT). PyCDFT provides an object-oriented, customizable implementation of CDFT, and allows for both single-point self-consistent-field calculations and geometry optimizations. PyCDFT is designed to interface with existing density functional theory (DFT) codes to perform CDFT calculations where constraint potentials are added to the Kohn–Sham Hamiltonian. Here, we demonstrate the use of PyCDFT by performing calculations with a massively parallel first-principles molecular dynamics code, Qbox, and we benchmark its accuracy by computing the electronic coupling between diabatic states for a set of organic molecules. We show that PyCDFT yields results in agreement with existing implementations and is a robust and flexible package for performing CDFT calculations. The program is available at https://dx.doi.org/10.5281/zenodo.3821097.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore

The planning of district-scale electric grids, i.e., distribution grids, has traditionally relied on finding the most cost-effective design such that they are able to supply the peak loads in a district. With the advent of electric demand side flexibility (DSF), there is the opportunity to reshape peak loads such that the investment cost of the electric grid decreases in exchange for a minor increase in the operation cost. This paper formulates an optimal planning approach for the electric grid at the district scale, which incorporates the DSF from thermal building systems, e.g., heating ventilation and air-conditioning (HVAC) systems. The problem is formulated as a mixed-integer linear program (MILP) and aims at minimizing the investment cost for the grid along with the operation cost of the flexible loads. This is subjected to the fixed electricity demand and thermal comfort constraints of building occupants. To this end, linear models for the thermal comfort in the buildings and the power flow in electric grid are considered. The approach is tested on a district planning test case based in Singapore, where the results show up to 30.9 % reductions in investment cost and up to 3.7 % reduction in total annualized cost. Urban planning authorities, developers and utility companies can all benefit from the presented approach to make optimized investment decisions. For building operators, the results point to the need of adopting their control systems for DSF.

Troitzsch, Sebastian↗
DOE OSTI2022

Forward and inverse modeling of fault transmissibility in subsurface flows

Characterizing physical properties of faults, such as their transmissibility, is crucial for performing predictive numerical simulation of subsurface flows, such as those encountered in petroleum engineering and remediation of subsurface contamination. Here, this paper provides a complete investigation of the inverse problem for fault transmissibility in subsurface flow models, under appropriate assumptions on fault structure. In particular, the following aspects are considered: 1) fault modeling and well-posedness of the forward problem; 2) finite element (FEM) discretizations of the forward problem and their rigorous a priori convergence analysis; 3) Well-posedness of the Bayesian inverse problem, FEM discretization of the infinite dimensional Bayesian inverse formulation, and its rigorous a priori analysis. Moreover, computation of the maximum a posteriori (MAP) point via fast inexact Newton-conjugate gradient optimization and a Laplace approximation of the Bayesian posterior are also presented. Numerical results illustrate the use of the proposed fault model in forward and inverse problems for subsurface flows in two dimensional domains with multiple faults.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

From electronic structure to model application of key reactions for gasoline/alcohol combustion: Hydrogen-atom abstraction by $CH_3O\dot{O}$ radicals

Hydrogen atom abstraction by methyl peroxy ($CH_3O\dot{O}$) radicals can play an important role in gasoline/ethanol interacting chemistry for fuels that produce high concentrations of methyl radicals. Detailed kinetic reactions for hydrogen atom abstraction by $CH_3O\dot{O}$ radicals from the components of FGF-LLNL (a gasoline surrogate) including cyclopentane, toluene, 1-hexene, n -heptane, and isooctane have been systematically studied in this work. Here, the M06-2X/6-311 ++ G(d,p) level of theory was used to obtain the optimized structure and vibrational frequency for all stationary points and the low-frequency torsional modes. The 1-D hindered rotor treatment for low-frequency torsional modes was treated at M06-2X/6-31G level of theory. The UCCSD(T)-F12a/cc-pVDZ-F12 and QCISD(T)/CBS level of theory were used to calculate single point energies for all species. High pressure limiting rate constants for all hydrogen atom abstraction channels were performed using conventional transition state theory with unsymmetric tunneling corrections. Individual rate constants are reported in the temperature range from 298.15 to 2000 K. Our computed results show that the abstraction of allylic hydrogen atoms from 1-hexene is the fastest at low temperatures. When the temperature increases, the hydrogen atom abstraction reaction channel at the primary alkyl site gradually becomes dominant. Thermodynamics properties for all stable species and high-pressure limiting rate constants for each reaction pathway obtained in this work were incorporated into the latest gasoline surrogate/ethanol model to investigate the influence of the rate constants calculated here on model predicted ignition delay times.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Variational actor-critic algorithms,

We introduce a class of variational actor-critic algorithms based on a variational formulation over both the value function and the policy. The objective function of the variational formulation consists of two parts: one for maximizing the value function and the other for minimizing the Bellman residual. Besides the vanilla gradient descent with both the value function and the policy updates, we propose two variants, the clipping method and the flipping method, in order to speed up the convergence. We also prove that, when the prefactor of the Bellman residual is sufficiently large, the fixed point of the algorithm is close to the optimal policy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences

We describe our development of ab initio protein-ligand binding pose prediction models based on transformers and binding affinity prediction models based on the neural tangent kernel (NTK). Folding both protein and ligand, the TwoFold models achieve efficient and quality predictions matching state-of-the-art implementations while additionally reconstructing protein structures. In conclusion, solving NTK models points to a new use case for highly optimized linear solver benchmarking codes on HPC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Multistage Stochastic Transmission Expansion Algorithm for Wide-Area Planning under Uncertainty

The overall objective for this project was to develop and demonstrate a set of methods for solving the transmission investment problem for a large network considering many possible scenarios of future conditions and multiple decision points when investments can be made. Project sub-objectives achieved this goal through a succession of extending the methods to apply to problems with increasing complexity or additional features, including the number of decision points, whether generation and transmission are co-optimized, and whether AC or DC power flow is used. A transmission model was developed for the Western Electric Coordinating Council (WECC) region, the high-voltage transmission system that serves the western third of the continental U.S. Using a dataset provided by WECC and by researchers from John Hopkins University, we have validated and demonstrated the model and used it to compare the new method for solving multi-stage stochastic transmission planning to several state-of-the-art techniques. The project has resulted in several key outcomes and achievements: The covariance-based method for choosing a small set of hours to represent short-term variability has superior performance in terms of accuracy to existing methods, including K-means clustering and Importance Sampling; The combined partitioning method for long-term uncertainty with the nested clustering approach for choosing representative hours for each long-term group has superior accuracy for equivalent computational effort compared with existing methods; Using the partitioning/clustering method combined with Sample Average Approximation provides both statistical bounds on the quality of the solution and at the same time, a complete investment plan for all contingencies in the full uncertainty set; no existing methods can provide both at the same time; The method is demonstrated to work well for choosing both transmission and generation investments; A variant on the method allows for both scenario selection and simultaneous correction for the error from the DC power flow approximation to provide a tractable method for AC power flow-based transmission planning under uncertainty; The method applied to the WECC case study demonstrates the additional value to the system operator and the consumer of identifying flexible investment options in the near-term decisions. In particular, the case study exhibits significant option value in postponing some transmission additions that appear useful but in some long-term system states create new congestion problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Multi-mechanistic Strategies for Novel Solid Electrolytes with Superior Properties

Despite a wide range of solid electrolyte phases, most of them only exist at high temperatures. The challenge is to tailor the chemical compositions of solid electrolyte materials that yield high ionic conductivities and low activation energies at ambient temperature. This is crucial for the development of all-solid-state batteries that are both powerful and safe. Here, we report our recent works to meet this challenge by utilizing multiple mechanistic principles and clusters as the building blocks. We show that the atomic-level interactions that govern the fast-ion conduction can be optimized by incorporating polyanion dynamics, non-stoichiometry, point defects and strong ionic correlations. Specifically, two case studies of Li/Na solid electrolytes will be covered, including lithium solid electrolytes (SE) with record-high ionic conductivities at room temperature (over 100 mS/cm) and sodium SE with record-low activation energies (< 0.1 eV).

Fang, Hong↗
DOE OSTI2026

Single-Phase to Split-Phase Inverters with Advanced Grid Support Functions for Grid-Interactive Applications

This work presents a cost-effective single-phase to split-phase inverter with a reduced switch count, achieving grid interactive performance while maintaining operational efficiency. The proposed system integrates an Andronov-Hopf oscillator based secondary controller, which inherently embeds a nonlinear resistive droop architecture, ensuring rapid dynamic response. A Lyapunov energy function-based primary control enhances transient stability and regulation, while an internal model-based point of common coupling voltage estimation enables cost optimization without additional sensors. Equipped with advanced grid support functionalities, the inverter facilitates seamless distribution system operation with enhanced robustness. The effectiveness of the proposed architecture and control strategy is validated through MATLAB/Simulink and PLECS simulations, demonstrating its feasibility for high-performance grid-supportive applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Opportunities for Bright Beam Generation at the Argonne Wakefield Accelerator (AWA)

Bright electron beams have played a critical role in many recent advances in accelerator technology. Producing bright beams via photo-emission is ultimately limited by the mean transverse energy (MTE), which is determined by the photocathode. This paper discusses the opportunity to generate bright electron beams using an upgraded version of the Argonne Wakefield Accelerator (AWA) photo-injector. The focus of this study is to examine the optimal configurations of the AWA photo-injector to produce 100 pC with a ∼100 nm transverse emittance (corresponding to a 5D brightness B5≥1015 A·m−2). The numerical optimization of the AWA photo-injector operating point, including realistic electromagnetic field maps, is presented for the different types of photocathodes under consideration.

Frame, Emily↗