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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Optimization of Air-Breathing Engine Concept

The design optimization of air-breathing propulsion engine concepts has been accomplished by soft-coupling the NASA Engine Performance Program (NEPP) analyzer with the NASA Lewis multidisciplinary optimization tool COMETBOARDS. Engine problems, with their associated design variables and constraints, were cast as nonlinear optimization problems with thrust as the merit function. Because of the large number of mission points in the flight envelope, the diversity of constraint types, and the overall distortion of the design space; the most reliable optimization algorithm available in COMETBOARDS, when used by itself, could not produce satisfactory, feasible, optimum solutions. However, COMETBOARDS' unique features-which include a cascade strategy, variable and constraint formulations, and scaling devised especially for difficult multidisciplinary applications-successfully optimized the performance of subsonic and supersonic engine concepts. Even when started from different design points, the combined COMETBOARDS and NEPP results converged to the same global optimum solution. This reliable and robust design tool eliminates manual intervention in the design of air-breathing propulsion engines and eases the cycle analysis procedures. It is also much easier to use than other codes, which is an added benefit. This paper describes COMETBOARDS and its cascade strategy and illustrates the capabilities of the combined design tool through the optimization of a high-bypass- turbofan wave-rotor-topped subsonic engine and a mixed-flow-turbofan supersonic engine.

Patnaik, Surya N.↗
NASA NTRS2002

Design and architecture of the Mars relay network planning and analysis framework

In this paper we describe the design and architecture of the Mars Network planning and analysis framework that supports generation and validation of efficient planning and scheduling strategy. The goals are to minimize the transmitting time, minimize the delaying time, and/or maximize the network throughputs. The proposed framework would require (1) a client-server architecture to support interactive, batch, WEB, and distributed analysis and planning applications for the relay network analysis scheme, (2) a high-fidelity modeling and simulation environment that expresses link capabilities between spacecraft to spacecraft and spacecraft to Earth stations as time-varying resources, and spacecraft activities, link priority, Solar System dynamic events, the laws of orbital mechanics, and other limiting factors as spacecraft power and thermal constraints, (3) an optimization methodology that casts the resource and constraint models into a standard linear and nonlinear constrained optimization problem that lends itself to commercial off-the-shelf (COTS)planning and scheduling algorithms.

Mars relay network planning analysis↗
DOE OSTI2018

Ageless Aluminum-Cerium-Based Alloys in High-Volume Die Casting for Improved Energy Efficiency

Strong chemical reactions between Al and Ce lead to the formation of intermetallics with exceptional thermal stability. The rapid formation of intermetallics directly from the liquid phase during solidification of Al-Ce alloys leads to an ultrafine microconstituent structure that effectively strengthens as-cast alloys without further microstructural optimization via thermal processing. Die casting is a high-volume manufacturing technology that accounts for greater than 40% of all cast Al products, whereas Ce is highly overproduced as a waste product of other rare earth element (REE) mining. Reducing heat treatments would stimulate significant improvements in manufacturing energy efficiency, exceeding (megatonnes/year) per large-scale heat-treatment line. In this study, multiple compositions were evaluated with wedge mold castings to test the sensitivity of alloys to the variable solidification rate inherent in high-pressure die casting. Once a suitable composition was determined, it was successfully demonstrated at 800 lbs/h in a 600-ton die caster, after which the as-die cast parts performed similarly to ubiquitous A380 in the same geometry without requiring heat treatment. Furthermore, this work demonstrates the compatibility of Al REE alloys with high-volume die-casting applications with minimal heat treatments.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Cascade Optimization Strategy for Aircraft and Air-Breathing Propulsion System Concepts

Design optimization for subsonic and supersonic aircraft and for air-breathing propulsion engine concepts has been accomplished by soft-coupling the Flight Optimization System (FLOPS) and the NASA Engine Performance Program analyzer (NEPP), to the NASA Lewis multidisciplinary optimization tool COMETBOARDS. Aircraft and engine design problems, with their associated constraints and design variables, were cast as nonlinear optimization problems with aircraft weight and engine thrust as the respective merit functions. Because of the diversity of constraint types and the overall distortion of the design space, the most reliable single optimization algorithm available in COMETBOARDS could not produce a satisfactory feasible optimum solution. Some of COMETBOARDS' unique features, which include a cascade strategy, variable and constraint formulations, and scaling devised especially for difficult multidisciplinary applications, successfully optimized the performance of both aircraft and engines. The cascade method has two principal steps: In the first, the solution initiates from a user-specified design and optimizer, in the second, the optimum design obtained in the first step with some random perturbation is used to begin the next specified optimizer. The second step is repeated for a specified sequence of optimizers or until a successful solution of the problem is achieved. A successful solution should satisfy the specified convergence criteria and have several active constraints but no violated constraints. The cascade strategy available in the combined COMETBOARDS, FLOPS, and NEPP design tool converges to the same global optimum solution even when it starts from different design points. This reliable and robust design tool eliminates manual intervention in the design of aircraft and of air-breathing propulsion engines where it eases the cycle analysis procedures. The combined code is also much easier to use, which is an added benefit. This paper describes COMETBOARDS and its cascade strategy and illustrates the capability of the combined design tool through the optimization of a subsonic aircraft and a high-bypass-turbofan wave-rotor-topped engine.

Patnaik, Surya N.↗
DOE OSTI2018

Optimization of Mold Flux for the Continuous Casting of Cr-Contained Steels

To compensate the negative effect caused by the absorption of chromium oxide inclusions during the casting process of Cr-contained steels, a new mold flux system has been designed and investigated. The melting temperature range of the newly designed mold flux system is from [1124 K to 1395 K (851 °C to 1122 °C)]. The viscosity at 1573 K (1300 °C) and the break temperature increase with the addition of MnO and Cr{sub 2}O{sub 3} but decrease with the addition of B{sub 2}O{sub 3}. The crystalline fraction of mold flux decreases from 81 to 42.1 pct with the addition of MnO and Cr{sub 2}O{sub 3}, and then further decreases to 25.3 pct with the addition of B{sub 2}O{sub 3}; however, it improves from 54.4 to 81.5 pct when the basicity increases. Besides, the heat-transfer ability of mold flux is inverse to the crystallization ratio of the slag. The comprehensive study of the properties for the four designed mold fluxes suggests that the mold flux with 1.15 basicity-3.01 pct B{sub 2}O{sub 3}-1.10 pct MnO-2.10 pct Cr{sub 2}O{sub 3} shows the best properties for the continuous casting of Cr-contained steels.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Solid Phase Gradient Alloying Method via ShAPE

Alloying has been used to confer desirable properties to various metallic systems since the bronze age. For example, Ni, Mn, and Cr are alloyed into an Fe matrix to make steel, which has improved strength and corrosion resistance (as displayed in Fig. 1). In addition to the type of alloying elements, the amount of alloying elements added into a matrix is also very critical for a material’s mechanical property, physical property, machinability, and cost. Conventionally, new alloys are discovered by combining alloy precursors and elemental constituents into a mixture and melting them together. The solidified product or ingot represents a usually non-homogeneous combination of the chemistry with a microstructure dictated by the physics of solidification. It is time and energy intensive to optimize the alloying amounts via the casting process and hence, economically not conducive to rapid alloy discovery. In addition, the cast microstructure seen in the as-cast ingot is often not the ideal, nor even desired structure for optimized performance. Cast materials often need further processing such as homogenization, annealing, and deformation work put in through rolling, forging, extruding, etc. to have favorable microstructures and properties. A faster method to discover new alloy combinations and evaluate them in their worked or processed form is needed. Recently, Laser Engineered Net Shaping was applied to fabricate gradient compositional material for alloy designing. However, the mechanical properties of this gradient alloy were poor due to the existence of impurities, oxidation and cracks that are inherent in the melt-solidification process. Because of these limitations, we propose to use a solid-phase process (ShAPE) to create bulk materials (extrudates) that vary in composition from one end of the extruded solid to the other. Various manufacturing methods for alloy design including conventional casting method, laser based combinatorial method and current solid phase gradient alloying method are displayed and compared in Fig. 2. ShAPE machine and a schematic of ShAPE process are displayed in Fig. 3. Starting material is processed by a rotating and plunging die to form an extrudate. We are proposing through this methodology to invent a new, bulk-scale combinatorial technique. With this novel technique, alloying element can be dissolved into the matrix with a continued gradient without bulk melting. Formation of inter-metallics and defects originating from melt processing can be avoided. In addition, the ShAPE process creates the mixed alloy chemistry, and meanwhile subjects the material to severe plastic strain, which induces the favorable “worked” microstructure. Products from the ShAPE process can be tested in hardness directly providing a path to rapid evaluation of mechanical properties. The ability to create graded structures using friction stir processing (FSP) has been demonstrated, however using the ShAPE process we believe will lead to much faster and higher fidelity results. When combined with high throughput screening methods of physical, mechanical and microstructural property characterization, efficiency and accuracy of alloy design can be significantly improved.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments

Here, we present a novel stochastic approach to binary optimization suited for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations. The OED utility function, namely, the regularized optimality criterion, is cast into a stochastic objective function in the form of an expectation over a multivariate Bernoulli distribution. The probabilistic objective is then solved by using a stochastic optimization routine to find an optimal observational policy. This formulation (a) is generally applicable to binary optimization problems with soft constraints and is ideal for OED and sensor placement problems; (b) does not require differentiability of the original objective function (e.g., a utility function in OED applications) with respect to the design variable, and thus it enables direct employment of sparsity-enforcing penalty functions such as $\ell_0$, without needing to utilize a continuation procedure or apply a rounding technique; (c) exhibits much lower computational cost than traditional gradient-based relaxation approaches; and (d) can be applied to both linear and nonlinear OED problems with proper choice of the utility function. The proposed approach is analyzed from an optimization perspective with detailed convergence analysis of the optimization approach and is also analyzed from a machine learning perspective with correspondence to policy gradient reinforcement learning. The approach is demonstrated numerically by using an idealized two-dimensional Bayesian linear inverse problem and validated by extensive numerical experiments carried out for sensor placement in a parameter identification setup.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Application of A Dual-Quaternion Six Degree-of-Freedom Guidance to Human-Scale Mars Entry, Descent, and Landing

Landing humans on Mars comes with many challenges, including the execution of a safe and precise entry, descent, and landing (EDL) sequence. Various NASA studies have shown that there are a variety of EDL guidance methods that potentially offer solutions to the human-scale EDL precision landing problem and work is ongoing to assess new and novel methods. As part of these ongoing studies, a dual-quaternion-based six degree-of-freedom guidance algorithm was implemented in the Program to Optimize Simulated Trajectories II (POST2), a NASA-and industry-standard spacecraft trajectory and vehicle design tool. This algorithm considers both translational and rotational dynamics and casts the trajectory optimization problem as a quadratically constrained quadratic program (QCQP) with various constraints at discrete nodes throughout the trajectory. The QCQP problem is solved via an alternating direction method of multipliers (ADMM) approach, and the output is a discretized optimal trajectory. The guidance is applied to a NASA reference human-scale Mars EDL system, and results are compared and discussed.

Optimization↗
NASA NTRSDate not supplied

Application of A Dual-Quaternion Six Degree-of-Freedom Guidance to Human-Scale Mars Entry, Descent, and Landing

Landing humans on Mars comes with many challenges, including the execution of a safe and precise entry, descent, and landing (EDL) sequence. Various NASA studies have shown that there are a variety of EDL guidance methods that potentially offer solutions to the human-scale EDL precision landing problem and work is ongoing to assess new and novel methods. As part of these ongoing studies, a dual-quaternion-based six degree-of-freedom guidance algorithm was implemented in the Program to Optimize Simulated Trajectories II (POST2), a NASA-and industry-standard spacecraft trajectory and vehicle design tool. This algorithm considers both translational and rotational dynamics and casts the trajectory optimization problem as a quadratically constrained quadratic program (QCQP) with various constraints at discrete nodes throughout the trajectory. The QCQP problem is solved via an alternating direction method of multipliers (ADMM) approach, and the output is a discretized optimal trajectory. The guidance is applied to a NASA reference human-scale Mars EDL system, and results are compared and discussed.

Optimization↗
NASA NTRS1992

Vision-based stereo ranging as an optimal control problem

The recent interest in the use of machine vision for flight vehicle guidance is motivated by the need to automate the nap-of-the-earth flight regime of helicopters. Vision-based stereo ranging problem is cast as an optimal control problem in this paper. A quadratic performance index consisting of the integral of the error between observed image irradiances and those predicted by a Pade approximation of the correspondence hypothesis is then used to define an optimization problem. The necessary conditions for optimality yield a set of linear two-point boundary-value problems. These two-point boundary-value problems are solved in feedback form using a version of the backward sweep method. Application of the ranging algorithm is illustrated using a laboratory image pair.

Menon, P. K. A.↗
NASA NTRS2017

Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

Adaptive Control↗
DOE OSTI2025

Classical optimization with imaginary-time block encoding on quantum computers: The MaxCut problem

Optimization problems in finance, physics, and computer science are typically very hard to tackle in classical computing; quantum computing could help speed up computations and provide efficient methods for tackling large problems. Typically, to treat a problem with a quantum computer, the optimal solution is cast as the ground state of a diagonal Hamiltonian. Here, we develop a method, called imaginary-time evolution block encoding (ITE-BE), based on a recent imaginary-time algorithm, which requires no variational parameter optimization, as all parameters can be derived analytically from the target Hamiltonian. We also demonstrate that our method can be successfully combined with other quantum algorithms such as the quantum approximate optimization algorithm (QAOA). For illustration, here we study the MaxCut problem. We find that the QAOA ansatz increases the postselection success of ITE-BE, and shallow QAOA circuits, when boosted with ITE-BE, achieve better performance than deeper QAOA circuits. For the special case of the transverse initial state, we adapt our block-encoding scheme to allow for a deterministic application of the first layer of the circuit.

Zhong, Dawei [University of Southern California, L↗
DOE OSTI2026

Oxygen Effects and Selective Oxidation of Group IV Alloying Additions in Group V-Based Refractory Multi-principal Element Alloys

Refractory multi-principal element alloys (RMPEAs) hold significant potential for advancing ultra-high-temperature technologies due to their remarkable strength retention under these conditions. However, the beneficial effects of alloying on microstructural evolution and mechanical properties are often obscured by the presence of interstitial alloying elements. The intricate interactions between substitutional alloying elements of Groups IV, V, and VI and interstitial content, whether intentional or incidental, remain poorly understood. In this study, we investigate the impact of dissolved oxygen on the microstructural evolution and stability of RMPEAs primarily composed of Group V elements, Nb and V, along with Group IV elements Ti, Zr, and Hf. We show that the strong affinity of oxygen for Group IV elements Zr and Hf leads to the internal precipitation of oxides during heat treatment, which competes with the homogenization of the as-cast dendritic microstructure. Here, we demonstrate that careful control and design of oxygen content and Group IV alloying additions are essential to minimize micro-segregation and prevent the detrimental precipitation of internal oxides. To address these challenges, we propose employing non-equilibrium solidification calculations to predict and optimize as-cast solidification structures, thereby reducing the reliance on homogenization processes.

Alloy design↗
DOE OSTI2019

Design and Application of CSC-Roll for Heavy Reduction of the Bloom Continuous Casting Process

Center quality control is a key issue affecting large-section bloom production and product quality. The central convex roll could avoid the bloom side part and yield a high reduction amount, which benefit the implement of heavy reduction (HR) for bloom continuous casting process without upgrading the mechanical and hydraulic system of withdrawal and straightening machine. In this work, a curving surface convex roll (CSC-Roll), which could significantly improve bloom center quality, was designed by finite element simulation for a 360 mm × 450 mm #45 steel continuous casting bloom. The optimal roll surface shape of the CSC-Roll was determined based on an analysis of the distribution of the reduction amount in the bloom center and the strain of the bloom centerline and inner surface. The calculation results showed that the optimal size of the CSC-Roll was 200 mm in convex platform region length, 30 mm in convex platform region height, and 80 mm in gradient curvature region length. The bloom heat transfer and deformation behavior in the CSC-Roll reduction process were then analyzed. The results showed that in the CSC-Roll HR process, 61.71 pct of the reduction amount could be transmitted to the inner side of the porosity zone. Macrographs of the 360 mm × 450 mm #45 steel continuous casting bloom proved that the bloom center quality was significantly improved after CSC-Roll HR was applied.

36 MATERIALS SCIENCE↗
DOE OSTI2017

In Situ GIWAXS Analysis of Solvent and Additive Effects on PTB7 Thin Film Microstructure Evolution during Spin Coating

The influence of solvent and processing additives on the pathways and rates of crystalline morphology formation for spin-coated semiconducting PTB7 (poly[[4,8-bis[(2- ethylhexyl)oxy]benzo[1,2-b:4,5-b']dithiophene-2,6-diyl][3-fluoro-2-[(2-ethylhexyl)- carbonyl]-thieno[3,4-b]thiophenediyl]]) thin films is investigated by in situ grazing incident wide angle x-ray scattering (GIWAXS) and optical reflectance, to better understand polymer solar cell (PSC) optimization approaches. In situ characterization of PTB7 film formation from chloroform (CF), chlorobenzene (CB), and 1,2-dichlorobenzene (DCB) solutions, as well as CB solutions with 1% and 3% v/v of the processing additives 1-chloronapthalene (CN), diphenyl ether (DPE), and 1,8-diiodooctane (DIO), reveals multiple crystallization pathways with: i) single-solvent systems exhibiting rapid (<3s) crystallization after a solvent boiling point-dependent film thinning transition, ii) solvent + additive systems exhibiting different crystallization pathways and crystallite formation times from minutes (CN, DPE) to 2 1.5 hours (DIO). Here, identifying crystalline intermediates has implications for bulk-heterojunction PSC morphology optimization via optimized spin-casting processes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Low-Vapor-Pressure Solvent Additives Function as Polymer Swelling Agents in Bulk Heterojunction Organic Photovoltaics

Here, bulk heterojunction (BHJ) photovoltaics based on blends of conjugated polymers and fullerenes require an optimized nanoscale morphology. Casting BHJ films using solvent additives such as 1,8-diiodooctane (DIO), 1,8-octanedithiol (ODT), chloronapthalene (CN), or diphenyl ether (DPE) often helps achieve this proper morphology: adding just a few volume percent of additive to the casting solution can improve polymer/fullerene mixing or phase separation, so that solvent additives have become staples in producing high-efficiency BHJ solar cells. The mechanism by which these additives improve BHJ morphology, however, is poorly understood. Here, we investigate how these additives control polymer/fullerene mixing by taking advantage of sequential processing (SqP), in which the polymer is deposited first and then the fullerene is intercalated into the polymer underlayer in a second processing step using a quasi-orthogonal solvent. In this way, SqP isolates the role of the additives’ interactions with the polymer and the fullerene.

1,8-diiodooctane↗
DOE OSTI2020

Layer-Parallel Training of Deep Residual Neural Networks

Residual neural networks (ResNets) are a promising class of deep neural networks that have shown excellent performance for a number of learning tasks, e.g., image classification and recognition. Mathematically, ResNet architectures can be interpreted as forward Euler discretizations of a nonlinear initial value problem whose time-dependent control variables represent the weights of the neural network. Hence, training a ResNet can be cast as an optimal control problem of the associated dynamical system. For similar time-dependent optimal control problems arising in engineering applications, parallel-in-time methods have shown notable improvements in scalability. This paper demonstrates the use of those techniques for efficient and effective training of ResNets. The proposed algorithms replace the classical (sequential) forward and backward propagation through the network layers with a parallel nonlinear multigrid iteration applied to the layer domain. This adds a new dimension of parallelism across layers that is attractive when training very deep networks. From this basic idea, we derive multiple layer-parallel methods. The most efficient version employs a simultaneous optimization approach where updates to the network parameters are based on inexact gradient information in order to speed up the training process. Finally, using numerical examples from supervised classification, we demonstrate that the new approach achieves a training performance similar to that of traditional methods, but enables layer-parallelism and thus provides speedup over layer-serial methods through greater concurrency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Fan Fuel Casting Final Report

LANL was approached to provide material and design guidance for a fan-shaped fuel element. A total of at least three castings were planned. The first casting is a simple billet mold to be made from high carbon DU-10Mo charge material. The second and third castings are for optimization of the actual fuel plate mold. The experimental scope for optimization is only broad enough for a second iteration of the mold design. It is important to note that partway through FY17, this project was cancelled by the sponsor. This report is being written in order to capture the knowledge gained should this project resume at a later date.

42 ENGINEERING↗