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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 109 records · Page 6

Foam Core Shielding for Spacecraft

A foam core shield (FCS) system is now being developed to supplant multilayer insulation (MLI) systems heretofore installed on spacecraft for thermal management and protection against meteoroid impacts. A typical FCS system consists of a core sandwiched between a face sheet and a back sheet. The core can consist of any of a variety of low-to-medium-density polymeric or inorganic foams chosen to satisfy application-specific requirements regarding heat transfer and temperature. The face sheet serves to shock and thereby shatter incident meteoroids, and is coated on its outer surface to optimize its absorptance and emittance for regulation of temperature. The back sheet can be dimpled to minimize undesired thermal contact with the underlying spacecraft component and can be metallized on the surface facing the component to optimize its absorptance and emittance. The FCS systems can perform better than do MLI systems, at lower mass and lower cost and with greater volumetric efficiency.

Adams, Marc↗

Neural Network and Response Surface Methodology for Rocket Engine Component Optimization

The goal of this work is to compare the performance of response surface methodology (RSM) and two types of neural networks (NN) to aid preliminary design of two rocket engine components. A data set of 45 training points and 20 test points obtained from a semi-empirical model based on three design variables is used for a shear coaxial injector element. Data for supersonic turbine design is based on six design variables, 76 training, data and 18 test data obtained from simplified aerodynamic analysis. Several RS and NN are first constructed using the training data. The test data are then employed to select the best RS or NN. Quadratic and cubic response surfaces. radial basis neural network (RBNN) and back-propagation neural network (BPNN) are compared. Two-layered RBNN are generated using two different training algorithms, namely solverbe and solverb. A two layered BPNN is generated with Tan-Sigmoid transfer function. Various issues related to the training of the neural networks are addressed including number of neurons, error goals, spread constants and the accuracy of different models in representing the design space. A search for the optimum design is carried out using a standard gradient-based optimization algorithm over the response surfaces represented by the polynomials and trained neural networks. Usually a cubic polynominal performs better than the quadratic polynomial but exceptions have been noticed. Among the NN choices, the RBNN designed using solverb yields more consistent performance for both engine components considered. The training of RBNN is easier as it requires linear regression. This coupled with the consistency in performance promise the possibility of it being used as an optimization strategy for engineering design problems.

Vaidyanathan, Rajkumar↗

Optimal sensing on an asymmetric exceptional surface

We study the connection between exceptional points (EPs) and optimal parameter estimation, in a simple system consisting of two counterpropagating traveling wave modes in a microring resonator. The unknown parameter to be estimated is the strength of a perturbing cross-coupling between the two modes. Partially reflecting the output of one mode into the other creates a non-Hermitian Hamiltonian that exhibits a family of EPs, creating an exceptional surface (ES). We use a fully quantum treatment of field inputs and noise sources to obtain a quantitative bound on the estimation error by calculating the quantum Fisher information (QFI) in the output fields, whose inverse gives the Cramér-Rao lower bound on the mean-squared error of any unbiased estimator. We determine the bounds for two input states, namely, a semiclassical coherent state and a highly nonclassical NOON state. We find that the QFI is enhanced in the presence of an EP for both of these input states and that both states can saturate the Cramér-Rao bound. We then identify idealized yet experimentally feasible measurements that achieve the minimum bound for these two input states. We also investigate how the QFI changes for parameter values that do not lie on the ES, finding that these can have a larger QFI, suggesting alternative routes to optimize the parameter estimation for this problem.

Exceptional points↗

Optimization of Random Phase Approximation Calculations for Improved Energies of Molecules, Solids, and Surfaces

We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA through an optimized choice of reference orbitals and energy components, rather than a modification of the RPA correlation functional itself. The method employs an empirically constructed hybrid functional to generate DFT orbitals to evaluate the RPA correlation energy, which is then scaled by a constant. Comprehensive benchmarks across molecules, bulk solids, and surface systems demonstrate that optRPA26 consistently achieves high accuracy, with mean absolute errors of 0.05 eV for W4-11-RE reaction energies, 0.07 eV for cohesive energies, 0.09 eV for metal oxide formation energies, 0.11–0.12 eV for adsorption of small molecules on metals, and 0.06 eV for adsorption on oxides. In addition, optRPA26 correctly captures phase stability in metal oxides and magnetic metals. The optRPA26 approach can be run using standard RPA implementations, highlighting its potential as a general-purpose reference method that can accurately capture covalent, ionic, metallic, and van der Waals bonding in molecules, solids, and interfaces.

Adsorption↗

High-intensity polarized electron gun featuring distributed Bragg reflector GaAs photocathode

The polarized electron source is a critical component in accelerator facilities such as the electron–ion collider, which requires a polarized electron gun with higher voltage and higher bunch charge than existing sources. One challenge we faced was the surface charge limit of the distributed Bragg reflector GaAs/GaAsP superlattice (DBR-SL-GaAs) photocathode. We suppressed this effect by optimizing the surface doping and heat cleaning procedures. We achieved up to 11.6 nC bunch charge of polarized electron beam. In this report, we discuss the performance of tests of a DBR-SL-GaAs photocathode in the high voltage direct current gun. Possible reasons for the observed peak quantum efficiency wavelength shift are analyzed, and we addressed it by using a wavelength tunable laser. In addition, the impact of the DBR layer and laser on the lifetime is investigated in this paper. The optimal DBR-SL-GaAs operating zone has been proposed, which gave us a long lifetime and high polarization at 30 μA operation. Finally, the success of this polarized gun will be key to the future of the nuclear sciences.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Systematic optimization of a detailed kinetic model using a methane ignition example

An approach to the systematic optimization of a large-scale dynamic model is proposed which consists in parameterization of simulation results as response surfaces. The optimization procedure is carried out using a second-order orthogonal design. The approach proposed here is demonstrated by an example involving the shock-initiated ignition of methane.

Frenklach, M.↗

Optimizing Integrated Arrival, Departure and Surface Operations Under Uncertainty

In airports and surrounding terminal airspaces, the integration of arrival, departure and surface scheduling and routing have the potential to improve the operations efficiency. Recent research had developed mixed-integer-linear programming algorithm-based scheduler for integrated arrival and departure operations in the presence of uncertainty. This paper extends to the surface previous research performed by the authors to integrate taxiway and runway operations. The developed algorithm is capable of computing optimal aircraft schedules and routings that reflects the integration of air and ground operations. A preliminary study case is conducted for a set of thirteen aircraft evolving in a model of the Los Angeles International airport and surrounding terminal areas. Using historical data, a representative traffic scenario is constructed and probabilistic distributions of pushback delay and arrival gate delay are obtained. To assess the benefits of optimization, a First- Come-First-Serve algorithm approach comparison is realized. Evaluation results demonstrate that the optimization can help identifying runway sequencing and schedule that reduce gate waiting time without increasing average taxi times.

Bosson, Christabelle↗

Investigation of Electrocatalytic CO 2 Reduction on MXene Materials via First-Principles Simulations

Computational studies of CO 2 reduction to yield various products were carried out on the basal plane and edges of different MXene materials. The impact of vacancies upon Mo 2 TiC 2 T x , W 2 TiC 2 T x , and Ti 3 C 2 T x (T x = O and OH) was also examined for both edge and basal sites. Initial calibrations were carried out to generate surfaces with optimal oxide/hydroxide ratios and proper termination sites upon which various vacancy sites were explored to ensure an accurate model of the surfaces’ resting states. From this work, Mo 2 TiC 2 O was determined to exhibit the lowest theoretical overpotential for methane as determined by volcano plot analyses. At a large enough vacancy concentration, the CO 2 reduction reaction (CO 2 RR) is predicted to outcompete the hydrogen evolution reaction (HER) as the predominant reaction on the surface. In conclusion, when examining the edge of Mo 2 TiC 2 O, stronger CO 2 binding was exhibited to such an extent that the reaction was predicted to terminate after the generation of formate on the edge.

Lund, Colton [Argonne National Laboratory (ANL), A↗

Surface science capabilities from IMP spectral imaging

The Imager for Mars Pathfinder (IMP) had a single 12-position filter wheel for one of its two 'eyes'. Originally eight, and then nine, of these filters were optimized for surface science, and three narrow-band filters for atmospheric science. Because of some design revisions we will now have filter wheels on both sides. The wheels for right and left eyes are identical, 12 filter positions each, and rigidly linked to the same rotation shaft. There are now 13 surface filters, in addition to 5 for atmospheric observations. Details of all the filter positions are tabulated and approximate gaussian bandpasses for the 13 surface filters are shown.

Singer, Robert B.↗

Simulated annealing in orbital flight planning

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is unique because the space station will define the first true multivehicle environment in space. The optimization yields surfaces which are potentially complex, with multiple local minima. Because of the likelihood of these local minima, descent techniques are unable to offer robust solutions. Other deterministic optimization techniques were explored without success. The simulated annealing optimization is capable of identifying a minimum-fuel, two-burn trajectory subject to four constraints. Furthermore, the computational efforts involved in the optimization are such that missions could be planned on board the space station. Potential applications could include the on-site planning of rendezvous with a target craft of the emergency rescue of an astronaut. Future research will include multiwaypoint maneuvers, using a knowledge base to guide the optimization.

Soller, Jeffrey↗

Melt Pool characteristics on surface roughness and printability of 316L stainless steel in laser powder bed fusion

Purpose Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel. Design/methodology/approach A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy. Findings The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm 3 ) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation. Originality/value This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Engineering↗

Secondary electron emission for reticulated carbon foam surfaces using direct measurements and spectroscopic analysis

This study investigates secondary electron emission (SEE) characteristics of reticulated foams using direct measurements and analytical modeling. Total SEE was quantified, revealing suppression of up to 44% in carbon foam structures compared to planar graphite surfaces. An optimal geometric configuration was identified and supported by analytical models. SEE angular dependence experiments showed diverse behaviors: fiber-like behavior and directional dependence for pore and ligaments on the mm scale, with fuzz-like characteristics when the foam features are between 10–100 µm. Electron energy analyzer measurements showed that carbon foams preferentially suppress inelastic backscattered electrons (BSEs) more so than true secondary electrons (SEs). The analysis indicated a larger fraction of low-energy SE generation in foams compared to flat surfaces due to increased emission from curved fiber ligaments and tertiary SEs from high-energy BSEs. These findings have implications for design and optimization of materials with tailored electron emission properties for applications like plasma-facing components, spacecraft materials, and accelerator surfaces.

Auger↗

Optimization of Triply Periodic Minimal Surface Heat Exchanger to Achieve Compactness, High Efficiency, and Low-Pressure Drop

With advancements in additive manufacturing (AM) techniques, high-quality triply periodic minimal surface (TPMS) structures can now be produced. TPMS walled heat exchangers (HX) hold significant potential for industrial applications and are receiving increasing attention. This paper explores the impact of various TPMS design variables on flow and thermal performance to optimize TPMS heat exchangers for compactness, high efficiency, and low pressure drop. The design variables examined include the type of TPMS lattice, unit cell size, wall thickness, aspect ratio, TPMS orientation, and equivalent thickness. The study reveals that the flow and heat transfer performance of TPMS structures are significantly affected by these design variables. For the Gyroid, Diamond, and SplitP lattices, performance is nearly identical when the surface-to-volume ratio is kept constant. The average velocity of the fluid in the TPMS HX should be 0.3 m/s. The corresponding Re is between 300~800. Thin wall thickness, small equivalent thickness, and flat lattice configurations can significantly reduce pressure drop while maintaining the overall heat transfer coefficient. Additionally, the angle between the flow direction and TPMS orientation can increase pressure drop. Three aluminum heat exchangers were successfully printed using an AM machine, and testing results are comparable with theoretical prediction.

42 ENGINEERING↗

Nano-Engineered Catalysts for Direct Methanol Fuel Cells

Nano-engineered catalysts, and a method of fabricating them, have been developed in a continuing effort to improve the performances of direct methanol fuel cells as candidate power sources to supplant primary and secondary batteries in a variety of portable electronic products. In order to realize the potential for high energy densities (as much as 1.5 W h/g) of direct methanol fuel cells, it will be necessary to optimize the chemical compositions and geometric configurations of catalyst layers and electrode structures. High performance can be achieved when catalyst particles and electrode structures have the necessary small feature sizes (typically of the order of nanometers), large surface areas, optimal metal compositions, high porosity, and hydrophobicity. The present method involves electrodeposition of one or more catalytic metal(s) or a catalytic-metal/polytetrafluoroethylene nanocomposite on an alumina nanotemplate. The alumina nanotemplate is then dissolved, leaving the desired metal or metal/polytetrafluoroethylene-composite catalyst layer. Unlike some prior methods of making fine metal catalysts, this method does not involve processing at elevated temperature; all processing can be done at room temperature. In addition, this method involves fewer steps and is more amenable to scaling up for mass production. Alumina nanotemplates are porous alumina membranes that have been fabricated, variously, by anodizing either pure aluminum or aluminum that has been deposited on silicon by electronbeam evaporation. The diameters of the pores (7 to 300 nm), areal densities of pores (as much as 7 x 10(exp 10)sq cm), and lengths of pores (up to about 100 nm) can be tailored by selection of fabrication conditions. In a given case, the catalytic metal, catalytic metal alloy, or catalytic metal/ polytetrafluoroethylene composite is electrodeposited in the pores of the alumina nanotemplate. The dimensions of the pores, together with the electrodeposition conditions, determine the sizes and surface areas of the catalytic particles. Hence, the small features and large surface areas of the porosity translate to the desired small particle size and large surface area of the catalyst (see figure). When polytetrafluoroethylene is included, it is for the purpose of imparting hydrophobicity in order to prevent water from impeding the desired diffusion of gases through the catalyst layer. To incorporate polytetrafluoroethylene into a catalytic-metal/polytetrafluoroethylene nanocomposite, one suspends polytetrafluoroethylene nanoparticles in the electrodeposition solution. The polytetrafluoroethylene content can be varied to obtain the desired degree of hydrophobicity and permeability by gas.

Myung, Nosang↗

Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods

Turbine performance directly affects engine specific impulse, thrust-to-weight ratio, and cost in a rocket propulsion system. A global optimization framework combining the radial basis neural network (RBNN) and the polynomial-based response surface method (RSM) is constructed for shape optimization of a supersonic turbine. Based on the optimized preliminary design, shape optimization is performed for the first vane and blade of a 2-stage supersonic turbine, involving O(10) design variables. The design of experiment approach is adopted to reduce the data size needed by the optimization task. It is demonstrated that a major merit of the global optimization approach is that it enables one to adaptively revise the design space to perform multiple optimization cycles. This benefit is realized when an optimal design approaches the boundary of a pre-defined design space. Furthermore, by inspecting the influence of each design variable, one can also gain insight into the existence of multiple design choices and select the optimum design based on other factors such as stress and materials considerations.

Papila, Nilay↗

Parametric Optimization of Rigid Wheels for Planetary Surface Mobility Applications

Design-Build-Test approaches for spaceflight hardware are time and cost intensive, which can result in suboptimal mechanism designs. Optimization-based approaches that utilize high-fidelity models and physics simulation could overcome these limitations while simultaneously speeding up the mechanical design process and reducing cost. In this work, we present a toolchain that enables the multi-objective optimization of rigid rover wheels for planetary surface mobility applications. The toolchain uses Chrono’s Continuous Representation Model (CRM) functionality to simulate granular soil and performs multi-objective parametric optimization on candidate rover wheels to meet a desired performance criterion. The resulting wheel design is then evaluated experimentally using a single-wheel testbed. We end with a discussion of how the toolchain can be extended to simultaneously co-optimize other system parameters, such as system power consumption and feedback control gains.

Optimization↗

N/P GaAs concentrator solar cells with an improved grid and bushbar contact design

The major requirements for a solar cell used in space applications are high efficiency at AMO irradiance and resistance to high energy radiation. Gallium arsenide, with a band gap of 1.43 eV, is one of the most efficient sunlight to electricity converters (25%) when the the simple diode model is used to calculate efficiencies at AMO irradiance, GaAs solar cells are more radiation resistant than silicon solar cells and the N/P GaAs device has been reported to be more radiation resistant than similar P/N solar cells. This higher resistance is probably due to the fact that only 37% of the current is generated in the top N layer of the N/P cell compared to 69% in the top layer of a P/N solar cell. This top layer of the cell is most affected by radiation. It has also been theoretically calculated that the optimized N/P device will prove to have a higher efficiency than a similar P/N device. The use of a GaP window layer on a GaAs solar cell will avoid many of the inherent problems normally associated with a GaAlAs window while still proving good passivation of the GaAs surface. An optimized circular grid design for solar cell concentrators has been shown which incorporates a multi-layer metallization scheme. This multi-layer design allows for a greater current carrying capacity for a unit area of shading, which results in a better output efficiency.

Desalvo, G. C.↗

Studies of H2O on beta-AgI surfaces - An effective pair potential model

The adsorption of a water molecule on surfaces of beta-AgI, the hexagonal crystal believed to be primarily responsible for the ice-nucleating properties of AgI, is studied on the basis of an effective pair potential model. The water molecule is represented by a rigid point charge ST-2 model and the AgI substrate by an array of point atoms, and maximal binding energy surfaces and optimal H2O configurations are generated for the water molecule adsorbed on the rigid and unrelaxed basal and prism faces. Modeling of H2O adsorption above a two-layer ledge, an iodine vacancy and an H2O molecule trapped in the vacancy indicates that H2O adsorption is favored at interstitial sites where no substrate atoms lie directly below. The prism face is found to attract the water molecule more strongly and provide larger energy barriers to surface diffusion than basal face sites, with the ideal basal faces providing hexagonal patterns of adsorption sites for the H2O with preferred dipole moments aligned.

Hale, B. N.↗