Engineering topics

Lawson, John W.

Publications and source records attributed to Lawson, John W..

52 records · Page 3

NASA NTRS2012

Multiscale Modeling of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2: Application to Lattice Thermal Conductivity

We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

Lawson, John W.↗

NASA NTRS2012

Potential of Glassy Carbon and Silicon Carbide Photonic Structures as Electromagnetic Radiation Shields for Atmospheric Re-entry

During high-velocity atmospheric entries, space vehicles can be exposed to strong electromagnetic radiation from ionized gas in the shock layer. Glassy carbon (GC) and silicon carbide (SiC) are candidate thermal protection materials due to their high melting point and also their good thermal and mechanical properties. Based on data from shock tube experiments, a significant fraction of radiation at hypersonic entry conditions is in the frequency range from 215 to 415 THz. We propose and analyze SiC and GC photonic structures to increase the reflection of radiation in that range. For this purpose, we performed numerical optimizations of various structures using an evolutionary strategy. Among the considered structures are layered, porous, woodpile, inverse opal and guided-mode resonance structures. In order to estimate the impact of fabrication inaccuracies, the sensitivity of the reflectivity to structural imperfections is analyzed. We estimate that the reflectivity of GC photonic structures is limited to 38% in the aforementioned range, due to material absorption. However, GC material can be effective for photonic reflection of individual, strong spectral line. SiC on the other hand can be used to design a good reflector for the entire frequency range.

Komarevskiy,Nikolay↗

NASA NTRS2011

Correlation Function Approach for Estimating Thermal Conductivity in Highly Porous Fibrous Materials

Heat transport in highly porous fiber networks is analyzed via two-point correlation functions. Fibers are assumed to be long and thin to allow a large number of crossing points per fiber. The network is characterized by three parameters: the fiber aspect ratio, the porosity and the anisotropy of the structure. We show that the effective thermal conductivity of the system can be estimated from knowledge of the porosity and the correlation lengths of the correlation functions obtained from a fiber structure image. As an application, the effects of the fiber aspect ratio and the network anisotropy on the thermal conductivity is studied.

Martinez-Garcia, Jorge↗

NASA NTRS2011

Ab initio Computations of the Electronic, Mechanical, and Thermal Properties of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2

Refractory materials such as metallic borides, often considered as ultra high temperature ceramics (UHTC), are characterized by high melting point, high hardness, and good chemical inertness. These materials have many applications which require high temperature materials that can operate with no or limited oxidation. Ab initio, first principles methods are the most accurate modeling approaches available and represent a parameter free description of the material based on the quantum mechanical equations. Using these methods, many of the intrinsic properties of these material can be obtained. We performed ab initio calculations based on density functional theory for the UHTC materials ZrB2 and HfB2. Computational results are presented for structural information (lattice constants, bond lengths, etc), electronic structure (bonding motifs, densities of states, band structure, etc), thermal quantities (phonon spectra, phonon densities of states, specific heat), as well as information about point defects such as vacancy and antisite formation energies.

Lawson, John W.↗

NASA NTRS2011

Lattice Thermal Conductivity of Ultra High Temperature Ceramics ZrB2 and HfB2 from Atomistic Simulations

Atomistic Green-Kubo simulations are performed to evaluate the lattice thermal conductivity for single crystals of the ultra high temperature ceramics ZrB2 and HfB2 for a range of temperatures. Recently developed interatomic potentials are used for these simulations. Heat current correlation functions show rapid oscillations which can be identified with mixed metal-Boron optical phonon modes. Agreement with available experimental data is good.

Lawson, John W.↗

NASA NTRS2011

Correlation Function Analysis of Fiber Networks: Implications for Thermal Conductivity

The heat transport in highly porous fiber structures is investigated. The fibers are supposed to be thin, but long, so that the number of the inter-fiber connections along each fiber is large. We show that the effective conductivity of such structures can be found from the correlation length of the two-point correlation function of the local conductivities. Estimation of the parameters, determining the conductivity, from the 2D images of the structures is analyzed.

Martinez-Garcia, Jorge↗

NASA NTRS2010

Modeling Initial Stage of Ablation Material Pyrolysis: Graphitic Precursor Formation and Interfacial Effects

Reactive molecular dynamics simulations are used to study initial stage of pyrolysis of ablation materials and their composites with carbon nanotubes and carbon fibers. The products formed during pyrolysis are characterized and water is found as the primary product in all cases. The water formation mechanisms are analyzed and the value of the activation energy for water formation is estimated. A detailed study on graphitic precursor formation reveals the presence of two temperature zones. In the lower temperature zone (less than 2000 K) polymerization occurs resulting in formation of large, stable graphitic precursors, and in the high temperature zone (greater than 2000 K) polymer scission results in formation of short polymer chains/molecules. Simulations performed in the high temperature zone on the phenolic resin composites (with carbon nanotubes and carbon fibers) shows that the presence of interfaces had no substantial effect on the chain scission rate or the activation energy value for water formation.

Desai, Tapan G.↗

NASA NTRS2010

Formation, Structure and Properties of Amorphous Carbon Char from Polymer Materials in Extreme Atmospheric Reentry Environments

Amorphous carbonaceous char produced from the pyrolysis of polymer solids has many desirable properties for ablative heat shields for space vehicles. Molecular dynamics simulations are presented to study the transformation of the local atomic structure from virgin polymer to a dense, disordered char [1]. Release of polymer hydrogen is found to be critical to allow the system to collapse into a highly coordinated char structure. Mechanisms of the char formation process and the morphology of the resulting structures are elucidated. Thermal conductivity and mechanical response of the resulting char are evaluated [2]. During reenty, the optical response and oxidative reactivity of char are also important properties. Results of ab initio computations of char optical functions [3] and char reactivity [4] are also presented.

Lawson, John W.↗

NASA NTRS2010

Examination of Scanning Electron Microscope and Computed Tomography Images of PICA

Micrographs of PICA (Phenolic Impregnated Carbon Ablator) taken using a Scanning Electron Microscope (SEM) and 3D images taken with a Computed Tomography (CT) system are examined. PICA is a carbon fiber based composite (Fiberform ) with a phenolic polymer matrix. The micrographs are taken at different surface depths and at different magnifications in a sample after arc jet testing and show different levels of oxidative removal of the charred matrix (Figs 1 though 13). CT scans, courtesy of Xradia, Inc. of Concord CA, were captured for samples of virgin PICA, charred PICA and raw Fiberform (Fig. 14). We use these images to calculate the thermal conductivity (TC) of these materials using correlation function (CF) methods. CF methods give a mathematical description of how one material is embedded in another and is thus ideally suited for modeling composites like PICA. We will evaluate how the TC of the materials changes as a function of surface depth. This work is in collaboration with ETH-Zurich, which has expertise in high temperature materials and TC modeling (including CF methods).

Lawson, John W.↗

NASA NTRS2010

Role of Microstructure on the Performance of UHTCs

We have investigated a number of methods to control microstructure. We have routes to form: a) in situ "composites" b) Very fine microstructures. Arcjet testing and other characterization of monolithic materials. Control oxidation through microstructure and composition. Beginning to incorporate these materials as matrices for composites. Modeling effort to facilitate material design and characterization.

Johnson, Sylvia M.↗

NASA NTRS2009

Recent Developments in Ultra High Temperature Ceramics at NASA Ames

NASA Ames is pursuing a variety of approaches to modify and control the microstructure of UHTCs with the goal of improving fracture toughness, oxidation resistance and controlling thermal conductivity. The overall goal is to produce materials that can perform reliably as sharp leading edges or nose tips in hypersonic reentry vehicles. Processing approaches include the use of preceramic polymers as the SiC source (as opposed to powder techniques), the addition of third phases to control grain growth and oxidation, and the use of processing techniques to produce high purity materials. Both hot pressing and field assisted sintering have been used to make UHTCs. Characterization of the mechanical and thermal properties of these materials is ongoing, as is arcjet testing to evaluate performance under simulated reentry conditions. The preceramic polymer approach has generated a microstructure in which elongated SiC grains grow in the form of an in-situ composite. This microstructure has the advantage of improving fracture toughness while potentially improving oxidation resistance by reducing the amount and interconnectivity of SiC in the material. Addition of third phases, such as Ir, results in a very fine-grained microstructure, even in hot-pressed samples. The results of processing and compositional changes on microstructure and properties are reported, along with selected arcjet results.

Johnson, Sylvia M.↗

NASA NTRS2004

Multi-Agent Methods for the Configuration of Random Nanocomputers

As computational devices continue to shrink, the cost of manufacturing such devices is expected to grow exponentially. One alternative to the costly, detailed design and assembly of conventional computers is to place the nano-electronic components randomly on a chip. The price for such a trivial assembly process is that the resulting chip would not be programmable by conventional means. In this work, we show that such random nanocomputers can be adaptively programmed using multi-agent methods. This is accomplished through the optimization of an associated high dimensional error function. By representing each of the independent variables as a reinforcement learning agent, we are able to achieve convergence must faster than with other methods, including simulated annealing. Standard combinational logic circuits such as adders and multipliers are implemented in a straightforward manner. In addition, we show that the intrinsic flexibility of these adaptive methods allows the random computers to be reconfigured easily, making them reusable. Recovery from faults is also demonstrated.

Lawson, John W.↗

NASA NTRS2004

Designing Agent Collectives For Systems With Markovian Dynamics

The Collective Intelligence (COIN) framework concerns the design of collectives of agents so that as those agents strive to maximize their individual utility functions, their interaction causes a provided world utility function concerning the entire collective to be also maximized. Here we show how to extend that framework to scenarios having Markovian dynamics when no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. Our approach transforms the (time-extended) argument of each agent's utility function before evaluating that function. This transformation has benefits in scenarios not involving Markovian dynamics of an agent's utility function are observable. We investigate this transformation in simulations involving both hear and quadratic (nonlinear) dynamics. In addition, we find that a certain subset of these transformations, which result in utilities that have low opacity (analogous to having high signal to noise) but are not factored (analogous to not being incentive compatible), reliably improve performance over that arising with factored utilities. We also present a Taylor Series method for the fully general nonlinear case.

Wolpert, David H.↗

NASA NTRS2004

The Design of Collectives of Agents to Control Non-Markovian Systems

The Collective Intelligence (COIN) framework concerns the design of collectives of reinforcement-learning agents such that their interaction causes a provided "world" utility function concerning the entire collective to be maximized. Previously, we applied that framework to scenarios involving Markovian dynamics where no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. This approach sets the individual utility function of each agent to be both aligned with the world utility, and at the same time, easy for the associated agents to optimize. Here we extend that approach to systems involving non-Markovian dynamics. In computer simulations, we compare our techniques with each other and with conventional "team games". We show whereas in team games performance often degrades badly with time, it steadily improves when our techniques are used. We also investigate situations where the system's dimensionality is effectively reduced. We show that this leads to difficulties in the agents ability to learn. The implication is that learning is a property only of high-enough dimensional systems.

Lawson, John W.↗

NASA NTRS2002

The Design of Collectives of Agents to Control Non-Markovian Systems

The 'Collective Intelligence' (COIN) framework concerns the design of collectives of reinforcement-learning agents such that their interaction causes a provided 'world' utility function concerning the entire collective to be maximized. Previously, we applied that framework to scenarios involving Markovian dynamics where no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. This approach sets the individual utility function of each agent to be both aligned with the world utility, and at the same time, easy for the associated agents to optimize. Here we extend that approach to systems involving non-Markovian dynamics. In computer simulations, we compare our techniques with each other and with conventional-'team games'. We show whereas in team games performance often degrades badly with time, it steadily improves when our techniques are used. We also investigate situations where the system's dimensionality is effectively reduced. We show that this leads to difficulties in the agents' ability to learn. The implication is that 'learning' is a property only of high-enough dimensional systems.

Lawson, John W.↗

NASA NTRS2001

Designing Agent Collectives For Systems With Markovian Dynamics

The "Collective Intelligence" (COIN) framework concerns the design of collectives of agents so that as those agents strive to maximize their individual utility functions, their interaction causes a provided "world" utility function concerning the entire collective to be also maximized. Here we show how to extend that framework to scenarios having Markovian dynamics when no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. Our approach transforms the (time-extended) argument of each agent's utility function before evaluating that function. This transformation has benefits in scenarios not involving Markovian dynamics, in particular scenarios where not all of the arguments of an agent's utility function are observable. We investigate this transformation in simulations involving both linear and quadratic (nonlinear) dynamics. In addition, we find that a certain subset of these transformations, which result in utilities that have low "opacity (analogous to having high signal to noise) but are not "factored" (analogous to not being incentive compatible), reliably improve performance over that arising with factored utilities. We also present a Taylor Series method for the fully general nonlinear case.

Wolpert, David H.↗