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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fuel Injection Dynamics and Composition Effects on RDE Performance

Rotating detonation engines (RDEs) provide a promising route to substantially increasing cycle efficiency in stationary gas turbines. Much of this increase relies on the ability to achieve consistent pressure gain within the combustor. In particular, the design of injectors that feed fuel and air into the detonation channel plays a crucial role. Such injectors have to ensure proper mixing of fuel and oxidizer, while minimizing backflow of detonation products into the feed plenums, and reduce susceptibility to the complex wave structures that exist within the combustor. From a practical perspective, such RDEs also need to operate with variable fuel composition. When fuel mixtures with components that possess vastly different oxidation pathways and time-scales are used, there could be additional losses through deflagrative burning instead of detonation-driven heat release. Such sensitivity to the complete flow path is akin to the physics of thermoacoustic instabilities in conventional gas turbines. In this sense, RDEs pose a unique research challenge: the performance of the device relies on the small-scale heat release process, which is highly dependent on the flow interactions within the full-scale system. As a result, canonical flow configurations, instrumented with detailed diagnostics or modeled using high-fidelity tools, but only focus on the small-scale processes will not contain the key system-level interactions. At the same time, macroscopic measurements and models that only capture system-level performance will not provide insight into the key sources of pressure losses. These couplings and sensitivities provide a formidable challenge to both experimental and simulation studies of the effects Thus, a joint experimental/computational program designed specifically to address these challenges was undertaken in this program. The focus of this program was on two key topics: a) the interaction between injector flow and the overall wave dynamics within the combustor, and b) the deflagration/detonation structure in multi-component fuels that are of practical interest. Both topics involve interaction of small-scale heat release processes with the geometry-dependent wave structure. Studies focused on the study of full-scale RDE systems, based on a 6-inch conventional annular geometry. Experimentally RDEs were studied using a combination of diagnostics. A combination of optical diagnostics and aero-thermo-acoustic analysis based on a combination of spectral and mode decomposition analysis was used to identify the dynamics of the detonation wave and other secondary waves that exist in the system. These studies have helped the identification and investigation of injector and detonation dynamics arising from coupling, and how they affect RDE mixing, detonation structure, operability and performance. Performance of RDEs was investigated through thrust stand measurements, which was used to evaluate the effective pressure gain generated by the system through the concept of equivalent available pressure. Optical diagnostics were developed and implemented to investigate the distribution of heat release, across the detonation wave. Novel optical diagnostics of NIR imaging was also developed and applied to investigate the high temperature / high pressure distribution across the detonation wave. In order to complement the experiments, the computational tools were geared to simulate the full experimental setup. GPU-based acceleration of the models and computations were developed to enable rapid simulation of the full system. In addition, the use of adaptive mesh refinement, and unstructured grid formulation, enabled the investigation of realistic geometries studied in the laboratory. The simulations produced a wealth of detail on the structure of the detonation wave under different operating conditions. Emphasis was placed on quantifying mixture pre-burning and the impact on wave propagation and structure.

03 NATURAL GAS↗
DOE OSTI2014

Particle acceleration via reconnection processes in the supersonic solar wind

An emerging paradigm for the dissipation of magnetic turbulence in the supersonic solar wind is via localized small-scale reconnection processes, essentially between quasi-2D interacting magnetic islands. Charged particles trapped in merging magnetic islands can be accelerated by the electric field generated by magnetic island merging and the contraction of magnetic islands. We derive a gyrophase-averaged transport equation for particles experiencing pitch-angle scattering and energization in a super-Alfvénic flowing plasma experiencing multiple small-scale reconnection events. A simpler advection-diffusion transport equation for a nearly isotropic particle distribution is derived. The dominant charged particle energization processes are (1) the electric field induced by quasi-2D magnetic island merging and (2) magnetic island contraction. The magnetic island topology ensures that charged particles are trapped in regions where they experience repeated interactions with the induced electric field or contracting magnetic islands. Steady-state solutions of the isotropic transport equation with only the induced electric field and a fixed source yield a power-law spectrum for the accelerated particles with index α = –(3 + M{sub A} )/2, where M{sub A} is the Alfvén Mach number. Considering only magnetic island contraction yields power-law-like solutions with index –3(1 + τ {sub c}/(8τ{sub diff})), where τ {sub c}/τ{sub diff} is the ratio of timescales between magnetic island contraction and charged particle diffusion. The general solution is a power-law-like solution with an index that depends on the Alfvén Mach number and the timescale ratio τ{sub diff}/τ {sub c}. Observed power-law distributions of energetic particles observed in the quiet supersonic solar wind at 1 AU may be a consequence of particle acceleration associated with dissipative small-scale reconnection processes in a turbulent plasma, including the widely reported c {sup –5} (c particle speed) spectra observed by Fisk and Gloeckler and Mewaldt et al.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Exploring small-scale chemostats to scale up microbial processes: 3-hydroxypropionic acid production in S. cerevisiae

The physiological characterization of microorganisms provides valuable information for bioprocess development. Chemostat cultivations are a powerful tool for this purpose, as they allow defined changes to one single parameter at a time, which is most commonly the growth rate. The subsequent establishment of a steady state then permits constant variables enabling the acquisition of reproducible data sets for comparing microbial performance under different conditions. We performed physiological characterizations of a 3-hydroxypropionic acid (3-HP) producing Saccharomyces cerevisiae strain in a miniaturized and parallelized chemostat cultivation system. The physiological conditions under investigation were various growth rates controlled by different nutrient limitations (C, N, P). Based on the cultivation parameters obtained subsequent fed-batch cultivations were designed.We report technical advancements of a small-scale chemostat cultivation system and its applicability for reliable strain screening under different physiological conditions, i.e. varying dilution rates and different substrate limitations (C, N, P). Exploring the performance of an engineered 3-HP producing S. cerevisiae strain under carbon-limiting conditions revealed the highest 3-HP yields per substrate and biomass of 16.6 %C-mol and 0.43 g gCDW -1 , respectively, at the lowest set dilution rate of 0.04 h -1 . 3-HP production was further optimized by applying N- and P-limiting conditions, which resulted in a further increase in 3-HP yields revealing values of 21.1 %C-mol and 0.50 g gCDW -1 under phosphate-limiting conditions. The corresponding parameters favoring an increased 3-HP production, i.e. dilution rate as well as C- and P-limiting conditions, were transferred from the small-scale chemostat cultivation system to 1-L bench-top fermenters operating in fed-batch conditions, revealing 3-HP yields of 15.9 %C-mol and 0.45 g gCDW -1 under C-limiting, as well as 25.6 %C-mol and 0.50 g gCDW -1 under phosphate-limiting conditions. Small-scale chemostat cultures are well suited for the physiological characterization of microorganisms, particularly for investigating the effect of changing cultivation parameters on microbial performance. In our study, optimal conditions for 3-HP production comprised (i) a low dilution rate of 0.04 h -1 under carbon-limiting conditions and (ii) the use of phosphate-limiting conditions. Similar 3-HP yields were achieved in chemostat and fed-batch cultures under both C- and P-limiting conditions proving the growth rate as robust parameter for process transfer and thus the small-scale chemostat system as powerful tool for process optimization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Modeling and Optimal Design of Absorbent Enhanced Ammonia Synthesis

Synthetic ammonia produced from fossil fuels is essential for agriculture. However, the emissions-intensive nature of the Haber–Bosch process, as well as a depleting supply of these fossil fuels have motivated the production of ammonia using renewable sources of energy. Small-scale, distributed processes may better enable the use of renewables, but also result in a loss of economies of scale, so the high capital cost of the Haber–Bosch process may inhibit this paradigm shift. A process that operates at lower pressure and uses absorption rather than condensation to remove ammonia from unreacted nitrogen and hydrogen has been proposed as an alternative. In this work, a dynamic model of this absorbent-enhanced process is proposed and implemented in gPROMS ModelBuilder. This dynamic model is used to determine optimal designs of this process that minimize the 20-year net present cost at small scales of 100 kg/h to 10,000 kg/h when powered by wind energy. The capital cost of this process scales with a 0.77 capacity exponent, and at production scales below 6075 kg/h, it is less expensive than the conventional Haber–Bosch process.

10 SYNTHETIC FUELS↗
DOE OSTI2015

A Hybrid Multiscale Framework for Subsurface Flow and Transport Simulations

Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, or system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Multiscale Modeling of Supercritical Combustion with Two-Level Simulation on Adaptive Beamlets

Supercritical carbon dioxide (sCO 2 ) direct-powered turbine technology is a promising choice for the next generation of high-efficiency and low-emissions fossil fuel power systems. Breakthrough improvements in the design and development of the sCO 2 oxy-combustion devices are hampered by the lack of high-fidelity simulation tools suitable for the supercritical highly-CO 2 diluted reactive flow environment. The critically missing capabilities in many commercial and research codes exist due to the unaccounted effects of many nonlinearities, and the small-scale complex processes which become prominent at supercritical conditions. The present approach aims to address many shortcomings of the currently used models by adopting and generalizing a multiscale modeling concept of the Two-Level Simulation (TLS). In the TLS, all small-scale flow fields are simulated explicitly, albeit on one-dimensional (1D) domains -- beamlets represented by a collection of line segments embedded in a three-dimensional (3D) computational domain. In this research, we laid theoretical groundwork needed for application of the developed approach to variable density turbulent reacting flows and to sCO 2 combustors, in particular. The small-scale governing equations on the beamlets were introduced and analyzed by drawing a comparison with the supercritical Direct Numerical Simulation (DNS) data sets to validate the TLS modeling assumptions. A series of the 2D DNS studies of premixed flame propagation in pipes, in a highly CO 2 -diluted environment, was performed in order to elucidate the effects of dilution on the laminar burning velocity, flame thickness, as well as on the dynamics and morphology of a corrugated flame front. The demonstrated approach could be applicable to high-fidelity modeling of other supercritical combustion devices including liquid rocket engines.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Strontium Speciation in Relevant Tank Waste Components Examined by Electrospray Ionization Mass Spectrometry

The identification of chemical species formed in complex nuclear waste is crucial for the development and employment of advanced separations technologies to remediate the Hanford site by processing tank waste. The current Tank Side Cesium Removal (TSCR) process deployed at Hanford utilizes crystalline silicotitanate (CST) ion exchange (IX) media to aid in the separation of low-activity waste for proper treatment and disposal. The inorganic IX media is highly selective for Cs but has been shown to also remove Sr from caustic simulants and small-scale IX processing of Hanford tank waste.(Fiskum, Rovira et al. 2019, Fiskum, Campbell et al. 2021, Westesen, Campbell et al. 2022) Quantitative Sr removal has not been observed in all tank waste supernates tested; thus, to better understand Sr removal and effectively predict processing behavior through TSCR, it is necessary to first investigate Sr speciation in tank waste. This work utilized electrospray ionization mass spectrometry (ESI-MS) to identify ionic Sr complexes that form in the presence of NO 3 –, NO 2 –, OH–, and Cl–. Although our results show that NO 3 –, NO 2 –, and OH– are competitive for Sr 2+ binding, previous data from IX studies indicate that [SrOH] + is not the dominant species of concern in tank waste processing schemes.(Fiskum, Campbell and Trang-Le 2020) Our results show that the [Sr(NO3)]+ species and the [Sr(NO2)] + species form in considerable abundances, which may affect the ability to separate Sr using CST in nuclear waste separation processes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Atomic layer etching of SiO 2 with Ar and CHF 3 plasmas: A self-limiting process for aspect ratio independent etching

With ever increasing demands on device patterning to achieve smaller critical dimensions, the need for precise, controllable atomic layer etching (ALE) is steadily increasing. In this work, a cyclical fluorocarbon/argon plasma is successfully used for patterning silicon oxide by ALE in a conventional inductively coupled plasma tool. The impact of plasma parameters and substrate electrode temperature on the etch performance is established. We achieve the self-limiting behavior of the etch process by modulating the substrate temperature. We find that at an electrode temperature of -10°C, etching stops after complete removal of the modified surface layer as the residual fluorine from the reactor chamber is minimized. Finally, we demonstrate the ability to achieve independent etching, which establishes the potential of the developed cyclic ALE process for small scale device patterning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

What Controls the Entrainment Rate of Dry Buoyant Thermals with Varying Initial Aspect Ratio?

Here, this study uses theory and numerical simulations to analyze the nondimensional spreading rate a (change in radius with height) of buoyant thermals as they rise and entrain surrounding environmental fluid. A focus is on how a varies with initial thermal aspect ratio A r , defined as height divided by width of the initial buoyancy perturbation. An analytic equation for thermal ascent rate w t that depends on a is derived from the thermal-volume-averaged momentum bud get equation. The thermal top height when w t is maximum, defining a critical height z c , is inversely proportional to a. The height z c also corresponds to the thermal top height when buoyant fluid along the thermal’s vertical axis is fully replaced by entrained nonbuoyant environmental fluid rising from below the thermal. The time scale for this process is controlled by the vertical velocity of parcels rising upward through the thermal’s core. This parcel vertical velocity is approximated from Hill’s analytic spherical vortex, yielding an analytic inverse relation between a and A r . Physically, this a–A r relation is connected to changes in circulation as A r is modified. Numerical simulations of thermals with A r varied from 0.5 to 2 give a values close to the analytic theoretical relation, with a factor of ~3 decrease in a as A r is increased from 0.5 to 2. The theory also explains why a of initially spherical thermals from past laboratory and modeling studies is about 0.15. Overall, this study provides a theoretical underpinning for understanding the entrainment behavior of thermals, relevant to buoyantly driven atmospheric flows.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Directed Printing and Reconfiguration of Thermoresponsive Silica–pNIPAM Nanocomposites

Printing of polymeric composites into desired patterns and shapes has revolutionized small-scale manufacturing processes. However, high-resolution printing of adaptive materials that change shape in response to external stimuli remains a significant technical challenge. The article presents a new approach of printing thermoresponsive poly(N-isopropylacrylamide) into macroscopic structures that dynamically reconfigure in response to heatingand cooling cycles. The printing process is performed using an external laser source, which enables thermal cross-linking of the polymer ink consisting of monomer, cross-linker, initiator, and inorganic nanoparticles. It is shown that the addition of silica nanoparticles enhances the mechanical properties of poly(N-isopropylacrylamide) while maintaining its thermoresponsiveness at micrometer-scale resolution, which otherwise is not feasible by extrusion-based three-dimensional printing techniques. It is demonstrated that spatial reconfiguration of the printed monolayers upon increasing temperature is governed by the local geometry, which enables mimicking the reconfiguration of plant leaves in a natural environment. Furthermore, the study lays a foundation for developing a new fabrication platform to print thermoresponsive structures that may find applications in biomedical implants, sensors, and other multi-responsive materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n -Moment Bulk Microphysics Scheme

The small-scale microphysical processes governing the formation of precipitation particles cannot be resolved explicitly by cloud resolving and climate models. Instead, they are represented by microphysics schemes that are based on a combination of theoretical knowledge, statistical assumptions, and fitting to data (“tuning”). Historically, tuning was done in an ad hoc fashion, leading to parameter choices that are not explainable or repeatable. Recent work has treated it as an inverse problem that can be solved by Bayesian inference. The posterior distribution of the parameters given the data—the solution of Bayesian inference—is found through computationally expensive sampling methods, which require over $\mathcal{O}$(10 5 ) evaluations of the forward model; this is prohibitive for many models. We present a proof of concept of Bayesian learning applied to a new bulk microphysics scheme named “Cloudy,” using the recently developed Calibrate-Emulate-Sample (CES) algorithm. Cloudy models collision-coalescence and collisional breakup of cloud droplets with an adjustable number of prognostic moments and with easily modifiable assumptions for the cloud droplet mass distribution and the collision kernel. The CES algorithm uses machine learning tools to accelerate Bayesian inference by reducing the number of forward evaluations needed to $\mathcal{O}$(10 2 ). It also exhibits a smoothing effect when forward evaluations are polluted by noise. In a suite of perfect-model experiments, we show that CES enables computationally efficient Bayesian inference of parameters in Cloudy from noisy observations of moments of the droplet mass distribution. In an additional imperfect-model experiment, a collision kernel parameter is successfully learned from output generated by a Lagrangian particle-based microphysics model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Visualizing electromagnetic fields in laser-produced counter-streaming plasma experiments for collisionless shock laboratory astrophysics

Collisionless shocks are often observed in fast-moving astrophysical plasmas, formed by non-classical viscosity that is believed to originate from collective electromagnetic fields driven by kinetic plasma instabilities. However, the development of small-scale plasma processes into large-scale structures, such as a collisionless shock, is not well understood. It is also unknown to what extent collisionless shocks contain macroscopic fields with a long coherence length. For these reasons, it is valuable to explore collisionless shock formation, including the growth and self-organization of fields, in laboratory plasmas. The experimental results presented here show at a glance with proton imaging how macroscopic fields can emerge from a system of supersonic counter-streaming plasmas produced at the OMEGA EP laser. Interpretation of these results, plans for additional measurements, and the difficulty of achieving truly collisionless conditions are discussed. Future experiments at the National Ignition Facility are expected to create fully formed collisionless shocks in plasmas with no pre-imposed magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Advancing Marine Arctic Science through Facilitating International Collaborations

The Consortium for the Advancement of Marine Arctic Science (CAMAS) held its inaugural Workshop and Early Career School in Santa Fe, New Mexico, from 13 to 16 February 2024. The event brought together 80 Arctic marine scientists from around the world to discuss current research and to develop ideas for collaborative research projects that can be executed in the next few years to advance our understanding of the marine Arctic system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗
DOE OSTI2015

Evolution of carbides in cold-work tool steels

This study aimed to present the complete history of carbide evolution in a cold-work tool steel along its full processing route for fabrication and application. A sequence of processes from cast to final hardening heat treatment was conducted on an 8% Cr-steel to reproduce a typical commercial processing route in a small scale. The carbides found at each process step were then identified by electron diffraction with energy dispersive spectroscopy in a scanning or transmission electron microscope. After solidification, MC, M{sub 7}C{sub 3} and M{sub 2}C carbides were identified and the last one dissolved during hot compression at 1180 °C. In a subsequent annealing at 870 °C followed by slow cooling, M{sub 6}C and M{sub 23}C{sub 6} were added, while they were dissolved in the following austenitization at 1030 °C. After the final tempering at 520 °C, fine M{sub 23}C{sub 6} precipitated again, thus the final microstructure was the tempered martensite with MC, M{sub 7}C{sub 3} and M{sub 23}C{sub 6} carbide. The transient M{sub 2}C and M{sub 6}C originated from the segregation of Mo and finally disappeared due to attenuated segregation and the consequent thermodynamic instability. - Highlights: • The full processing route of a cold-work tool steel was simulated in a small scale. • The carbides in the tool steel were identified by chemical–crystallographic analyses. • MC, M{sub 7}C{sub 3}, M{sub 2}C, M{sub 6}C and M{sub 23}C{sub 6} carbides were found during the processing of the steel. • M{sub 2}C and M{sub 6}C finally disappeared due to thermodynamic instability.

36 MATERIALS SCIENCE↗
DOE OSTI2013

THE OPACITY OF THE INTERGALACTIC MEDIUM DURING REIONIZATION: RESOLVING SMALL-SCALE STRUCTURE

Early in the reionization process, the intergalactic medium (IGM) would have been quite inhomogeneous on small scales, due to the low Jeans mass in the neutral IGM and the hierarchical growth of structure in a cold dark matter universe. This small-scale structure acted as an important sink during the epoch of reionization, impeding the progress of the ionization fronts that swept out from the first sources of ionizing radiation. Here we present results of high-resolution cosmological hydrodynamics simulations that resolve the cosmological Jeans mass of the neutral IGM in representative volumes several Mpc across. The adiabatic hydrodynamics we follow are appropriate in an unheated IGM, before the gas has had a chance to respond to the photoionization heating. Our focus is determination of the resolution required in cosmological simulations in order to sufficiently sample and resolve small-scale structure regulating the opacity of an unheated IGM. We find that a dark matter particle mass of m {sub dm} {approx}< 50 M {sub Sun} and box size of L {approx}> 1 Mpc are required. With our converged results we show how the mean free path of ionizing radiation and clumping factor of ionized hydrogen depend on the ultraviolet background flux and redshift. We find, for example at z = 10, clumping factors typically of 10-20 for an ionization rate of {Gamma} {approx} (0.3-3) Multiplication-Sign 10{sup -12} s{sup -1}, with corresponding mean free paths of {approx}3-15 Mpc, extending previous work on the evolving mean free path to considerably smaller scales and earlier times.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Messiah College Biodiesel Fuel Generation Project (Final Technical Report)

Many obvious and significant concerns arise when considering the concept of small-scale biodiesel production. Does the fuel produced meet the stringent requirements set by the commercial biodiesel industry? Is the process safe? How are small-scale producers collecting and transporting waste vegetable oil? How is waste from the biodiesel production process handled by small-scale producers? These concerns and many others were the focus of the research preformed in the Messiah College Biodiesel Fuel Generation project over the last three years. This project was a unique research program in which undergraduate engineering students at Messiah College set out to research the feasibility of small-biodiesel production for application on a campus of approximately 3000 students. This Department of Energy (DOE) funded research program developed out of almost a decade of small-scale biodiesel research and development work performed by students at Messiah College. Over the course of the last three years the research team focused on four key areas related to small-scale biodiesel production: Quality Testing and Assurance, Process and Processor Research, Process and Processor Development, and Community Education. The objectives for the Messiah College Biodiesel Fuel Generation Project included the following: 1. Preparing a laboratory facility for the development and optimization of processors and processes, ASTM quality assurance, and performance testing of biodiesel fuels. 2. Developing scalable processor and process designs suitable for ASTM certifiable small-scale biodiesel production, with the goals of cost reduction and increased quality. 3. Conduct research into biodiesel process improvement and cost optimization using various biodiesel feedstocks and production ingredients.

09 BIOMASS FUELS↗
DOE OSTI2016

A PORTRAIT OF COLD GAS IN GALAXIES AT 60 pc RESOLUTION AND A SIMPLE METHOD TO TEST HYPOTHESES THAT LINK SMALL-SCALE ISM STRUCTURE TO GALAXY-SCALE PROCESSES

The cloud-scale density, velocity dispersion, and gravitational boundedness of the interstellar medium (ISM) vary within and among galaxies. In turbulent models, these properties play key roles in the ability of gas to form stars. New high-fidelity, high-resolution surveys offer the prospect to measure these quantities across galaxies. We present a simple approach to make such measurements and to test hypotheses that link small-scale gas structure to star formation and galactic environment. Our calculations capture the key physics of the Larson scaling relations, and we show good correspondence between our approach and a traditional “cloud properties” treatment. However, we argue that our method is preferable in many cases because of its simple, reproducible characterization of all emission. Using, low- J {sup 12}CO data from recent surveys, we characterize the molecular ISM at 60 pc resolution in the Antennae, the Large Magellanic Cloud (LMC), M31, M33, M51, and M74. We report the distributions of surface density, velocity dispersion, and gravitational boundedness at 60 pc scales and show galaxy-to-galaxy and intragalaxy variations in each. The distribution of flux as a function of surface density appears roughly lognormal with a 1 σ width of ∼0.3 dex, though the center of this distribution varies from galaxy to galaxy. The 60 pc resolution line width and molecular gas surface density correlate well, which is a fundamental behavior expected for virialized or free-falling gas. Varying the measurement scale for the LMC and M31, we show that the molecular ISM has higher surface densities, lower line widths, and more self-gravity at smaller scales.

79 ASTRONOMY AND ASTROPHYSICS↗