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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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NASA NTRS1988

Budget study of a mesoscale convective system - Model simulation

A tropical squall-type cloud cluster is examined as an example of a mesoscale convective complex. The precipitation growth processes and air circulations that develop in the convective and stratiform regions are studied using a data set generated from a time-dependent numerical cloud model. The relationship of the stratiform region of the mesoscale convective complex is discussed. The vertical profiles of heating and drying are calculated. Comparisons are made between simulations with and without ice-phase microphysical processes and a simulation with forcing by weaker lifting at middle and upper levels.

Tao, Wei-Kuo↗
NASA NTRS2008

The Super Tuesday Outbreak: Forecast Sensitivities to Single-Moment Microphysics Schemes

Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.

Molthan, Andrew L.↗
DOE OSTI2016

Validation of gamma-ray detection techniques for safeguards monitoring at natural uranium conversion facilities

Recent IAEA circulars and policy papers have sought to implement safeguards when any purified aqueous uranium solution or uranium oxides suitable for isotopic enrichment or fuel fabrication exists. Under the revised policy, IAEA Policy Paper 18, the starting point for nuclear material under safeguards was reinterpreted, suggesting that purified uranium compounds should be subject to safeguards procedures no later than the first point in the conversion process. In response to this technical need, a combination of simulation models and experimental measurements were employed to develop and validate concepts of nondestructive assay monitoring systems in a natural uranium conversion plant (NUCP). In particular, uranyl nitrate (UO 2 (NO 3 ) 2 ) solution exiting solvent extraction was identified as a key measurement point (KMP), where gamma-ray spectroscopy was selected as the process monitoring tool. The Uranyl Nitrate Calibration Loop Equipment (UNCLE) facility at Oak Ridge National Laboratory was employed to simulate the full-scale operating conditions of a purified uranium-bearing aqueous stream exiting the solvent extraction process in an NUCP. Nondestructive assay techniques using gamma-ray spectroscopy were evaluated to determine their viability as a technical means for drawing safeguards conclusions at NUCPs, and if the IAEA detection requirements of 1 significant quantity (SQ) can be met in a timely way. This work investigated gamma-ray signatures of uranyl nitrate circulating in the UNCLE facility and evaluated various gamma-ray detector sensitivities to uranyl nitrate. These detector validation activities include assessing detector responses to the uranyl nitrate gamma-ray signatures for spectrometers based on sodium iodide, lanthanum bromide, and high-purity germanium detectors. The results of measurements under static and dynamic operating conditions at concentrations ranging from 10–90 g U/L of natural uranyl nitrate are presented. A range of gamma-ray lines is examined, including attenuation for transmission measurement of density and concentration. It was determined that transmission-corrected gamma-ray spectra provide a reliable way to monitor the 235 U concentration of uranyl nitrate solution in transfer pipes in NUCPs. Furthermore, existing predictive and analysis methods are adequate to design and realize practical designs. The 137 Cs transmission source employed in this work is viable but not optimal for 235 U densitometry determination. Validated simulations assessed the viability of 133 Ba and 57Co as alternative densitometry sources. All three gamma-ray detectors are viable for monitoring natural uranium feed; although high-purity germanium is easiest to interpret, it is, however, the least attractive as an installation instrument. Overall, for monitoring throughput in a facility such as UNCLE, emulating the uranium concentration and pump speeds of the Springfields conversion facility in the United Kingdom, an uncertainty of less than 0.17% is required in order to detect the diversion of 1 SQ of uranyl nitrate through changes in uranium concentration over an accountancy period of one year with a detection probability of 50%. As a result, calibrated gamma-ray detection systems are capable of determining the concentration of uranium content in NUCPs, it is only in combination with verifiable operator declarations and supporting data, such as flow rate and enrichment, that safeguards conclusions can be drawn.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2019

Neutron Star Mergers Might Not Be the Only Source of r -process Elements in the Milky Way

Probing the origin of r -process elements in the universe represents a multidisciplinary challenge. We review the observational evidence that probes the properties of r -process sites, and address them using galactic chemical evolution simulations, binary population synthesis models, and nucleosynthesis calculations. Our motivation is to define which astrophysical sites have significantly contributed to the total mass of r -process elements present in our Galaxy. We found discrepancies with the neutron star (NS–NS) merger scenario. When we assume that they are the only site, the decreasing trend of [Eu/Fe] at [Fe/H] > -1 in the disk of the Milky Way cannot be reproduced while accounting for the delay-time distribution (DTD) of coalescence times ( ∝t -1 ) derived from short gamma-ray bursts (GRBs) and population synthesis models. Steeper DTD functions ( ∝t -1.5 ) or power laws combined with a strong burst of mergers before the onset of supernovae (SNe) Ia can reproduce the [Eu/Fe] trend, but this scenario is inconsistent with the similar fraction of short GRBs and SNe Ia occurring in early-type galaxies, and it reduces the probability of detecting GW170817 in an early-type galaxy. One solution is to assume an additional production site of Eu that would be active in the early universe, but would fade away with increasing metallicity. If this is correct, this additional site could be responsible for roughly 50% of the Eu production in the early universe before the onset of SNe Ia. Rare classes of supernovae could be this additional r -process source, but hydrodynamic simulations still need to ensure the conditions for a robust r -process pattern.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Kinetic Monte Carlo Simulation of Hydrogen Diffusion in Tungsten

Nuclear fusion is considered as the most promising sustainable energy source. If achieved, it could provide electricity to the mankind for millions of years. During the reaction, the fusion ash is continuously removed from the magnetic gap, the divertor region, and the divertor facing component is subjected to intense plasma bombardment. It is proposed to use tungsten as the divertor facing material, because it has low physical sputtering yield and superior thermomechanical properties. However, the high mobility of hydrogen in tungsten and the high bombardment flux bring the hydrogen isotopes deep into the tungsten tile. The presence of hydrogen in tungsten tends to weaken the gram boundaries and produce surface blistering. The ejection of tungsten particulates into the plasma core will cool the reaction and cease the fusion reactions. Therefore, it is important to have a detailed understanding of the hydrogen diffusion in tungsten bulk. The KMC method is a stochastic computer simulation to predict the time evolution of a certain system. Typically, at a given time, the system will evolve through a few possible paths with known probabilities. In each step, the KMC method analyzes the entire system and randomly determines the system evolving events based on all transition rates of all possible events and advance the physical time. This process is repeated till the simulation of the entire physical time is completed. In previous work, the authors developed a kinetic Monte Carlo (KMC) algorithm and program to simulate hydrogen diffusion process on tungsten reconstructed surface. In this article, this KMC method is extended to model the hydrogen diffusion in tungsten bulk. The diffusion coefficients are calculated and fitted to the Arrhenius equation. The result matches the experiment measurement very well. KMC diffusion simulation needs the locations of the hydrogen trapping sites, diffusion paths and the corresponding diffusion energy barriers. The hydrogen interstitial sites in tungsten crystal have been thoroughly studied by density function theory (DFT) and molecular dynamics (MD). Johnson and Carter used DFT to determine the preferred location of the hydrogen interstitial sites m tungsten crystal, which are the tetrahedral sites (T-sites) in body-centered-cubic (bcc) lattice surfaces. All T-sites are located on the surfaces of a lattice cell. There are four T-sites per surface and twelve T-sites per lattice cell. The hydrogen atoms diffuse by traveling from one T-site to one of its nearest four T-site neighbors. Thus, each T-site is surrounded by two neighbors on the same surface, and one neighbor on each of the two adjacent surfaces perpendicular to the surface holding the center T-site. The diffusion barrier between two neighboring T-sites was calculated to be 0.38 eV. Knowing the diffusion path, energy barrier, and the crystal structure, the KMC simulation is readily to be performed. Based on other researchers' DFT calculations, the hydrogen stable interstitial site in tungsten bulk is determined as the tetrahedral site on the surface of the bee lattice. Each T-site has 4 neighbors and the energy barrier between two adjacent T-sites are estimated to be 0.38 eV. Based on those facts and the KMC theory, a MATLAB program is developed to model the hydrogen diffusion in tungsten bulk. In the MATLAB program, substrate temperature, hydrogen concentration, physical time to be simulated, and the number of cycles are all customizable. To compare the KMC determined diffusion coefficients with experiment results in the literature, the simulations are performed for temperature 300 K - 2500 K and low hydrogen concentration (0.1%), mimicking the experiment condition. The calculated diffusion coefficients match the reference values measured by the experiment under low hydrogen concentration condition. The results are also fitted to the Arrhenius equation. The pre-exponential factor and the average activation energy in Arrhenius equation are obtained. The good agreement between simulation and experiment proves that the developed KMC algorithm truly reflect the well-established theory of interstitial hydrogens in tungsten. The developed program could easily be used to model the diffusion process and predict the diffusion coefficients under other concentrations and temperatures. This work is part of the ongoing development of hydrogen diffusion in tungsten integrating surface diffusion (previous work), bulk diffusion (this work), and adsorption/desorption on surface (future work)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Modeling the thermal deformation of TATB-based explosives. Part 1: Thermal expansion of “neat-pressed” polycrystalline TATB

We detail a modeling approach to simulate the anisotropic thermal expansion of polycrystalline (1,3,5-triamino-2,4,6-trinitrobenzene) TATB-based explosives that utilizes microstructural information including porosity, crystal aspect ratio, and processing-induced texture. This report, the first in a series, focuses on nonlinear thermal expansion of “neat-pressed” polycrystalline TATB specimens which do not contain any binder; additional complexities related to polymeric binder and irreversible ratcheting behavior are briefly discussed, however detailed investigation of these aspects are deferred to subsequent reports. In this work we have, for the first time, developed a mesoscale continuum model relating the thermal expansion of polycrystal TATB specimens to their microstructural characteristics. A self-consistent homogenization procedure is used to relate macroscopic thermoelastic response to the constitutive behavior of single-crystal TATB. The model includes a representation of grain aspect ratio, porosity, and crystallographic texture attributed to the consolidation process. A quantitative model is proposed to describe the evolution of preferred orientation of graphitic planes in TATB during consolidation and an algorithm constructed to develop a discrete representation of the associated orientation distribution function. Analytical and numerical solutions using this model are shown to produce textures consistent with previous measurements and characterization for isostatic and uniaxial “die-pressed” specimens. Predicted thermal strain versus temperature for textured specimens are shown to be in agreement with corresponding experimental measurements. Using the developed modeling approach, several simulations have been run to investigate the influence of microstructure on macroscopic thermal expansion behavior. Results from these simulations are used to identify qualitative trends. Implications of the identified trends are discussed in the context of thermal deformation of engineered components whose consolidation process is generally more complex than isostatic or die-pressed specimens. Finally, an envisioned application of the modeling approach to simulating thermal expansion of weapon systems and components is outlined along with necessary future work to introduce the effects of binder and ratcheting behavior. Key conclusions from this work include the following. Both porosity and grain aspect ratio have an influence on the thermal expansion of polycrystal TATB considering realistic material variability. Thepreferred orientation of the single crystal TATB [001] poles within a polycrystal gives rise to pronounced anisotropy of the macroscopic thermal expansion. The extent of this preferred orientation depends on the magnitude of deformation, and consequently, is expected to vary spatially throughout manufactured components much like porosity. The modeling approach presented here has utility toward bringing spatially variable microstructural features into macroscale system engineering modelsAbstract Not Provided

36 MATERIALS SCIENCE↗
DOE OSTI2016

Collaborative Project: Building improved optimized parameter estimation algorithms to improve methane and nitrogen fluxes in a climate model

Soils in natural and managed ecosystems and wetlands are well known sources of methane, nitrous oxides, and reactive nitrogen gases, but the magnitudes of gas flux to the atmosphere are still poorly constrained. Thus, the reasons for the large increases in atmospheric concentrations of methane and nitrous oxide since the preindustrial time period are not well understood. The low atmospheric concentrations of methane and nitrous oxide, despite being more potent greenhouse gases than carbon dioxide, complicate empirical studies to provide explanations. In addition to climate concerns, the emissions of reactive nitrogen gases from soils are important to the changing nitrogen balance in the earth system, subject to human management, and may change substantially in the future. Thus improved modeling of the emission fluxes of these species from the land surface is important. Currently, there are emission modules for methane and some nitrogen species in the Community Earth System Model’s Community Land Model (CLM-ME/N); however, there are large uncertainties and problems in the simulations, resulting in coarse estimates. In this proposal, we seek to improve these emission modules by combining state-of-the-art process modules for emissions, available data, and new optimization methods. In earth science problems, we often have substantial data and knowledge of processes in disparate systems, and thus we need to combine data and a general process level understanding into a model for projections of future climate that are as accurate as possible. The best methodologies for optimization of parameters in earth system models are still being developed. In this proposal we will develop and apply surrogate algorithms that a) were especially developed for computationally expensive simulations like CLM-ME/N models; b) were (in the earlier surrogate optimization Stochastic RBF) demonstrated to perform very well on computationally expensive complex partial differential equations in earth science with limited numbers of simulations; and, c) will be (as part of the proposed research) significantly improved both by adding asynchronous parallelism, early truncation of unsuccessful simulations, and the improvement of both serial and parallel performance by the use of derivative and sensitivity information from global and local surrogate approximations S(x) . The algorithm development and testing will be focused on the CLM-ME/N model application, but the methods are general and are expected to also perform well on optimization for parameter estimation of other climate models and other classes of continuous multimodal optimization problems arising from complex simulation models. In addition, this proposal will compile available datasets of emissions of methane, nitrous oxides and reactive nitrogen species and develop protocols for site level comparisons with the CLM-ME/N. Once the model parameters are optimized against site level data, the model will be simulated at the global level and compared to atmospheric concentration measurements for the current climate, and future emissions will be estimated using climate change as simulated by the CESM. This proposal combines experts in earth system modeling, optimization, computer science, and process level understanding of soil gas emissions in an interdisciplinary team in order to improve the modeling of methane and nitrogen gas emissions. This proposal thus meets the requirements of the SciDAC RFP, by integrating state-of-the-art computer science and earth system to build an improved earth system model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Predicting the mineral composition of dust aerosols – Part 2: Model evaluation and identification of key processes with observations

A global compilation of nearly sixty measurement studies is used to evaluate two methods of simulating the mineral composition of dust aerosols in an Earth system model. Both methods are based upon a Mean Mineralogical Table (MMT) that relates the soil mineral fractions to a global atlas of arid soil type. The Soil Mineral Fraction (SMF) method assumes that the aerosol mineral fractions match the fractions of the soil. The MMT is based upon soil measurements after wet sieving, a process that destroys aggregates of soil particles that would have been emitted from the original, undisturbed soil. The second method approximately reconstructs the emitted aggregates. This model is referred to as the Aerosol Mineral Fraction (AMF) method because the mineral fractions of the aerosols differ from those of the wet-sieved parent soil, partly due to reaggregation. The AMF method remedies some of the deficiencies of the SMF method in comparison to observations. Only the AMF method exhibits phyllosilicate mass at silt sizes, where they are abundant according to observations. In addition, the AMF quartz fraction of silt particles is in better agreement with measured values, in contrast to the overestimated SMF fraction. Measurements at distinct clay and silt particle sizes are shown to be more useful for evaluation of the models, in contrast to the sum over all particles sizes that is susceptible to compensating errors, as illustrated by the SMF experiment. Model errors suggest that allocation of the emitted silt fraction of each mineral into the corresponding transported size categories is an important remaining source of uncertainty. Evaluation of both models and the MMT is hindered by the limited number of size-resolved measurements of mineral content that sparsely sample aerosols from the major dust sources. In conclusion, the importance of climate processes dependent upon aerosol mineral composition shows the need for global and routine mineral measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A GPU based high-resolution multilevel biomechanical head and neck model for validating deformable image registration

Purpose: Validating the usage of deformable image registration (DIR) for daily patient positioning is critical for adaptive radiotherapy (RT) applications pertaining to head and neck (HN) radiotherapy. The authors present a methodology for generating biomechanically realistic ground-truth data for validating DIR algorithms for HN anatomy by (a) developing a high-resolution deformable biomechanical HN model from a planning CT, (b) simulating deformations for a range of interfraction posture changes and physiological regression, and (c) generating subsequent CT images representing the deformed anatomy. Methods: The biomechanical model was developed using HN kVCT datasets and the corresponding structure contours. The voxels inside a given 3D contour boundary were clustered using a graphics processing unit (GPU) based algorithm that accounted for inconsistencies and gaps in the boundary to form a volumetric structure. While the bony anatomy was modeled as rigid body, the muscle and soft tissue structures were modeled as mass–spring-damper models with elastic material properties that corresponded to the underlying contoured anatomies. Within a given muscle structure, the voxels were classified using a uniform grid and a normalized mass was assigned to each voxel based on its Hounsfield number. The soft tissue deformation for a given skeletal actuation was performed using an implicit Euler integration with each iteration split into two substeps: one for the muscle structures and the other for the remaining soft tissues. Posture changes were simulated by articulating the skeletal structure and enabling the soft structures to deform accordingly. Physiological changes representing tumor regression were simulated by reducing the target volume and enabling the surrounding soft structures to deform accordingly. Finally, the authors also discuss a new approach to generate kVCT images representing the deformed anatomy that accounts for gaps and antialiasing artifacts that may be caused by the biomechanical deformation process. Accuracy and stability of the model response were validated using ground-truth simulations representing soft tissue behavior under local and global deformations. Numerical accuracy of the HN deformations was analyzed by applying nonrigid skeletal transformations acquired from interfraction kVCT images to the model’s skeletal structures and comparing the subsequent soft tissue deformations of the model with the clinical anatomy. Results: The GPU based framework enabled the model deformation to be performed at 60 frames/s, facilitating simulations of posture changes and physiological regressions at interactive speeds. The soft tissue response was accurate with a R{sup 2} value of >0.98 when compared to ground-truth global and local force deformation analysis. The deformation of the HN anatomy by the model agreed with the clinically observed deformations with an average correlation coefficient of 0.956. For a clinically relevant range of posture and physiological changes, the model deformations stabilized with an uncertainty of less than 0.01 mm. Conclusions: Documenting dose delivery for HN radiotherapy is essential accounting for posture and physiological changes. The biomechanical model discussed in this paper was able to deform in real-time, allowing interactive simulations and visualization of such changes. The model would allow patient specific validations of the DIR method and has the potential to be a significant aid in adaptive radiotherapy techniques.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Classification; Climate change; Crop model; Ensemb↗
NASA NTRS2004

Ring Current Electrodynamic Coupling

In this talk we will address the two primary issues of ring current (RC) electrodynamic coupling: 1. RC self-consistent coupling with electromagnetic ion cyclotron (EMIC) waves (small scale electrodynamic coupling); and 2. RC self-consistent magnetosphere-ionosphere coupling that includes calculation of the magnetospheric electric field (large scale electrodynamic coupling). Our study will be based on two RC models that we have recently developed in our group. The first model by Khazanov et al. [2002, 20031 couples the system of two kinetic equations: one equation which describes the RC ion dynamics and another equation which describes the energy density evolution of EMIC waves. The second model by Khazanov et al. [2003] deals with large scale electrodynamic coupling processes and provides a self-consistent simulation of RC ions, electrons and the magnetospheric electric field. There is presently no model that addresses both of these issues simultaneously in a self-consistent calculation. However, the need exists for such a model, because these two processes directly influence each other, with the mesoscale coupling changing the drift paths of the thermal and energetic particle populations in the inner magnetosphere, thereby changing the wave interactions, and the microscale coupling altering the pitch angle distributions and ionospheric conductivities (through increased precipitation), thus changing the field-aligned currents and electric potential structure. The initial thrust of the work will be the development of a combined kinetic model of micro- and meso-scale RC electrodynamic coupling processes and to examine their interactions with each other on a global scale. We also discuss the nonlinear coupling of EMIC and lower hybrid waves in the RC region during the May 2-7, 1998 storm period.

Khazanov, G. V.↗
DOE OSTI2018

Impacts of feedstock properties on the process economics of fast-pyrolysis biorefineries

Feedstock properties are an important factor affecting process yields and economics of fast pyrolysis biorefineries. Here, this study develops a fast pyrolysis process model sensitive to feedstock properties based on the experimental results. 64 simulations are run to evaluate the impacts of carbon, ash and moisture content in biomass feedstocks on process yields and energy consumptions. An economic analysis is conducted for each run to quantify process economics under different feedstock properties. With biomass feedstocks of 48% carbon and 15% moisture, Minimum Fuel Selling Price (MFSP) increases from 0.97/L to 1.06/L when ash content increases from 1% to 7%, due to reduced hydrocarbon yields. With biomass feedstocks of 48% carbon and 3% ash content, MFSP increases from 1.03/L to 1.08/L when feedstock moisture increases from 15% to 45% as a consequence of increased energy demand for feedstock drying. Finally, the impact of feedstock ash content decreases gradually as ash content increases. Feedstock carbon content has less significant impacts on process economics in this study.

09 BIOMASS FUELS↗
NASA NTRS1991

Monte Carlo study of vibrational relaxation processes

A new model is proposed for the computation of vibrational nonequilibrium in the direct simulation Monte Carlo method (DSMC). This model permits level to level vibrational transitions for the first time in a Monte Carlo flowfield simulation. The model follows the Landau-Teller theory for a harmonic oscillator in which the rates of transition are related to an experimental correlation for the vibrational relaxation time. The usual method for simulating such processes in the DSMC technique applies a constant exchange probability to each collision and the vibrational energy is treated as a continuum. A comparison of these two methods is made for the flow of nitrogen over a wedge. Significant differences exist for the vibrational temperatures computed. These arise as a consequence of the incorrect application of a constant exchange probability in the old method. It is found that the numerical performances of the two vibrational relaxation models are equal.

Boyd, Iain D.↗
NASA NTRS2010

The Habitat Demonstration Unit System Integration

The Lunar Surface System Habitat Demonstration Unit (HDU) will require a project team to integrate a variety of contributions from National Aeronautics and Space Administration (NASA) centers and potential outside collaborators and poses a challenge in integrating these disparate efforts into a cohesive architecture. To accomplish the development of the first version of the HDU, the Pressurized Excursion Module (PEM), from conception in June 2009 to rollout for operations in July 2010, the HDU project team is using several strategies to mitigate risks and bring the separate efforts together. First, a set of design standards is being developed to define the interfaces between the various systems of PEM and to the payloads, such as the Geology Laboratory, that those systems will support. Scheduled activities such as early fit-checks and the utilization of a habitat avionics test bed prior to equipment installation into HDU PEM are planned to facilitate the integration process. A coordinated effort to establish simplified Computer Aided Design (CAD) standards and the utilization of a modeling and simulation systems will aid in design and integration concept development. Finally, decision processes on the shell development including the assembly sequence and the transportation have been fleshed out early on HDU design to maximize the efficiency of both integration and field operations.

Gill, Tracy R.↗
NASA NTRS2011

The Roles of Transport and Wave-Particle Interactions on Radiation Belt Dynamics

Particle fluxes in the radiation belts can vary dramatically during geomagnetic active periods. Transport and wave-particle interactions are believed to be the two main types of mechanisms that control the radiation belt dynamics. Major transport processes include substorm dipolarization and injection, radial diffusion, convection, adiabatic acceleration and deceleration, and magnetopause shadowing. Energetic electrons and ions are also subjected to pitch-angle and energy diffusion when interact with plasma waves in the radiation belts. Important wave modes include whistler mode chorus waves, plasmaspheric hiss, electromagnetic ion cyclotron waves, and magnetosonic waves. We investigate the relative roles of transport and wave associated processes in radiation belt variations. Energetic electron fluxes during several storms are simulated using our Radiation Belt Environment (RBE) model. The model includes important transport and wave processes such as substorm dipolarization in global MHD fields, chorus waves, and plasmaspheric hiss. We discuss the effects of these competing processes at different phases of the storms and validate the results by comparison with satellite and ground-based observations. Keywords: Radiation Belts, Space Weather, Wave-Particle Interaction, Storm and Substorm

Fok, Mei-Ching↗
DOE OSTI2019

Investigating the effect of oxy-fuel combustion and light coal volatiles interaction: A mass spectrometric study

Given the multi-physical nature of coal combustion, the development and validation of detailed chemical models reproducing coal volatiles combustion under oxy-fuel conditions is a crucial step towards the advancement of predictive full-scale simulations. During the devolatilization process, a large variety of gases is released and undergoes secondary pyrolysis and oxidation reactions. Therefore, the ability to capture their interactions is a prerequisite for each chemical model used in its detailed or reduced form to simulate these processes. In this work, a high-resolution time-of-flight molecular-beam mass spectrometer was employed to enable fast and simultaneous detection of stable and unstable species in counterflow flames of typical light volatiles. Following an approach of increasing complexity, carbon dioxide and methane were progressively added to an argon diluted acetylene base flame. For the three flames investigated here, results showed a significant increase in the concentration of C 2 and C 3 hydrocarbons and oxygenated compounds caused by methane addition to the acetylene flame. By hindering the production of the butadienyl radical, the addition of methane induces the reduction of benzene which triggers the decrease of aromatic species. Conversely, CO 2 addition did not have significant effects on intermediates. To guide and interpret the measurements, numerical simulations with two existing chemical models were performed and the results were found to be consistent with the experimental data for small hydrocarbons. Some discrepancies were found between the two model predictions and between simulations and experiments for C 4 and C 5 species. In addition, numerical simulations were found to overestimate the role of the methyl radical in aromatics formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Development and Future of the Ten Simple Rules for Credible Practice of Models and Simulations in HealthCare

In this session, we will review the development and implementation history of the Ten Simple Rules (TSR) for credible practice in models and simulations that support healthcare. Our focus will be initially on the need and background for the Committee on Credible Practice of Models and Simulations in Healthcare (CPMS) as well as the TSR development process and implementation. This will flow into a demonstration of how the TSR has evolved as means of communicating and understanding the model development process, likely successful application and where the model could fail. We will end this presentation with a discussion on future development avenue, the CPMS efforts to develop a comprehensive rubric supporting current TSR implementation, and efforts to support further adoption of the TSR. The audience will be encouraged to comment on the current state of the TSR, share their TSR application experiences, and provide their insights on future development.

model↗