SEARCH · Search NASA

Results for “selection methodology”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

NASA NTRS1999

Apollo 17 Soil Characterization for Reflectance Spectroscopy

It is the fine fractions that dominate the observed spectral signatures of bulk lunar soil, and the next to the smallest size fractions are the most similar to the overall properties of the bulk soil. Thus, our Lunar Soil Characterization Consortium has concentrated on understanding the inter-relations of compositional, mineralogical, and optical properties of the <45-micron size fraction and its component sizes (20-44 micron, 10-20 micron, and <10 micron size fractions). To be able to generalize our results beyond the particular sample set studied, it is necessary to quantitatively identify the observed effects of space weathering and evaluate the processes involved. For this, it is necessary to know the chemistry of each size fraction, modal abundances of each phase, average compositions of the minerals and glasses, I(sub s)/FeO values, reflectance spectra, and the physical makeup of the individual particles and their patinas. This characterization includes the important dissection of the pyroxene minerals into four separate populations, with data on both modes and average chemical compositions. Armed with such data, it should be possible to effectively isolate spectral effects of space weathering from spectral properties related to mineral and glass chemistry. Four mare soils from the Apollo 17 site were selected for characterization based upon similarities in bulk composition and their contrasting maturities, ranging from immature to submature to mature. The methodology of our characterization has been discussed previously. Results of the Apollo 17 mare soils, outlined herein, are being prepared for publication in MAPS. As shown, with decreasing grain size, the agglutinitic (impact) glass content profoundly increases. This is the most impressive change for the mare soils. In several soils we have examined, there is an over two-fold increase in the agglutinitic glass contents between the 90-150- micron and the 10-20-micron size fractions. Accompanying this increase in agglutinitic glass is a definite decrease in pyroxenes and to lesser extents, the oxides (ilmenite), volcanic glass, and olivine. Unexpectedly, however, the absolute plagioclase abundances stay relatively constant throughout the different grain sizes, although the abundance of plagioclase relative to the mafic minerals increases with decreasing particle size. These soils were chosen for study based upon their similarities in FeO and Ti02 content, allowing for direct comparisons between evolutions of chemistry between size fractions and among different maturities of soils. The bulk chemistry of these fractions was determined by EMP analyses of fused glass beads. In contrast to the systematic variations in bulk chemistry discussed below, the relatively uniform composition of agglutinitic glass with grain size and soil maturity is illustrated. The composition of the bulk fraction of each size fraction becomes more feldspathic with increasing maturity, with the effect being most pronounced for the finest fractions. The composition of the agglutinitic glass, however, is relatively invariant and more feldspathic (i.e., rich in Al2O3) than even the <10-micron fraction. This relation not only strengthens the "fusion of the finest fraction" (F(sup 3)) hypothesis, but also highlights the important role of plagioclase in the formation of agglutinitic glass. With decreasing grain size, FeO, MgO, and TiO2 contents decrease, whereas CaO, Na2O, and Al2O3 (plag components) increase for all soils. These chemical variations would appear to be coupled with the significant increase in agglutinitic glass and decrease in oxide (ilmenite),pyroxene, and volcanic glass. These changes in chemistry do not appear to be due to distinct changes in the compositions of individual phases but to their abundances. Values of I(sub s)/FeO increase with decreasing grain size, even though the bulk FeO contents decrease. That is, the percentage of the total Fe that is present as nanophase Fe(sup O) has increased substantially in the smaller size fraction. Note that the increase in nanophase FeO in smaller size fractions is significantly greater than the increase in agglutinitic glass content, with its single-domain FeO component. This would seem to indicate that at least some of the FeO is surface correlated. To illustrate this effect, if it is assumed that the nanophase FeO is entirely surface correlated, then equal masses of 15-micron and 6-micron spheres should have about 3x as much FeO in the finer fraction. The recent findings of Kelleret al. of the major role of vapor-deposited, nanophase FeO-containing patinas on most soil particles is a major breakthrough in our understanding of the distribution of FeO within agglutinitic glass and upon grain surfaces. Bidirectional reflectance spectra for a representative Apollo 17 soil (70181) are shown. The size separates all have similar albedo in the blue and follow a regular sequence in which the continuum slope increases, ferrous bands weaken, and albedo, increases with decreasing particle size. The bulk <45-micron soil is typically close to the 10-20 micron spectrum. It is important to note that although the finest fraction (<10 micron) is close in composition to the abundant agglutinitic glass in each size fraction, this size fraction is relatively featureless and does not dominate the spectrum of the bulk <45-micron soil. It has long been suspected that agglutinitic glass, to a large extent, is the product of melting of the finest fraction of the soils, with a dominance of plagioclase. Given the low abundance of pyroxene in the finest fractions of each soil the source of the FeO in these Apollo 17 agglutinitic glasses is not fully identified. We suspect the abundant volcanic glass in these samples may be a significant contributor and this hypothesis will be tested with the suite under study from other Apollo sites.

Taylor, L. A.↗

NASA NTRS2015

Advancing the State-of-the-Practice for Liquid Rocket Engine Injector Design

Current shortcomings in both the overall injector design process and its underlying combustion stability assessment methodology are rooted in the use of empirically based or low fidelity representations of complex physical phenomena and geometry details that have first order effects on performance, thermal environments and combustion stability. The result is a design and analysis capability that is often inadequate to reliably arrive at a suitable injector design in an efficient manner. Specifically, combustion instability has been particularly difficult to predict and mitigate. Large hydrocarbon-fueled booster engines have been especially problematic in this regard. Where combustion instability has been a problem, costly and time-consuming redesign efforts have often been an unfortunate consequence. This paper presents an overview of a recently completed effort at NASA Marshall Space Flight Center to advance the state-of-the-practice for liquid rocket engine injector design. Multiple perturbations of a gas-centered swirl coaxial (GCSC) element that burned gaseous oxygen and RP-1 were designed, assessed for combustion stability, and tested. Three designs, one stable, one marginally unstable and one unstable, were used to demonstrate both an enhanced overall injector design process and an improved combustion stability assessment process. High-fidelity results from state-of-the-art computational fluid dynamics CFD simulations were used to substantially augment and improve the injector design methodology. The CFD results were used to inform and guide the overall injector design process. They were also used to upgrade selected empirical or low-dimensional quantities in the ROCket Combustor Interactive Design (ROCCID) stability assessment tool. Hot fire single element injector testing was used to verify both the overall injector designs and the stability assessments. Testing was conducted at the Air Force Research Laboratory and at Purdue University. Companion papers provide details of the overall injector design process, full- and sub-scale testing, ROCCID-based stability assessments and the CFD simulations.

Tucker, P. K.↗

NASA NTRSDate not supplied

Development of Improved Thermal Analysis Capabilities at the NASA Goddard Space Flight Center

Goddard Space Flight Center (GSFC) has been developing a framework of additional analysis capabilities to aid in the verification, development, and execution of thermal models using the OpenTD Application Programming Interface (API). This paper provides a brief overview of the data structures, properties, methods, and relationships between the objects accessible through the current API and describes some of the algorithms necessary to implement the desired functions at GSFC. Some example code snippets are also provided to aid potential users in the development of their own utilities. Following the overview are descriptions and algorithm methodologies of the new capabilities added to the GSFC framework, including: a new PI heater/controller approach for improved steady state predictions, selective copying of symbol over-rides from one source CaseSet to destination CaseSet(s), comparison of submodel object counts between a source and destination model to verify model integration, comparison of thermo-optical and thermo-physical properties between models, and improved display of extracted thermo-optical and thermo-physical properties for documentation.

ThermalDesktop↗

NASA NTRSDate not supplied

Development of Improved Thermal Analysis Capabilities at the NASA Goddard Space Flight Center

ThermalDesktop, API, v6.2, OpenTD↗

DOE OSTI2017

Continuous energy cross section adjustment: a new method to generalize nuclear data assimilation for a wider range of applications.

This work presents a new method to perform continuous-energy cross section adjustment. The proposed method is based on recently developed Monte Carlo perturbation capabilities with continuous-energy sensitivity functions implemented in an extended Serpent version. The generation of continuous energy basis functions aseigendecomposition of the covariance matrices and the Generalized Least Squares method applied to these functions are described. The new approach is verified against standard, multi-group adjustment methodologies in a case study involving four different response functions in Jezebel. The results obtained by the two approaches for the selected case study are presented and compared in term of adjusted cross sections, adjusted covariance matrices, and uncertainty reduction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

On BWR regional oscillations with rotational symmetry line using SIMULATE-3K

A new stability analysis methodology is being developed at the Paul Scherrer Institute (PSI) using the best-estimate coupled neutronic/thermal- hydraulics code, SIMULATE-3K (S3K). This methodology has so far been validated against Leibstadt NPP (KKL) stability tests of C10, C13 and C19, which all show global (in-phase) oscillations. However, the methodology has not yet been validated for regional instabilities and to that aim, a special KKL cycle 07 stability test was selected. Indeed, during this test, the core not only showed growing power oscillation amplitudes in an out-of-phase regime but also an oscillating and rotating symmetry line. Thereby, it was selected in order to verify the S3K capability to predict regional instabilities and on that basis, obtain more insights towards understanding the causes for the oscillatory and rotational behaviour of symmetry lines. The results obtained so far are presented in this paper. First, it is found that the S3K results are in good agreement with measurements both qualitatively and quantitatively, although the resonance frequency is slightly over-predicted. Secondly, the excitation of the out-of-phase mode with oscillations as well as rotation of the symmetry line is also well captured i.e. in accordance to the experimental observations. Related to this, an in-depth analysis of LPRM signals indicates that two out-of-phase oscillation modes associated to two azimuthal neutronic modes are simultaneously excited. Furthermore, it is found that a superposition of these two modes will trigger the symmetry line dynamics and that the behaviour will be guided by the dominance ratio between these two modes. More precisely, the oscillatory behaviour is due to the superposition of the two azimuthal modes but with one dominant mode. The rotational behaviour is however due to the superposition of the two modes with comparable strengths. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

NASA NTRSDate not supplied

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

air traffic management↗

NASA NTRS1992

Distributed intelligent control and management (DICAM) applications and support for semi-automated development

We have recently begun a 4-year effort to develop a new technology foundation and associated methodology for the rapid development of high-performance intelligent controllers. Our objective in this work is to enable system developers to create effective real-time systems for control of multiple, coordinated entities in much less time than is currently required. Our technical strategy for achieving this objective is like that in other domain-specific software efforts: analyze the domain and task underlying effective performance, construct parametric or model-based generic components and overall solutions to the task, and provide excellent means for specifying, selecting, tailoring or automatically generating the solution elements particularly appropriate for the problem at hand. In this paper, we first present our specific domain focus, briefly describe the methodology and environment we are developing to provide a more regular approach to software development, and then later describe the issues this raises for the research community and this specific workshop.

Hayes-Roth, Frederick↗

DOE OSTI2018

Design of machine learning models with domain experts for automated sensor selection for energy fault detection

Data-driven techniques that extract insights from sensor data reduce the cost of improving system energy performance through fault detection and system health monitoring. To lower cost barriers to widespread deployment, a methodology is proposed that takes advantage of existing sensor data, encodes expert knowledge about the application system to create ‘virtual sensors’ and applies statistical and mathematical methods to reduce the time required for manual configurations. The approach combines sensor data points with encoded expert knowledge that is generic to the application system but independent of a particular deployment, thereby reducing the need to tailor to individual deployments. Additionally, this paper not only presents a method that detects faults from measured energy data, but also (1) describes an engagement method with experts in the energy system domain to identify data, (2) integrates domain knowledge with the data, (3) automatically selects from among the large pool of potential input data, and (4) uses machine learning to automatically build a data-driven fault detection model. Demonstration on a commercial building chiller plant shows that only a small number of virtual sensors is necessary for fault detection with high accuracy rates. This corresponds to the use of only five out of 52 original sensor data points features. With as few as four features, classification F1 scores exceed 90% on the training set and 80% on the testing set. The results are implementable and realizable using off-the-shelf tools. The goal is to design with domain experts an energy monitoring system that can be configured once and then widely deployed with little additional cost or effort.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2011

EFFICIENT THEORETICAL SCREENING OF SOLID SORBENTS FOR CO2 CAPTURE APPLICATIONS

Carbon dioxide is a major combustion product of coal, which once released into the air can contribute to global climate change. Current CO2 capture technologies for power generation processes including amine solvents and CaO-based sorbent materials require very energy intensive regeneration steps which result in significantly decreased efficiency. Hence, there is a critical need for new materials that can capture and release CO2 reversibly with acceptable energy costs if CO2 is to be captured and sequestered economically. Inorganic sorbents are one such class of materials which typically capture CO2 through the reversible formation of carbonates. By combining thermodynamic database mining with first principles density functional theory and phonon lattice dynamics calculations, a theoretical screening methodology to identify the most promising CO2 sorbent candidates from the vast array of possible solid materials has been proposed and validated. The ab initio thermodynamic technique has the advantage of identifying thermodynamic properties of CO2 capture reactions without any experimental input beyond crystallographic structural information of the solid phases involved. For a given solid, the first step is to attempt to extract thermodynamic properties from thermodynamic databases and available literatures. If the thermodynamic properties of the compound of interest are unknown, an ab initio thermodynamic approach is used to calculate them. These properties expressed conveniently as chemical potentials and heat of reactions, either from databases or from calculations, are further used for computing the thermodynamic reaction equilibrium properties of the CO2 absorption/desorption cycle based on the chemical potential and heat of reaction. Only those solid materials for which lower capture energy costs are predicted at the desired process conditions are selected as CO2 sorbent candidates and further considered for experimental validations. Solid sorbents containing alkali and alkaline earth metals have been reported in several previous studies to be good candidates for CO2 sorbent applications due to their high CO2 absorption capacity at moderate working temperatures. In addition to introducing our selection process in this presentation, we will present our results for solid systems of alkali and alkaline metal oxides, hydroxides and carbonates/bicarbonates to validate our methodology. Additionally, applications of our computational method to mixed solid systems of Li2O and SiO2 with different mixing ratios, we showed that increasing the Li2O/SiO2 ratio in lithium silicates increases their corresponding turnover temperatures for CO2 capture reactions. These theoretical predictions are in good agreement with available experimental findings.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS1998

Methodology for Examining the Operator and the System Concurrently: Pilot Interaction with Automation

Complex system description is problematic when considering operator task activities interacting with system dynamics. Engineering languages have matured sufficiently to allow machine system description at various levels of depth and breadth but without operator synergy. Concurrently, Task Analysis methods have evolved along diverse lines enabling a description of the operator in the system from various paradigms but not describing the system. A void exists when attempting to view the system and the operator in the same plane. We propose a methodology employing descriptive languages from different domains viewed in a single dimension. Finite Automata (FA) languages describe the machine system in the proposed approach. Operator task specifications, a form of task analysis output, examine the operator activities within the system. Operator task specifications were then selected for discrete task activities and overlaid on the system description to examine operator inputs and subsequently view system responses. Unexpected (surprise) and undesirable system behavior was expected to emerge from this analysis. In this paper we shall first describe the methodology and show how the two perspectives, machine model and operator task specifications are integrated. Following we describe the process of doing such analysis using an example from cockpit automation. The methodology was employed in the analysis of a new function that was added to an existing automatic flight control system. We begin by defining a flight scenario involving all aspects of pilot interaction with the new function. Then, we proceed to develop a basic model of the machine behavior, in the context of pilot actions. Finally we superimpose the operator task specification on the machine model and perform the analysis. The proposed methodology may have broad appeal to system designers and human factors specialists. A common language for engineers of diverse domains is a strong point of this approach. Systems engineers may not fully understand operational considerations and human limitations, and human factors specialists may not be exposed to the full extent of system behavior. We hope the proposed methodology is adopted by both disciplines and in the process each assimilates a common language to address potential shortcomings of either approach separately.

Austin, David↗

DOE OSTI2017

New Architectures for Designed Catalysts: Selective Oxidation using AgAu Nanoparticles on Colloid-Templated Silica

A highly modular synthesis of designed catalysts with controlled bimetallic nanoparticle size and composition and a well-defined structural hierarchy is shown. Exemplary catalysts—bimetallic dilute Ag-in-Au nanoparticles partially embedded in a porous SiO 2 matrix (SiO 2 –Ag x Au y )—were synthesized by the decoration of polymeric colloids with the bimetallic nanoparticles followed by assembly into a colloidal crystal backfilled with the matrix precursor and subsequent removal of the polymeric template. This work reports that these new catalyst architectures are significantly better than nanoporous dilute AgAu alloy catalysts (nanoporous Ag 3 Au 97 ) while retaining a clear predictive relationship between their surface reactivity with that of single-crystal Au surfaces. This paves the way for broadening the range of new catalyst architectures required for translating the designed principles developed under controlled conditions to designed catalysts under operating conditions for highly selective coupling of alcohols to form esters. Excellent catalytic performance of the porous SiO 2 –Ag x Au y structure for selective oxidation of both methanol and ethanol to produce esters with high conversion efficiency, selectivity, and stability was demonstrated, illustrating the ability to translate design principles developed for support-free materials to the colloid-templated structures. The synthetic methodology reported is customizable for the design of a wide range of robust catalytic systems inspired by design principles derived from model studies. Fine control over the composition, morphology, size, distribution, and availability of the supported nanoparticles was discussed.

36 MATERIALS SCIENCE↗

NASA NTRS1979

Thermal power systems small power systems applications project. Volume 2: Detailed report

Small power system technology as applied to power plants up to 10 MW in size was considered. Markets for small power systems were characterized and cost goals were established for the project. Candidate power plant system design concepts were selected for evaluation and preliminary performance and cost assessments were made. Breakeven capital costs were determined for leading contenders among the candidate systems. The potential use of small power systems in providing part of the demand for pumping power by the extensive aqueduct system of California, was studied. Criteria and methodologies were developed for the ranking of candidate power plant system design concepts. Experimental power plant concepts of 1 MW rating were studied to define a power plant configuration for subsequent detail design construction, testing and evaluation. Site selection criteria and ground rules were developed.

Marriott, A. T.↗

DOE OSTI2021

Emergence of nosocomial associated opportunistic pathogens in the gut microbiome after antibiotic treatment

Introduction: According to the Centers for Disease Control’s 2015 Hospital Acquired Infection Hospital Prevalence Survey, 1 in 31 hospital patients was infected with at least one nosocomial pathogen while being treated for unrelated issues. Many studies associate antibiotic administration with nosocomial infection occurrence. However, to our knowledge, there is little to no direct evidence of antibiotic administration selecting for nosocomial opportunistic pathogens. Aim: This study aims to confirm gut microbiota shifts in an animal model of antibiotic treatment to determine whether antibiotic use favors pathogenic bacteria. Methodology: We utilized next-generation sequencing and in-house metagenomic assembly and taxonomic assignment pipelines on the fecal microbiota of a urinary tract infection mouse model with and without antibiotic treatment. Results: Antibiotic therapy decreased the number of detectable species of bacteria by at least 20-fold. Furthermore, the gut microbiota of antibiotic treated mice had a significant increase of opportunistic pathogens that have been implicated in nosocomial infections, like Acinetobacter calcoaceticus/baumannii complex, Chlamydia abortus, Bacteroides fragilis, and Bacteroides thetaiotaomicron. Moreover, antibiotic treatment selected for antibiotic resistant gene enriched subpopulations for many of these opportunistic pathogens. Conclusions: Oral antibiotic therapy may select for common opportunistic pathogens responsible for nosocomial infections. In this study opportunistic pathogens present after antibiotic therapy harbored more antibiotic resistant genes than populations of opportunistic pathogens before treatment. Our results demonstrate the effects of antibiotic therapy on induced dysbiosis and expansion of opportunistic pathogen populations and antibiotic resistant subpopulations of those pathogens. Follow-up studies with larger samples sizes and potentially controlled clinical investigations should be performed to confirm our findings.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Gaussian kernel density functions for compositional quantification in atom probe tomography

Highlights: • A methodology for compositional quantification from atom probe tomography is proposed. • A probability density function p(x) given discrete data points is constructed. • Each atom approximated by a Gaussian function with a particular smoothing parameter. • Density Kernel functions are used to find the optimum smoothing parameter. • The method is validated by using simulated data of semiconductor materials. - Abstract: Atom probe tomography (APT) has the ability to identify the nature and position of single atoms in a material with an almost 3D atomic resolution. However, the quantification of the material composition requires an appropriate treatment of the discrete APT data. When the amount of atoms selected to quantify the composition is relatively small, the spatial resolution is enhanced but the statistical error worsens. Conversely, the increase in the number of atoms considered reduces the spatial resolution, but improving the statistics. We have developed a methodology to reach an optimum equilibrium between the positional and the statistical error in an unsupervised form using Gaussian Kernel density functions. The validity of the method has been tested using APT simulated data of semiconductor materials. It has been proved that the chemical quantification in these materials requires the appropriate selection of the smoothing parameter, obtained without user intervention. In addition, the results have been compared to the usual techniques for composition measurement from APT data (voxelization and proximity histograms), showing better precision for high spatial resolution. This work supplies a data driven methodology based in Gaussian Kernel density functions for the accurate quantification of the composition from APT data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Alaska Daily Extreme Precipitation Processes in a Subset of CMIP5 Global Climate Models

We analyze physical processes leading to daily wintertime (December, January, and February) extreme precipitation events in Alaska between 1986 and 2005. This is done by applying self-organizing maps to environmental conditions corresponding to National Centers for Environmental Information precipitation, using the European Centre for Medium-Range Weather Forecasts reanalysis (ERA-Interim) and Coupled Model Intercomparison Project 5 (CMIP5) global climate selected Global climate model (GCM; selected GCMs). We focus on widespread extreme events, defined as the top 0.1% of daily precipitation occurring on at least six grid boxes on the same day. The self-organizing maps methodology allows identifying large-scale circulations conducive to extreme events. This methodology identifies distinctive circulation patterns conducive to producing extreme events with a trough west of Alaska leading to south or southwest flow across the state. Extreme events occur along the windward (southern) side of the Alaska Range due to uplift by the mountains in the ERA-Interim and in all models. In the National Centers for Environmental Information observations, precipitation rates are greater than in any of the selected GCMs. Simulated extreme precipitation decreases as model resolution decreases, and our study suggests that the smoothness of model topography is a reason for the scaling between model precipitation rate and model resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗