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At least 1,261 records · Page 70

ARM Research in the Equatorial Western Pacific: A Decade and Counting

The tropical western Pacific (TWP) is an important climatic region. Strong solar heating, warm sea surface temperatures, and the annual progression of the intertropical convergence zone (ITCZ) across this region generate abundant convective systems, which through their effects on the heat and water budgets have a profound impact on global climate and precipitation. In order to accurately evaluate tropical cloud systems in models, measurements of tropical clouds, the environment in which they reside, and their impact on the radiation and water budgets are needed. Because of the remote location, ground-based datasets of cloud, atmosphere, and radiation properties from the TWP region have come primarily from short-term field experiments. While providing extremely useful information on physical processes, these short-term datasets are limited in statistical and climatological information. To provide longterm measurements of the surface radiation budget in the tropics and the atmospheric properties that affect it, the Atmospheric Radiation Measurement program established a measurement site on Manus Island, Papua New Guinea, in 1996 and on the island republic of Nauru in late 1998. These sites provide unique datasets now available for more than 10 years on Manus and Nauru. This article presents examples of the scientific use of these datasets including characterization of cloud properties, analysis of cloud radiative forcing, model studies of tropical clouds and processes, and validation of satellite algorithms. New instrumentation recently installed at the Manus site will provide expanded opportunities for tropical atmospheric science.

tropical regions↗

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗

Modeling Spacecraft Safe Mode Events

Spacecraft enter a ‘safe mode’ to protect the vehicle when a potentially harmful anomaly occurs. This minimally functioning state isolates faults, establishes contact with Earth, and orients the vehicle into a power positive attitude until operators intervene. Though ‘safings’ are inherently unpredictable, mission teams build in time margin during operations to determine root causes and restore functionality. Planning and managing this margin is both critical and enabling on mission architectures dependent on near-continuous operability – such as a low-thrust electric propulsion mission. To better quantify the occurrences and severity of safe mode anomalies, the Jet Propulsion Laboratory (JPL) has assembled a database of safings from past and active missions. Currently nearly 240 records are captured from 21 beyond-Earth missions, stemming from a collaboration between teams at JPL, Ames Research Center, Goddard Space Flight Center, and the Johns Hopkins University Applied Physics Laboratory. This paper discusses the event database, explores a statistical approach in modeling the occurrences and severity of safing events, presents a simulation technique, and details recommendations and future work to benefit future concepts.

Nicholas, Austin↗

Microbial Cell Imaging

Atomic force microscopy (AFM) is finding increasing application in a variety of fields including microbiology. Until the emergence of AFM, techniques for ivnestigating processes in single microbes were limited. From a biologist's perspective, the fact that AFM can be used to generate high-resolution images in buffers or media is its most appealing feature as live-cell imaging can be pursued. Imaging living cells by AFM allows dynamic biological events to be studied, at the nanoscale, in real time. Few areas of biological research have as much to gain as microbiology from the application of AFM. Whereas the scale of microbes places them near the limit of resolution for light microscopy. AFM is well suited for the study of structures on the order of a micron or less. Although electron microscopy techniques have been the standard for high-resolution imaging of microbes, AFM is quickly gaining favor for several reasons. First, fixatives that impair biological activity are not required. Second, AFM is capable of detecting forces in the pN range, and precise control of the force applied to the cantilever can be maintained. This combination facilitates the evaluation of physical characteristics of microbes. Third, rather than yielding the composite, statistical average of cell populations, as is the case with many biochemical assays, the behavior of single cells can be monitored. Despite the potential of AFM in microbiology, there are several limitations that must be considered. For example, the time required to record an image allows for the study of gross events such as cell division or membrane degradation from an antibiotic but precludes the evaluation of biological reactions and events that happen in just fractions of a second. Additionally, the AFM is a topographical tool and is restricted to imaging surfaces. Therefore, it cannot be used to look inside cells as with opticla and transmission electron microscopes. other practical considerations are the limitation on the maximum scan size (roughly 100 x 100 {mu}m) and the restricted movement of the cantilever in the Z (or height) direction. In most commercial AFMs, the Z range is restricted to roughly 10 {mu}m such that the height of cells to be imaged must be seriously considered. Nevertheless, AFM can provide structural-functional information at nanometer resolution and do so in physiologically relevant environments. Further, instrumentation for scanning probe microscopy continues to advance. Systems for high-speed imaging are becoming available, and techniques for looking inside the cells are being demonstrated. The ability to combine AFM with other imaging modalities is likely to have an even greater impact on microbiological studies. AFM studies of intact microbial cells started to appear in the literature in the 1990s. For example, AFM studies of Saccharomyces cerevisiae examined buddings cars after cell division and detailed changes related to cell growth processes. Also, the first AFM studies of bacterial biofilms appeared. In the late 1990s, AFM studies of intact fungal spores described clear changes in spore surfaces upon germination, and studies of individual bacterial cells were also described. These early bacterial imaging studies examined changes in bacterial morphology due to antimicrobial peptides exposure and bacterial adhesion properties. The majority of these early studies were carried out on dried samples and took advantage of the resolving power of AFM. The lack of cell mounting procedures presented an impediment for cell imaging studies. Subsequently, several approaches to mounting microbial cells have been developed, and these techniques are described later. Also highlighted are general considerations for microbial imaging and a description of some of the various applications of AFM to microbiology.

60 APPLIED LIFE SCIENCES↗

MODELING GALACTIC EXTINCTION WITH DUST AND 'REAL' POLYCYCLIC AROMATIC HYDROCARBONS

We investigate the remarkable apparent variety of galactic extinction curves by modeling extinction profiles with core-mantle grains and a collection of single polycyclic aromatic hydrocarbons. Our aim is to translate a synthetic description of dust into physically well-grounded building blocks through the analysis of a statistically relevant sample of different extinction curves. All different flavors of observed extinction curves, ranging from the average galactic extinction curve to virtually 'bumpless' profiles, can be described by the present model. We prove that a mixture of a relatively small number (54 species in 4 charge states each) of polycyclic aromatic hydrocarbons can reproduce the features of the extinction curve in the ultraviolet, dismissing an old objection to the contribution of polycyclic aromatic hydrocarbons to the interstellar extinction curve. Despite the large number of free parameters (at most the 54 Multiplication-Sign 4 column densities of each species in each ionization state included in the molecular ensemble plus the 9 parameters defining the physical properties of classical particles), we can strongly constrain some physically relevant properties such as the total number of C atoms in all species and the mean charge of the mixture. Such properties are found to be largely independent of the adopted dust model whose variation provides effects that are orthogonal to those brought about by the molecular component. Finally, the fitting procedure, together with some physical sense, suggests (but does not require) the presence of an additional component of chemically different very small carbonaceous grains.

79 ASTRONOMY AND ASTROPHYSICS↗

Ideal gas in a strong gravitational field: Area dependence of entropy

We study the thermodynamic parameters like entropy, energy etc. of a box of gas made up of indistinguishable particles when the box is kept in various static background spacetimes having a horizon. We compute the thermodynamic variables using both statistical mechanics as well as by solving the hydrodynamical equations for the system. When the box is far away from the horizon, the entropy of the gas depends on the volume of the box except for small corrections due to background geometry. As the box is moved closer to the horizon with one (leading) edge of the box at about Planck length (L{sub p}) away from the horizon, the entropy shows an area dependence rather than a volume dependence. More precisely, it depends on a small volume A{sub perpendicular}L{sub p}/2 of the box, up to an order O(L{sub p}/K){sup 2} where A{sub perpendicular} is the transverse area of the box and K is the (proper) longitudinal size of the box related to the distance between leading and trailing edge in the vertical direction (i.e. in the direction of the gravitational field). Thus the contribution to the entropy comes from only a fraction O(L{sub p}/K) of the matter degrees of freedom and the rest are suppressed when the box approaches the horizon. Near the horizon all the thermodynamical quantities behave as though the box of gas has a volume A{sub perpendicular}L{sub p}/2 and is kept in a Minkowski spacetime. These effects are: (i) purely kinematic in their origin and are independent of the spacetime curvature (in the sense that the Rindler approximation of the metric near the horizon can reproduce the results) and (ii) observer dependent. When the equilibrium temperature of the gas is taken to be equal to the horizon temperature, we get the familiar A{sub perpendicular}/L{sub p}{sup 2} dependence in the expression for entropy. All these results hold in a D+1 dimensional spherically symmetric spacetime. The analysis based on methods of statistical mechanics and the one based on thermodynamics applied to the gas treated as a fluid in static geometry, lead to the same results showing the consistency. The implications are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Shower Reconstruction for Cross-Section Measurements with Photon(s) in the Final State at SBND

The Short-Baseline Near Detector (SBND) is a 112-ton liquid argon time projection chamber operating in the Booster Neutrino Beam at Fermilab as part of the Short-Baseline Neutrino Program. Precise reconstruction of electromagnetic showers from photons and electrons is essential for searches for neutrino oscillations, cross-section measurements, and rare-process studies in liquid argon. In this poster, we present a unified set of SBND analyses enabled by the SPINE (Scalable Particle Imaging with Neural Embeddings) end-to-end machine-learning–based reconstruction framework, highlighting charged-current neutral pion (CC π⁰) production and neutral-current (NC) Δ radiative decay as complementary physics cases. Charged-current π⁰ interactions provide a high-statistics benchmark for validating photon reconstruction, constraining the electromagnetic energy scale, and modeling backgrounds to other cross-section measurements and BSM searches with one or more photons in the final state. We summarize progress toward the ongoing development of a CC π⁰ selection in SBND and, report on the current status of a search for NC resonant Δ production followed by radiative decay (Δ→Nγ) in SBND. This rare process, previously investigated in MicroBooNE, provides a stringent test of photon-only final-state reconstruction and is of interest in the context of the MiniBooNE low-energy excess. Together, these analyses demonstrate how modern machine-learning–based shower reconstruction enables a diverse and scalable physics program at SBND.

Chung, Seokju [Nevis Labs, Columbia U.]↗

Spectral analysis for the M AJORNA D EMONSTRATOR experiment

The M AJORNA D EMONSTRATOR is an experiment constructed to search for neutrinoless double-beta decays in germanium-76 and to demonstrate the feasibility to deploy a ton-scale experiment in a phased and modular fashion. It consists of two modular arrays of natural and 76 Ge-enriched germanium detectors totaling 44.1kg (29.7kg enriched detectors), located at the 4850' level of the Sanford Underground Research Facility in Lead, South Dakota, USA. Data taken with this setup since summer 2015 at different construction stages of the experiment show a clear reduction of the observed background index around the ROI for 0$νββ$- decay search due to improvements in shielding. We discuss the statistical approaches to search for a 0$νββ$-signal and derive the physics sensitivity for an expected exposure of 10kg y from enriched detectors using a profile likelihood based hypothesis test in combination with toy Monte Carlo data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Opacity of iron, nickel, and copper plasmas in the x-ray wavelength range: Theoretical interpretation of 2p-3d absorption spectra

This paper deals with theoretical studies on the 2p-3d absorption in iron, nickel, and copper plasmas related to LULI2000 (Laboratoire pour l'Utilisation des Lasers Intenses, 2000J facility) measurements in which target temperatures were of the order of 20 eV and plasma densities were in the range 0.004-0.01 g/cm{sup 3}. The radiatively heated targets were close to local thermodynamic equilibrium (LTE). The structure of 2p-3d transitions has been studied with the help of the statistical superconfiguration opacity code sco and with the fine-structure atomic physics codes hullac and fac. A new mixed version of the sco code allowing one to treat part of the configurations by detailed calculation based on the Cowan's code rcg has been also used in these comparisons. Special attention was paid to comparisons between theory and experiment concerning the term features which cannot be reproduced by sco. The differences in the spin-orbit splitting and the statistical (thermal) broadening of the 2p-3d transitions have been investigated as a function of the atomic number Z. It appears that at the conditions of the experiment the role of the term and configuration broadening was different in the three analyzed elements, this broadening being sensitive to the atomic number. Some effects of the temperature gradients and possible non-LTE effects have been studied with the help of the radiative-collisional code scric. The sensitivity of the 2p-3d structures with respect to temperature and density in medium-Z plasmas may be helpful for diagnostics of LTE plasmas especially in future experiments on the {Delta}n=0 absorption in medium-Z plasmas for astrophysical applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Detector noise statistics in the non-linear regime

The statistical behavior of an idealized linear detector in the presence of threshold and saturation levels is examined. It is assumed that the noise is governed by the statistical fluctuations in the number of photons emitted by the source during an exposure. Since physical detectors cannot have infinite dynamic range, our model illustrates that all devices have non-linear regimes, particularly at high count rates. The primary effect is a decrease in the statistical variance about the mean signal due to a portion of the expected noise distribution being removed via clipping. Higher order statistical moments are also examined, in particular, skewness and kurtosis. In principle, the expected distortion in the detector noise characteristics can be calibrated using flatfield observations with count rates matched to the observations. For this purpose, some basic statistical methods that utilize Fourier analysis techniques are described.

Shopbell, P. L.↗

Evaluation of the 29-km Eta Model: Objective Verification at Three Selected Stations - Part 1

This paper describes an objective verification of the National Centers for Environmental Prediction (NCEP) 29-km eta model from May 1996 through January 1998. The evaluation was designed to assess the model's surface and upper-air point forecast accuracy at three selected locations during separate warm (May - August) and cool (October - January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods. Systematic model deficiencies comprise the larger portion of the total error in most of the surface forecast variables that were evaluated. The error characteristics for both surface and upper-air forecasts vary widely by parameter, season, and station location. At upper levels, a few characteristic biases are identified. Overall however, the upper-level errors are more nonsystematic in nature and could be explained partly by observational measurement uncertainty. With a few exceptions, the upper-air results also indicate that 24-h model error growth is not statistically significant. In February and August 1997, NCEP implemented upgrades to the eta model's physical parameterizations that were designed to change some of the model's error characteristics near the surface. The results shown in this paper indicate that these upgrades led to identifiable and statistically significant changes in forecast accuracy for selected surface parameters. While some of the changes were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts. Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the meso-eta model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter. Overall verification results presented here and in part two should establish a reasonable benchmark from which model users and developers may pursue the ongoing eta model verification strategies in the future.

Nutter, Paul A.↗

Advanced Mesh-Enabled Monte Carlo Capability for Multi-Physics Reactor Analysis

This project will accumulate high-precision fluxes throughout reactor geometry on a non-orthogonal grid of cells to support multi-physics coupling, in order to more accurately calculate parameters such as reactivity coefficients and to generate multi-group cross sections. This work will be based upon recent developments to incorporate advanced geometry and mesh capability in a modular Monte Carlo toolkit with computational science technology that is in use in related reactor simulation software development. Coupling this capability with production-scale Monte Carlo radiation transport codes can provide advanced and extensible test-beds for these developments. Continuous energy Monte Carlo methods are generally considered to be the most accurate computational tool for simulating radiation transport in complex geometries, particularly neutron transport in reactors. Nevertheless, there are several limitations for their use in reactor analysis. Most significantly, there is a trade-off between the fidelity of results in phase space, statistical accuracy, and the amount of computer time required for simulation. Consequently, to achieve an acceptable level of statistical convergence in high-fidelity results required for modern coupled multi-physics analysis, the required computer time makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. More subtly, the statistical uncertainty is typically not uniform throughout the domain, and the simulation quality is limited by the regions with the largest statistical uncertainty. In addition, the formulation of neutron scattering laws in continuous energy Monte Carlo methods makes it difficult to calculate adjoint neutron fluxes required to properly determine important reactivity parameters. Finally, most Monte Carlo codes available for reactor analysis have relied on orthogonal hexahedral grids for tallies that do not conform to the geometric boundaries and are thus generally not well-suited to coupling with the unstructured meshes that are used in other physics simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Photoluminescence of A- and B-site Eu{sup 3+}-substituted (Sr{sub x}Ba{sub 1−x}){sub 2}CaW{sub y}Mo{sub 1−y}O{sub 6} phosphors

The photoluminescence of two series of A- and B-site Eu{sup 3+} substituted (Sr{sub x}Ba{sub 1−x}){sub 2}CaW{sub y}Mo{sub 1−y}O{sub 6} double perovskite phosphor materials, (Sr{sub x}Ba{sub 1−x}){sub 1.96}Eu{sub 0.02}K{sub 0.02}CaW{sub y}Mo{sub 1−y}O{sub 6} and (Sr{sub x}Ba{sub 1−x}){sub 2}Ca{sub 0.96}Eu{sub 0.02}Li{sub 0.02}W{sub y}Mo{sub 1−y}O{sub 6} (x and y=0, 0.25, 0.50, 0.75, and 1), were studied systematically as a function of stoichiometry and crystal structure. The Eu{sup 3+} lattice sites controlled by co-doping with either K or Li were confirmed by Raman spectroscopy. The variation in integrated emission intensity and emission colour over the experimental matrix was examined using statistical tools, and the observed trends were rationalized based on the physical and electronic structure of the phosphors. Phosphors with Eu on B-site with maximum Sr content had remarkably higher emission intensities than all other materials, but the emission was more orange than red due to domination of the {sup 5}D{sub 0}–{sup 7}F{sub 1} (595 nm) transition of Eu{sup 3+}. The relative intensities of the {sup 5}D{sub 0}–{sup 7}F{sub 2} (615 nm) and {sup 5}D{sub 0}–{sup 7}F{sub 1} transitions of Eu{sup 3+}, and thus the red-shift of the emission, decreased linearly with increasing Sr content in the A-site Eu-substituted phosphors, and reached a maximum for Sr{sub 1.96}Eu{sub 0.02}K{sub 0.02}CaW{sub 0.25}Mo{sub 0.75}O{sub 6}. A maximum external quantum efficiency of 17% was obtained for the phosphor Sr{sub 2}Ca{sub 0.7}Eu{sub 0.15}Li{sub 0.15}W{sub 0.5}Mo{sub 0.5}O{sub 6} with Eu on B-site. - Highlights: • Systematic study of the photoluminescence of Eu{sup 3+}-doped (Sr{sub x}Ba{sub 1−x}){sub 2}CaW{sub y}Mo{sub 1−y}O{sub 6}. • The Eu{sup 3+} lattice sites were confirmed by Raman spectroscopy. • A large parameter space was investigated using statistical tools. • A maximum external QE of 17% was obtained for Sr{sub 2}Ca{sub 0.7}Eu{sub 0.15}Li{sub 0.15}W{sub 0.5}Mo{sub 0.5}O{sub 6}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting turbulent wake flow of marine hydrokinetic turbine arrays in large-scale waterways via physics-enhanced convolutional neural networks

We present a physics-enhanced convolutional neural network (PECNN) algorithm for reconstructing the mean flow and turbulence statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large-scale meandering rivers. The algorithm embeds the mass and momentum conservation equations into the loss function of the PECNN algorithm to improve the physical realism of the reconstructed flow fields. The PECNN is trained using large eddy simulation (LES) results of the wake flow of a single row of turbines in a virtual meandering river. Subsequently, the trained PECNN is applied to predict the wake flow of MHK turbines with arrangements and positionings different than those considered during the training process. The PECNN predictions are validated using the results of separately performed LES. The results show that the PECNN algorithm can accurately predict the wake flow of MHK turbine farms at a small fraction of the cost of LES. The PECNN can improve the accuracy by around 1% and reduce the physical constraint indices by around 50% compared to the CNN without physical constraints. This work underscores the potential of PECNN to develop reduced-order models for control co-design and optimization of MHK turbine arrays in natural riverine environments.

Mechanics↗

Research Opportunities in the Physical Design Optimization of Hybrid Power Plants: Preprint

With renewable energy growing to 10%-20% or more of overall electricity generation, design objectives for renewable power plants are shifting from producing energy at the lowest levelized cost to maximizing profitability. Several research and commercial efforts have investigated how to size respective generation and storage assets together for hybrid power plant systems - including wind, solar, battery storage and other technologies. However, the physical design of hybrid power plants has yet to be considered in detail. Even the design of individual solar and wind power plants is complex with large numbers of design variables, constraints and complex physical interactions across subsystems. Developing an integrated approach for the design of hybrid power plants including multiple generation technologies compounds this complexity and requires domain knowledge across the technologies as well as new approaches for addressing the statistical representation of resource availability and revenue opportunities. To inform the research needs on physical design of these hybrid power plants, a workshop was held in December 2018 at the National Renewable Energy Laboratory. This paper provides a summary of findings from the workshop on research needs for hybrid power plant design.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Generic results of the space physics community survey

This report summarizes the results of a survey of the members of the space physics research community conducted in 1990-1991 to ascertain demographic information on the respondents and information on their views on a number of facets of their space physics research. The survey was conducted by questionnaire and the information received was compiled in a database and analyzed statistically. The statistical results are presented for the respondent population as a whole and by four different respondent cross sections: individual disciplines of space physics, type of employers, age groups, and research techniques employed. Data from a brief corresponding survey of the graduate students of respondents are also included.

Sharma, Rikhi R.↗

Surface coverage dynamics for reversible dissociative adsorption on finite linear lattices

Dissociative adsorption onto a surface introduces dynamic correlations between neighboring sites not found in non-dissociative absorption. We study surface coverage dynamics where reversible dissociative adsorption of dimers occurs on a finite linear lattice. We derive analytic expressions for the equilibrium surface coverage as a function of the number of reactive sites, N, and the ratio of the adsorption and desorption rates. Using these results, we characterize the finite size effect on the equilibrium surface coverage. For comparable N’s, the finite size effect is significantly larger when N is even than when N is odd. Moreover, as N increases, the size effect decays more slowly in the even case than in the odd case. The finite-size effect becomes significant when adsorption and desorption rates are considerably different. These finite-size effects are related to the number of accessible configurations in a finite system where the odd-even dependence arises from the limited number of accessible configurations in the even case. We confirm our analytical results with kinetic Monte Carlo simulations. We also analyze the surface-diffusion case where adsorbed atoms can hop into neighboring sites. As expected, the odd-even dependence disappears because more configurations are accessible in the even case due to surface diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data mining and statistical inference in selective laser melting

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations and experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.

36 MATERIALS SCIENCE↗