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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Self-Supplied Liquid Injection Field Desorption/Ionization Ion Source for an Orthogonal Time-of-Flight Instrument

A new implementation of a dedicated ion source for field ionization (FI), field desorption (FD), and liquid injection field desorption/ionization (LIFDI) for the JEOL AccuTOF GC series of orthogonal-acceleration time-of-flight instruments is presented. In contrast to existing implementations, this third-party LIFDI probe and source combination does not require the exchange of the entire ion source comprising ion source block and lens stack to switch from electron ionization (EI) to LIFDI. Rather, the methods may be swapped conveniently by only exchanging the ion source block for a mechanical probe guide and inserting the LIFDI probe in place of the standard direct insertion probe (DIP) via the vacuum lock. Further, this LIFDI setup does not require any changes of the electronics or software of the AccuTOF mass spectrometer because it is self-supplied in terms of power supply, observation optics, and computer control. The setup offers advanced FI/FD/LIFDI control features such as emission-controlled emitter heating current and emitter flash baking during elongated runs as required for gas chromatography-FI-mass spectrometry (MS). The LIFDI source and probe and its operation are reported in detail. FI spectra of the volatile analytes toluene, heptane, and pentafluoroiodobenzene are presented. LIFDI operation is demonstrated for the analysis of the saturated hydrocarbon dotriacontane and the low-mass hydrocarbon polymers polystyrene 484 and polystyrene 1050. Further, the air-sensitive 2nd-generation Hoveyda–Grubbs catalyst is analyzed by LIFDI-MS. For comparison with long-established LIFDI instrumentation, some of the spectra obtained with the new setup are also compared with those from a double-focusing magnetic sector instrument. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope

From neutron user principal investigator: We kindly request the public release of three neutron imaging datasets through ONCat. All datasets were collected from two forensic specimens, B12W and M8N, sectioned from zinc-filled steel-wire sockets recovered from the collapsed Arecibo Telescope. The dataset titled “Neutron radiographs of B12W and M8N socket sections of the Arecibo telescope” contains normalized two-dimensional (2D) neutron radiographs of the specimens, showing the geometry and spatial distribution of the steel wires embedded within the zinc matrix, as well as internal features such as voids and cracks. The dataset titled “Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope” contains normalized 2D neutron projection images acquired over a range of specimen rotation angles for one selected region of each specimen. These projection images were used to reconstruct three-dimensional (3D) tomographic volumes that reveal the embedded-wire geometry and internal defects. The dataset titled “Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope” contains six time-of-flight (TOF) neutron imaging datasets, three from each specimen, acquired at regions of interest selected based on the radiographs. The spatially resolved 2D TOF images show the zinc matrix and embedded steel wires, and the wavelength-dependent neutron transmission data were used to characterize crystallographic texture within the zinc. All components and their condition are in the public domain as they are the property of the National Science Foundation (NSF). The neutron imaging data, part geometries, and detailed forensic information have been widely published in the Arecibo Telescope Collapse Forensic Report by Thornton Tomasetti Engineers and others (NASA report and NASEM report).

Bilheux, Hassina↗
DOE OSTI2013

Tile-Based Fisher-Ratio Software for Improved Feature Selection Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Data

Two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS) is a highly capable instrumental platform that produces complex and information-rich multi-dimensional chemical data. The complex data can be overwhelming, especially when many samples (of various sample classes) are analyzed with multiple injections for each sample. Thus, the data must be analyzed in such a way to extract the most meaningful information. The pixel-based and peak table-based algorithmic use of Fisher ratios has been used successfully in the past to reduce the multi-dimensional data down to those chemical compounds that are changing between classes relative to those that are not (i.e., chemical feature selection). We report on the initial development of a computationally fast novel tile-based Fisher-ratio software that addresses challenges due to 2D retention time misalignment without explicitly aligning the data, which is a problem for both pixel-based and peak table- based methods. Concurrently, the tile-based Fisher-ratio software maximizes the sensitivity contrast of true positives against a background of potential false positives and noise. To study this software, eight compounds, plus one internal standard, were spiked into diesel at various concentrations. The tile-based F-ratio software was able to discover all spiked analytes, within the complex diesel sample matrix with thousands of potential false positives, in each possible concentration comparison, even at the lowest absolute spiked analyte concentration ratio of 1.06.

chemometrics↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗
DOE OSTI2019

Robustness to hydrodynamic instabilities in indirectly driven layered capsule implosions

Here, we report on a high convergence ratio liquid layer capsule implosion performed on the National Ignition Facility and contrast it to two previously reported layered implosions, in order to better understand how the capsule design impacts the hydrodynamic stability properties of implosions. Three implosions were performed with similar convergence ratios, fuel entropy, in-flight aspect ratios, and unablated shell mass; these qualities are important for determining hydrodynamic stability. Nevertheless, while two of these implosions exhibited robustness to asymmetries, including our recent experiment that had abnormally large amplitude long-wavelength capsule asymmetries, and produced more than 80% or the yield predicted by one-dimensional (1D) simulations, which do not account for the impacts of hydrodynamic instabilities, the third implosion produced only 14% of the yield from a 1D simulation. We perform a detailed computational analysis of these three shots, which suggests that the combination of several large asymmetry seeds result in the significantly degraded performance: a large 30 μm fill tube, the presence of a microstructure in the high density carbon ablator, and a higher level of drive asymmetry. This indicates that while it is possible to stabilize a high convergence ratio implosion through various means, the factors that determine stability cannot be considered independently. Furthermore, when these asymmetries are combined in 2D simulations, they can exhibit destructive interference and underpredict the yield degradation compared to experiment and three-dimensional simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A probabilistic graphical model foundation for enabling predictive digital twins at scale

A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset–twin system as a set of coupled dynamical systems, evolving over time through their respective state spaces and interacting via observed data and control inputs. The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems and control theory. The declarative and general nature of the proposed digital twin model make it rigorous yet flexible, enabling its application at scale in a diverse range of application areas. Here, we demonstrate how the model is instantiated to enable a structural digital twin of an unmanned aerial vehicle (UAV). The digital twin is calibrated using experimental data from a physical UAV asset. Its use in dynamic decision-making is then illustrated in a synthetic example where the UAV undergoes an in-flight damage event and the digital twin is dynamically updated using sensor data. The graphical model foundation ensures that the digital twin calibration and updating process is principled, unified and able to scale to an entire fleet of digital twins.

42 ENGINEERING↗
DOE OSTI2017

Combined Experimental and Computational Study on the Unimolecular Decomposition of JP-8 Jet Fuel Surrogates. II: n-Dodecane (n-C 12 H 26 )

In this paper, we investigated temperature-dependent products in the pyrolysis of helium-seeded n-dodecane, which represents a surrogate of the n-alkane fraction of Jet Propellant-8 (JP-8) aviation fuel. The experiments were performed in a high temperature chemical reactor over a temperature range of 1200 K to 1600 K at a pressure of 600 Torr, with in situ identification of the nascent products in a supersonic molecular beam using single photon vacuum ultraviolet (VUV) photoionization coupled with the analysis of the ions in a reflectron time-of-flight mass spectrometer (ReTOF). For the first time, the initial decomposition products of n-dodecane—including radicals and thermally labile closed-shell species—were probed in experiments, which effectively exclude mass growth processes. A total of 15 different products were identified, such as molecular hydrogen (H 2 ), C2 to C7 1-alkenes [ethylene (C 2 H 4 ) to 1-heptene (C 7 H 14 )], C1–C3 radicals [methyl (CH 3 ), ethyl (C 2 H 5 ), allyl (C 3 H 5 )], small C1–C3 hydrocarbons [acetylene (C 2 H 2 ), allene (C 3 H 4 ), methylacetylene (C 3 H 4 )], as well as the reaction products [1,3-butadiene (C 4 H 6 ), 2-butene (C 4 H 8 )] attributed to higher-order processes. Electronic structure calculations carried out at the G3(CCSD,MP2)//B3LYP/6-311G(d,p) level of theory combined with RRKM/master equation of rate constants for relevant reaction steps showed that n-dodecane decomposes initially by a nonterminal C–C bond cleavage and producing a mixture of alkyl radicals from ethyl to decyl with approximately equal branching ratios. The alkyl radicals appear to be unstable under the experimental conditions and to rapidly dissociate either directly by C–C bond β-scission to produce ethylene (C 2 H 4 ) plus a smaller 1-alkyl radical with the number of carbon atoms diminished by two or via 1,5-, 1,6-, or 1,7- 1,4-, 1,9-, or 1,8-H shifts followed by C–C β-scission producing alkenes from propene to 1-nonene together with smaller 1-alkyl radicals. The stability and hence the branching ratios of higher alkenes decrease as temperature increases. The C–C β-scission continues all the way to the propyl radical (C 3 H 7 ), which dissociates to methyl (CH 3 ) plus ethylene (C 2 H 4 ). Finally, in addition, at higher temperatures, another mechanism can contribute, in which hydrogen atoms abstract hydrogen from C 12 H 26 producing various n-dodecyl radicals and these radicals then decompose by C–C bond β-scission to C3 to C11 alkenes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Clustering Acoustic Background Noise in the Stratosphere Using Machine Learning

Infrasound, characterized by low-frequency sound inaudible to humans (<20 Hz), emanates from natural and anthropogenic sources. Its efficacy for monitoring phenomena necessitates robust sensing networks. Traditional ground-based infrasound sensors have limitations due to atmospheric dynamics and noise interference. Balloon-bore sensors have emerged as an alternative, offering reduced noise and improved capabilities. This study bridges clustering algorithms with balloon borne infrasound data, a domain yet to be explored. Employing K-Means, DBSCAN, and GMM algorithms on normalized and reshaped data and only normalized data from a New Zealand-based NASA balloon flight, insights into background noise at stratospheric altitudes were revealed. Despite challenges arising from distinguishing signals amid unique background noise, this research provides vital reference material for noise analysis and calibration. Beyond infrasound event capture, the dataset enriches comprehension of background noise characteristics in the southern hemisphere.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

A Generalized Grain-Scale Model for the Non-Plasma and Plasma-Assisted Hydrogen Direct Reduction of Iron Ore

Direct Reduction of Iron ore using hydrogen (H-DRI) is a promising pathway towards efficient steelmaking and accurate predictive models are a necessity for scale-up and optimization of this technology. However, accurate models of this process remain limited because existing models oversimplify grain-scale phenomena, such as nonlinearity inside grain, self-sufficient porosity, surface reactions, and the role of plasma species. These phenomena are important for flash steelmaking and plasma-assisted H-DRI processes. To address this need, we present a phenomenological model for simulating H-DRI at the scale of a single micron-sized grain of the iron ore. We call this the Transient Reactive Grain Model (TRGM). TRGM incorporates key physical process: gas species transport, a chemical kinetics of material conversion, nanopore structural evolution and, adsorption-desorption surface kinetics at the reactive nanopore surface. The important contribution of this work is that the model provides a dependence on different reductant species, specifically hydrogen atoms versus molecules, so that role of hydrogen plasma reduction can be clarified compared to the use of pure hydrogen gas reduction. TRGM predictions agree well with experimental data for both molecular H2 reduction of Fe2O3 and plasma hydrogen reduction of Fe3O4. Results reveal species concentration gradients with a diffuse reaction zone, and enhanced hydrogen diffusion at the grain outer surface due to evolving porosity. These findings challenge common assumptions in existing models, including sharp reaction fronts, quasi-steady diffusion and kinetics, and the neglect of surface chemistry. As a generalized grain-scale model for H-DRI processes, TRGM has practical applications in flash steelmaking and in-flight reduction using both molecular and plasma hydrogen.

08 HYDROGEN↗
DOE OSTI2022

Incoherent range-based holography of far-distant objects using LIDAR

Los Alamos National Laboratory has developed an incoherent, long-range, sub-centimeter resolution (LIDAR) with which we achieve centimeter-scale reflection holography at extremely long ranges. The system consists of a pulsed laser and photon-counting receiver. This combination yields round-trip time of flight data to illuminate parts of the object of interest. The aggregation of these data for many LIDAR pulses yields a plot with a range on the X axis and reflectance on the Y axis, which we refer to as a range profile. Observing that the range profile is a projection of the reflection map of the object onto the view vector, we collect profiles from a variety of viewing angles and invert these data to form an image. We adapt imaging algorithms from the field of computer aided tomography to suit our application and present results from imaging demonstrations at a 10 km range.

Hoffmann, Mitchell P. (ORCID:0000000170551324)↗
DOE OSTI2015

Vortex flow structures and interactions for the optimum thrust efficiency of a heaving airfoil at different mean angles of attack

The thrust efficiency of a two-dimensional heaving airfoil is studied computationally for a low Reynolds number using a vortex force decomposition. The auxiliary potentials that separate the total vortex force into lift and drag (or thrust) are obtained analytically by using an elliptic airfoil. With these auxiliary potentials, the added-mass components of the lift and drag (or thrust) coefficients are also obtained analytically for any heaving motion of the airfoil and for any value of the mean angle of attack α. The contributions of the leading- and trailing-edge vortices to the thrust during their down- and up-stroke evolutions are computed quantitatively with this formulation for different dimensionless frequencies and heave amplitudes (St{sub c} and St{sub a}) and for several values of α. Very different types of flows, periodic, quasi-periodic, and chaotic described as St{sub c}, St{sub a}, and α, are varied. The optimum values of these parameters for maximum thrust efficiency are obtained and explained in terms of the interactions between the vortices and the forces exerted by them on the airfoil. As in previous numerical and experimental studies on flapping flight at low Reynolds numbers, the optimum thrust efficiency is reached for intermediate frequencies (St{sub c} slightly smaller than one) and a heave amplitude corresponding to an advance ratio close to unity. The optimal mean angle of attack found is zero. The corresponding flow is periodic, but it becomes chaotic and with smaller average thrust efficiency as |α| becomes slightly different from zero.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A Real-Time Magnetoencephalography Brain-Computer Interface Using Interactive 3D Visualization and the Hadoop Ecosystem

Ecumenically, the fastest growing segment of Big Data is human biology-related data and the annual data creation is on the order of zetabytes. The implications are global across industries, of which the treatment of brain related illnesses and trauma could see the most significant and immediate effects. The next generation of health care IT and sensory devices are acquiring and storing massive amounts of patient related data. An innovative Brain-Computer Interface (BCI) for interactive 3D visualization is presented utilizing the Hadoop Ecosystem for data analysis and storage. The BCI is an implementation of Bayesian factor analysis algorithms that can distinguish distinct thought actions using magneto encephalographic (MEG) brain signals. We have collected data on five subjects yielding 90% positive performance in MEG mid- and post-movement activity. We describe a driver that substitutes the actions of the BCI as mouse button presses for real-time use in visual simulations. This process has been added into a flight visualization demonstration. By thinking left or right, the user experiences the aircraft turning in the chosen direction. The driver components of the BCI can be compiled into any software and substitute a user’s intent for specific keyboard strikes or mouse button presses. The BCI’s data analytics OPEN ACCESS Brain. Sci. 2015, 5 420 of a subject’s MEG brainwaves and flight visualization performance are stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse.

McClay, Wilbert↗
DOE OSTI2013

Mechanisms of H{sub 2}O desorption from amorphous solid water by 157-nm irradiation: An experimental and theoretical study

The photodesorption of water molecules from amorphous solid water (ASW) by 157-nm irradiation has been examined using resonance-enhanced multiphoton ionization. The rotational temperature has been determined, by comparison with simulations, to be 425 ± 75 K. The time-of-flight spectrum of H{sub 2}O (v= 0) has been fit with a Maxwell-Boltzmann distribution with a translational temperature of 700 ± 200 K (0.12 ± 0.03 eV). H{sup +} and OH{sup +} fragment ions have been detected with non-resonant multiphoton ionization, indicating vibrationally excited parent water molecules with translational energies of 0.24 ± 0.08 eV. The cross section for water removal from ASW by 7.9-eV photons near 100 K is (6.9 ± 1.8) × 10{sup −20} cm{sup 2} for >10 L H{sub 2}O exposure. Electronic structure computations have also probed the excited states of water and the mechanisms of desorption. Calculated electron attachment and detachment densities show that exciton delocalization leads to a dipole reversal state in the first singlet excited state of a model system of hexagonal water ice. Ab Initio Molecular Dynamics simulations show possible desorption of a photo-excited water molecule from this cluster, though the non-hydrogen bonded OH bond is stretched significantly before desorption. Potential energy curves of this OH stretch in the electronic excited state show a barrier to dissociation, lending credence to the dipole reversal mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hybrid manufacturing by additive friction stir deposition, metrology, CNC machining, and microstructure analysis

Aerospace flight panels must provide high strength with low mass. For aluminum panels, it is common practice to begin with a wrought plate and remove the majority of the material to attain the desired structure, comprising a thinner plate with the desired pattern of reinforcement ribs. As an alternative, this study implements hybrid manufacturing, where aluminum is first deposited on a baseplate only at the rib locations using additive friction stir deposition (AFSD). Structured light scanning is then used to measure the printed geometry. This geometry is finally used as the stock model for computer numerical control (CNC) machining. This paper details the hybrid manufacturing process that consists of: AFSD to print the preform, structured light scanning to generate the stock model and tool path, three-axis CNC machining, and post-process measurements for part geometry and microstructure.

42 ENGINEERING↗
DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Plotting XPS Narrow Scans (and other Data) with MATLAB’s Powerful Plotting Capabilities, 2. An Introduction to Handle Graphics

The graphical representation of numerical data plays a vital role in chemistry, materials science, and every other scientific field. No matter how good your results are, poorly represented data can ultimately make your work confusing. Indeed, with an increase in the amount of data that is being gathered, e.g., by the Materials Genome Initiative, or in X-ray photoelectron spectroscopy (XPS) or time-of-flight secondary ion mass spectrometry (ToF-SIMS) depth profiles, the importance of effectively representing data has increased. Good figures also matter because many researchers will not look at more than the title, abstract, and perhaps a few key figures from a paper.

42 ENGINEERING↗