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DOE OSTI2022

Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel–Ligand Docking

The identification of promising lead compounds showing pharmacological activities toward a biological target is essential in early stage drug discovery. With the recent increase in available small-molecule databases, virtual high-throughput screening using physics-based molecular docking has emerged as an essential tool in assisting fast and cost-efficient lead discovery and optimization. However, the best scored docking poses are often suboptimal, resulting in incorrect screening and chemical property calculation. We address the pose classification problem by leveraging data-driven machine learning approaches to identify correct docking poses from AutoDock Vina and Glide screens. To enable effective classification of docking poses, we present two convolutional neural network approaches: a three-dimensional convolutional neural network (3D-CNN) and an attention-based point cloud network (PCN) trained on the PDBbind refined set. We demonstrate the effectiveness of our proposed classifiers on multiple evaluation data sets including the standard PDBbind CASF-2016 benchmark data set and various compound libraries with structurally different protein targets including an ion channel data set extracted from Protein Data Bank (PDB) and an in-house KCa3.1 inhibitor data set. Our experiments show that excluding false positive docking poses using the proposed classifiers improves virtual high-throughput screening to identify novel molecules against each target protein compared to the initial screen based on the docking scores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1975

Application of EREP, LANDSAT, and aircraft image data to environmental problems related to coal mining

Remote sensing techniques were used to study coal mining sites within the Eastern Interior Coal Basin (Indiana, Illinois, and western Kentucky), the Appalachian Coal Basin (Ohio, West Virginia, and Pennsylvania) and the anthracite coal basins of northeastern Pennsylvania. Remote sensor data evaluated during these studies were acquired by LANDSAT, Skylab and both high and low altitude aircraft. Airborne sensors included multispectral scanners, multiband cameras and standard mapping cameras loaded with panchromatic, color and color infrared films. The research conducted in these areas is a useful prerequisite to the development of an operational monitoring system that can be peridically employed to supply state and federal regulatory agencies with supportive data. Further research, however, must be undertaken to systematically examine those mining processes and features that can be monitored cost effectively using remote sensors and for determining what combination of sensors and ground sampling processes provide the optimum combination for an operational system.

Amato, R. V.↗

NASA NTRS2019

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗

DOE OSTI2016

Analysis Capability and Data Needs Identified During the Evaluation of the SILENE CAAS Benchmarks

In October 2010, a series of benchmark experiments was conducted at the Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) Valduc SILENE facility. These experiments were a joint effort between the US Department of Energy (DOE) and the French CEA to create three benchmarks for verification and validation of radiation transport codes, as well as evaluated nuclear data, used to analyze criticality accident alarm systems (CAASs). Many preliminary details of these experiments and their evaluation have been discussed in previous publications. The first benchmark evaluation was published in 2015, and the second and third evaluations will be published at the end of 2016.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1992

Evaluation of tests for vestibular function

Vestibular testing methodologies are examined in terms of their clinical value and applicability to the assessment of astronaut candidates and human responses to microgravity. Classical and novel testing approaches are examined in terms of nine functions such as otolith organs, vestibular neural processing, and ocular motor systems. The tests reviewed include the basic vestibular-function test battery, postural stability testing, visual-vestibular interaction, reactions to off-axis rotation, and vestibular evoked responses. The basic test battery is shown to be essential for astronaut and inertial-environment baseline-data evaluations, whereas the newer and research tests are only recommended in special cases. Stimulus rearrangement and motion-sickness tests are indicated for testing adaptation to inertial environments. Postural stability and visual-vestibular interaction are recommended for evaluating one's suitability for being an astronaut.

Source record↗

NASA NTRS2016

Optical Testing and Verification Methods for the James Webb Space Telescope Integrated Science Instrument Module Element

NASA's James Webb Space Telescope (JWST) is a 6.6m diameter, segmented, deployable telescope for cryogenic IR space astronomy (~40K). The JWST Observatory includes the Optical Telescope Element (OTE) and the Integrated Science Instrument Module (ISIM) that contains four science instruments (SI) and the fine guider. The SIs are mounted to a composite metering structure. The SI and guider units were integrated to the ISIM structure and optically tested at the NASA Goddard Space Flight Center as a suite using the Optical Telescope Element SIMulator (OSIM). OSIM is a full field, cryogenic JWST telescope simulator. SI performance, including alignment and wave front error, were evaluated using OSIM. We describe test and analysis methods for optical performance verification of the ISIM Element, with an emphasis on the processes used to plan and execute the test. The complexity of ISIM and OSIM drove us to develop a software tool for test planning that allows for configuration control of observations, associated scripts, and management of hardware and software limits and constraints, as well as tools for rapid data evaluation, and flexible re-planning in response to the unexpected. As examples of our test and analysis approach, we discuss how factors such as the ground test thermal environment are compensated in alignment. We describe how these innovative methods for test planning and execution and post-test analysis were instrumental in the verification program for the ISIM element, with enough information to allow the reader to consider these innovations and lessons learned in this successful effort in their future testing for other programs.

spaceborne telescopes↗

NASA NTRS1973

Recognition of beach and nearshore depositional features of Chesapeake Bay

Beach and nearshore depositional features are being mapped with the objectives of determining a quick-look analysis of littoral drift and sedimentation patterns in areas of little or no data. Evaluation of beach and nearshore features aid in the selection of small boat harbors, shoreline protective structures, and general coastal zone development. Through ERTS-1 aircraft support imagery, beach depositional features mapped are cuspate forelands, welded beach ridges, and recurved spits. The nearshore depositional features exhibit a bar and trough topography with three distinct types of sedimentary structures; longshore, transverse, and reticulated bars. Synoptic coverage of beach and nearshore depositional features by ERTS-1 data help in determining the general sedimentation patterns, growth of the beach features and stability of the bar and trough topography.

Kerhin, R. T.↗

DOE OSTI2018

Correlations of Platooning Track Test and Wind Tunnel Data

In this report, the National Renewable Energy Laboratory analyzed results from multiple, independent truck platooning projects to compare and contrast track test results with wind tunnel test results conducted by Lawrence Livermore National Laboratory (LLNL). Some highlights from the report include compiled data, and results from four independent SAE J1321 full-size track test campaigns that were compared to LLNL wind tunnel testing results. All platooning scenarios tested demonstrated significant fuel savings with good correlation relative to following distances, but there are still unanswered questions and clear opportunities for system optimization. NOx emissions showed improvements from NREL tests in 2014 to Auburn tests in 2015 with respect to J1321 platooning track testing of Peloton system. NREL evaluated data from Volpe's Naturalistic Study of Truck Following Behavior, which showed minimal impact of naturalistic background platooning. We found significant correlation between multiple track studies, wind tunnel tests, and computational fluid dynamics, but also showed that there is more to learn regarding close formation and longer-distance effects. We also identified potential areas for further research and development, including development of advanced aerodynamic designs optimized for platooning, measurement of platoon system performance in traffic conditions, impact of vehicle lateral offsets on platooning performance, and characterization of the national potential for platooning based on fleet operational characteristics.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2023

Potentially Underestimated Gas Flaring Activities—A New Approach to Detect Combustion Using Machine Learning and NASA’s Black Marble Product Suite

Monitoring changes in greenhouse gas (GHG) emission is critical for assessing climate mitigation efforts towards the Paris Agreement goal. A crucial aspect of science-based GHG monitoring is to provide objective information for quality assurance and uncertainty assessment of the reported emissions. Emission estimates from combustion events (gas flaring and biomass burning) are often calculated based on activity data (AD) from satellite observations, such as those detected from the visible infrared imaging radiometer suite (VIIRS) onboard the Suomi-NPP and NOAA-20 satellites. These estimates are often incorporated into carbon models for calculating emissions and removals. Consequently, errors and uncertainties associated with AD propagate into these models and impact emission estimates. Deriving uncertainty of AD is therefore crucial for transparency of emission estimates but remains a challenge due to the lack of evaluation data or alternate estimates. This work proposes a new approach using machine learning (ML) for combustion detection from NASA's Black Marble product suite and explores the assessment of potential uncertainties through comparison with existing detections. We jointly characterize combustion using thermal and light emission signals, with the latter improving detection of probable weaker combustion with less distinct thermal signatures. Being methodologically independent, the differences in ML-derived estimates with existing approaches can indicate the potential uncertainties in detection. The approach was applied to detect gas flares over the Eagle Ford Shale, Texas. We analyzed the spatio-temporal variations in detections and found that approximately 79.04% and 72.14% of the light emission-based detections are missed by ML-derived detections from VIIRS thermal bands and existing datasets, respectively. This improvement in combustion detection and scope for uncertainty assessment is essential for comprehensive monitoring of resulting emissions and we discuss the steps for extending this globally.

gas flaring↗

DOE OSTI2013

Use of Covariances in a Consistent Data Assimilation for Improvement of Basic Nuclear Parameters in Nuclear Reactor Applications: From Meters to Femtometers

Recognition of the key role physics plays in innovative reactor design was already made clear by E. Wigner in his warning: “It has been a bit forgotten that in all really creative thinking in reactor design, a working knowledge of nuclear reaction theory is required.” More recently, extensive sensitivity and uncertainty studies and the availability of new covariance data have allowed preliminary quantification of the impact of current nuclear data uncertainties on the design parameters of the Generation-IV systems (both fast neutron and thermal neutron systems). Similar quantifications can be done for the parameters that characterize the associated innovative fuel cycle to insure sustainability, waste minimization and drastic reduction of the proliferation risks. In parallel, there has been a growing and very significant trend to develop a new generation of reactor simulation tools that rely more and more on first principles. It is safe to say that the next generation of innovative nuclear systems will be assessed with a completely new set of tools, more science based, in sharp contrast with what has been done in the past. However, the studies mentioned above point out that the present uncertainties in nuclear data should be significantly reduced in order to fully benefit from advances in modeling and simulation. Only a parallel effort in advanced simulation and nuclear data improvement will be able to provide designers with more general and well validated calculational tools to meet new design target accuracies. One further consideration related to the development of new advanced simulation tools is that there should be a more explicit link with the more fundamental physics parameters underlying the models used to describe cross sections that would avoid the use of processed, application-oriented, data (like multigroup cross sections). Finally, current methodologies for reducing uncertainties coming from nuclear data, which rely on the use of integral experiment information to perform statistical multigroup (i.e., energy spectrum weighted) cross section data assimilation should evolve to embrace new frontiers in advanced simulation. One of the drawbacks of the classical methodologies is related to the energy group structure and the type of neutron energy spectrum that are adopted in the assimilation (adjustment). In fact, after such an adjustment is performed, neutronic designers are then tied to this energy group structure and neutron energy spectrum when carrying out further calculations. In reality, this can be quite a limiting factor in view of the complex spectral issues that are involved in most reactor physics. This work combines novel, but proven, methodologies for overcoming these limitations. In fact, this is the first attempt to build up a link between the wealth of precise integral experiments and a basic theory of nuclear reactions. Essential ingredients of such a procedure, denominated here as assimilation, are covariances for model parameters and sensitivity matrices. The latter provide direct link between reaction theory and integral experiments. The result is a consistent data assimilation performed directly on the basic nuclear physics parameters that are being used in a variety of nuclear reaction mechanisms. The resulting improvement in their performance will consequently reduce related uncertainties when employed in reactor calculations. By using integral reactor physics experiments (meter scale), information is propagated back to the nuclear physics level (femtometers) covering a range of more than 13 orders of magnitude. The assimilation procedure should result in more accurate and more reliable evaluated data files of universal validity rather than tailored to a particular application. In fact, after data assimilation is carried out, the basic nuclear data file can be processed by a dedicated code into any energy group structure that the reactor physicist deems to be useful. On the other hand, integral experiments used in the assimilation should provide additional, possibly quite strict, constraints on the parameters entering nuclear reaction modeling, as well as the reaction models themselves. This report describes three years of combined research by Brookhaben National Lab (BNL) and Idaho National Lab (INL) on establishing viable assimilation methodology. The emphasis of this paper is on the empire code calculations to prepare the priors, sensitivity matrices and covariances for the model parameters. For completeness, we also include a short summary of the assimilation results produced by INL and reported earlier in annual reports [6], [7], [8].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1985

Ultra lightweight mirror performance at 8 degrees kelvin

Earlier work funded by DARPA, evaluating the optical stability of a 0.5-m ultra-lightweight, frit-bonded, fused silica mirror, is extended from the previous 100 deg K specification down to 8 deg K. The thermal stability is excellent and comparable to that for conventional fusion and solid mirrors. The total mirror change of 0.10 lambda rms (lambda = 0.6328 microns) meets the needs of most IR systems. Thermal elastic quilting is excellent (0.008 lambda). Ames Research Center and Kodak data evaluations, done independently, are in very good agreement.

Crowe, D. A.↗

DOE OSTI2019

The Data Quality Monitoring Software for the CMS experiment at the LHC: past, present and future

The Data Quality Monitoring software is a central tool in the CMS experiment. It is used in the following key environments: (i) Online, for real-time detector monitoring; (ii) Offline, for the prompt-offline-feedback and final fine-grained data quality analysis and certification; (iii) Validation of all the reconstruction software production releases; (iv) Validation in Monte Carlo productions. Though the basic structure of the Run1 DQM system remains the same for Run2, between the Run1 and Run2 periods, the DQM system underwent substantial upgrades in many areas, not only to adapt to the surrounding infrastructure changes, but also to provide improvements to meet the growing needs of the collaboration with an emphasis on more sophisticated methods for evaluating data quality. We need to cope with the higher-energy and -luminosity proton-proton collision data, as well as the data from various special runs, such as Heavy Ion runs. In this contribution, we will describe the current DQM software, structure and workflow in the different environments. We then discuss the performance and our experiences with the DQM system in Run2. The main technical challenges which we have encountered and the solutions adopted during Run2 will also be discussed, including efficient use of memory in multithreading environments. Finally, we present the prospect of a future DQM upgrade with emphasis on functionality and long-term robustness for LHC Run3.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

What can be learned from optical two-color diffusion and thermodiffusion experiments on ternary fluid mixtures?

A number of optical techniques have been developed during the recent years for the investigation of diffusion and thermodiffusion in ternary fluid mixtures, both on ground and on-board the International Space Station. All these methods are based on the simultaneous measurement of refractive index changes at two different wavelengths. Here, we discuss and compare different techniques with the emphasis on optical beam deflection (OBD), optical digital interferometry, and thermal diffusion forced Rayleigh scattering (TDFRS). We suggest to formally split the data evaluation into a phenomenological parameterization of the measured transients and a subsequent transformation from the refractive index into the concentration space. In all experiments, the transients measured at two different detection wavelengths can be described by four amplitudes and two eigenvalues of the diffusion coefficient matrix. It turns out that these six parameters are subjected to large errors and cannot be determined reliably. Five good quantities, which can be determined with a high accuracy, are the stationary amplitudes, the initial slopes as defined in TDFRS experiments and by application of a heuristic criterion for similar curves, a certain mean diffusion coefficient. These amplitudes and slopes are directly linked to the Soret and thermodiffusion coefficients after transformation with the inverse contrast factor matrix, which is frequently ill-conditioned. Since only five out of six free parameters are reliably determined, including the single mean diffusion coefficient, the determination of the four entries of the diffusion matrix is not possible. We apply our results to new OBD measurements of the symmetric (mass fractions 0.33/0.33/0.33) ternary benchmark mixture n-dodecane/isobutylbenzene/1,2,3,4-tetrahydronaphthalene and existing literature data for the same system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

Spectral analysis for automated exploration and sample acquisition

Future space exploration missions will rely heavily on the use of complex instrument data for determining the geologic, chemical, and elemental character of planetary surfaces. One important instrument is the imaging spectrometer, which collects complete images in multiple discrete wavelengths in the visible and infrared regions of the spectrum. Extensive computational effort is required to extract information from such high-dimensional data. A hierarchical classification scheme allows multispectral data to be analyzed for purposes of mineral classification while limiting the overall computational requirements. The hierarchical classifier exploits the tunability of a new type of imaging spectrometer which is based on an acousto-optic tunable filter. This spectrometer collects a complete image in each wavelength passband without spatial scanning. It may be programmed to scan through a range of wavelengths or to collect only specific bands for data analysis. Spectral classification activities employ artificial neural networks, trained to recognize a number of mineral classes. Analysis of the trained networks has proven useful in determining which subsets of spectral bands should be employed at each step of the hierarchical classifier. The network classifiers are capable of recognizing all mineral types which were included in the training set. In addition, the major components of many mineral mixtures can also be recognized. This capability may prove useful for a system designed to evaluate data in a strange environment where details of the mineral composition are not known in advance.

Eberlein, Susan↗

NASA NTRS1983

An evaluation of Landsat data for input to a state geographic information system

The results of a study to evaluate Landsat digital data, categorized by land cover, for input to the Maryland Automated Geographic Information (MAGI) system, the state georeferenced data base, are presented. Good correspondence is found between the MAGI system and Landsat data for six of seven categories: forest, water, crop/pasture, medium-density residential, low-density residential, and transitional (disturbed land, construction). Discrepancies between the results are found for commercial/industrial/institutional areas which are due to differences in interpretative methodologies, not to deficiencies in either data source. It is concluded that Landsat data are suitable for future Maryland land cover inventories, and can also be used to augment MAGI system data.

Middleton, E. M.↗

DOE OSTI2022

First Plant Cell Atlas symposium report

The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

Towards an improved evaluation of neutron-induced fission cross sections on actinides

Mean-field calculations can now provide all the nuclear ingredients required to describe the fission path from the equilibrium deformation up to the nuclear scission point. The information obtained from microscopic mean-field models has been included in the TALYS reaction code to improve the predictions of neutron-induced fission cross sections. The nuclear inputs concern not only the details of the energy surface along the fission path, but also the coherent estimate of the nuclear level density derived within the combinatorial approach on the basis of the same single-particle properties, in particular at the fission saddle points. The predictive power of such a microscopic approach is tested on the experimental data available for the uranium isotopic chain. It is also shown that the various inputs can be tuned to reproduce, at best, experimental data in one unique coherent framework, so that in a close future it should become possible to make, on the basis of such models, accurate fission-cross-section calculations and the corresponding estimates for nuclei, energy ranges, or reaction channels for which no data exist. Such model uncertainties are usually not taken into account in data evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

FAUST - Benchmark and Validation Framework [Slides]

This presentation discusses Python packages for nuclear data applications and for benchmarking. It also discusses the goals and objectives for FAUST which include providing input and output processing for different calculation codes, allowing for exchanging results between different applications and codes, running benchmarks and processing the results, automating and simplify plot and report generation, and providing a basis for developing applications useful for nuclear data evaluators. The presentation also discusses how the packages can be used both inside and outside LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗