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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗
NASA NTRS2017

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
NASA NTRS2001

A Simple XML Producer-Consumer Protocol

There are many different projects from government, academia, and industry that provide services for delivering events in distributed environments. The problem with these event services is that they are not general enough to support all uses and they speak different protocols so that they cannot interoperate. We require such interoperability when we, for example, wish to analyze the performance of an application in a distributed environment. Such an analysis might require performance information from the application, computer systems, networks, and scientific instruments. In this work we propose and evaluate a standard XML-based protocol for the transmission of events in distributed systems. One recent trend in government and academic research is the development and deployment of computational grids. Computational grids are large-scale distributed systems that typically consist of high-performance compute, storage, and networking resources. Examples of such computational grids are the DOE Science Grid, the NASA Information Power Grid (IPG), and the NSF Partnerships for Advanced Computing Infrastructure (PACIs). The major effort to deploy these grids is in the area of developing the software services to allow users to execute applications on these large and diverse sets of resources. These services include security, execution of remote applications, managing remote data, access to information about resources and services, and so on. There are several toolkits for providing these services such as Globus, Legion, and Condor. As part of these efforts to develop computational grids, the Global Grid Forum is working to standardize the protocols and APIs used by various grid services. This standardization will allow interoperability between the client and server software of the toolkits that are providing the grid services. The goal of the Performance Working Group of the Grid Forum is to standardize protocols and representations related to the storage and distribution of performance data. These standard protocols and representations must support tasks such as profiling parallel applications, monitoring the status of computers and networks, and monitoring the performance of services provided by a computational grid. This paper describes a proposed protocol and data representation for the exchange of events in a distributed system. The protocol exchanges messages formatted in XML and it can be layered atop any low-level communication protocol such as TCP or UDP Further, we describe Java and C++ implementations of this protocol and discuss their performance. The next section will provide some further background information. Section 3 describes the main communication patterns of our protocol. Section 4 describes how we represent events and related information using XML. Section 5 describes our protocol and Section 6 discusses the performance of two implementations of the protocol. Finally, an appendix provides the XML Schema definition of our protocol and event information.

Smith, Warren↗
NASA NTRS2012

Debris Impact Detection Instrument for Crewed Modules

When micrometeoroid or debris impacts occur on a space habitat, crew members need to be quickly informed of the likely extent of damage, and be directed to the impact location for possible repairs. This is especially important because the outer walls of pressurized volumes are often not easily accessible, blocked by racks or cabinets. The goal of the Habitat Particle Impact Monitoring System (HIMS) is to develop a fully automated, end-to-end particle impact detection system for crewed space exploration modules. The HIMS uses multiple passive, thin film piezo-polymer vibration sensors to detect impacts on a surface, and computer processing of the acoustical signals to characterize the impacts. Development and demonstration of the HIMS is proceeding in concert with NASA's Habitat Demonstration Unit (HDU) Project. The HDU Project is designed to develop and test various technologies, configurations, and operational concepts for exploration habitats. This paper describes the HIMS development, initial testing, and HDU integration efforts. Initial tests of the system on the HDU were conducted at NASA s 2010 and 2011 Desert Research and Technologies Studies (Desert-RATS or D-RATS). The HDU lab module, as seen from above, has an open circular floorplan divided into eight wedge-shaped Segments. The side wall of the module -- the surface used for this technology demonstration -- is a hard fiberglass composite covered with a layer of sprayed-on foam insulation. Four sensor locations were assigned near the corners of a rectangular pattern on the wall of one segment of the HDU lab module. The flat, self-adhesive sensors were applied to the module during its initial outfitting. To study the influence of the wall s construction (thickness and materials), three sets of four sensors were installed at different layer depths: on the interior of the module s wall, on the exterior of the same wall, and on the exterior of the foam insulation. The signal produced when a vibration passes through a sensor is first sent through a pre-amplifier. The amplified signal then is sent to the data acquisition and data processing systems. The vibration data from the sensors are then processed and reduced to a form suitable for presentation to the crew.

Opiela, J.↗
DOE OSTI2025

Investigation of design principles for metal-binding and conductive protein assemblies

Throughout the lifetime of this initiative, including renewals, we focused on understanding the fundamental principles of protein-protein interface design that enable predictable and modular spatial and kinetic control of multi-component protein self-assembly in 1D, 2D, and 3D, including the interface with inorganic materials, small molecules, and metal ions. We designed individual protein components that bind specific metal ions, including REEs and transport ions across lipid membranes. We created helical 1D filaments of repeating units with programmed periodicity, pitch, and multi-component environmentally responsive self-assembling protein fibers. We showed that these filaments reversibly assemble and disassemble under specific pH conditions and created end-specific caps that independently tune the balance of attachment and detachment rates at each terminus of the filament. Using similar filaments, we succeeded in binding arrays of heme and chlorophyll molecules and assembling patterned helical coatings around carbon nanotubes in efforts to create de novo conductive nanowires. By arraying REE binding sites in a large circular tandem array with a repeat protein-based cyclic oligomer, we created a molecular scaffold for superradiance and paramagnetic quantum sensing. We created a range of one-component and two-component self-assembling 2D arrays and showed that when designed to engage cell receptors, these arrays can control cell behavior from outside the cell signal to inside the cell. We designed helical repeat proteins with variable lengths displaying charged residues in a pattern matched to the cation lattice of mica. achieved a range of ordered states with an epitaxial match to the underlying crystal lattice. We further applied the learned principles of protein-induced biomineralization to design proteins with an interface lattice matching CaCO 3 and guide the formation of specific crystal forms of CaCO 3 from solution, a significant advance toward the global need to manage carbon. In all cases of mineral lattice matching and biomineralization, we followed assembly using molecularly resolved in situ AFM imaging and extracted information about assembly pathways and energetics, applying deep learning to quantify the dynamics of protein self-organization. We developed techniques for using dynamic metal-dependent interfaces on protein nanopores for discriminatively sensing dilute REEs in solution and demonstrated the use of strong metal-binding interfaces to drive nanocage disassembly for conditional nanocompartmentalization applications. This grant supported 11 people, including Asim Bera, Evans Brackenbrough, Andrew Borst, Nikita Hanikel, Timothy Huddy, Emily Joyce, Alex Young-Seug Kang, Ryan Kibler, Joshua Morris Lubner, Harley Pyles, and Shuai Zhang. The research effort culminated in the production of published papers and theses. Electronic Thesis/Dissertation are distributed by ProQuest/UMI Dissertation Publishing and made available on an open access basis through UW Libraries ResearchWorks Service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Fabrication of Self-Cleaning, Reusable Titania Templates for Nanometer and Micrometer Scale Protein Patterning

The photocatalytic self-cleaning characteristics of titania facilitate the fabrication of reuseable templates for protein nanopatterning. In this work, titania nanostructures were fabricated over square centimeter areas by interferometric lithography (IL) and nanoimprint lithography (NIL). With the use of a Lloyd’s mirror two-beam interferometer, self-assembled monolayers of alkylphosphonates adsorbed on the native oxide of a Ti film were patterned by photocatalytic nanolithography. In regions exposed to a maximum in the interferogram, the monolayer was removed by photocatalytic oxidation. In regions exposed to an intensity minimum, the monolayer remained intact. After exposure, the sample was etched in piranha solution to yield Ti nanostructures with widths as small as 30 nm. NIL was performed by using a silicon stamp to imprint a spin-cast film of titanium dioxide resin; after calcination and reactive ion etching, TiO 2 nanopillars were formed. For both fabrication techniques, subsequent adsorption of an oligo(ethylene glycol) functionalized trichlorosilane yielded an entirely passive, protein-resistant surface. Near-UV exposure caused removal of this protein-resistant film from the titania regions by photocatalytic degradation, leaving the passivating silane film intact on the silicon dioxide regions. Proteins labeled with fluorescent dyes were adsorbed to the titanium dioxide regions, yielding nanopatterns with bright fluorescence. Subsequent near-UV irradiation of the samples removed the protein from the titanium dioxide nanostructures by photocatalytic degradation facilitating the adsorption of a different protein. The process was repeated multiple times. These simple methods appear to yield durable, reuseable samples that may be of value to laboratories that require nanostructured biological interfaces but do not have access to the infrastructure required for nanofabrication.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Dynamics and structure of turbulent premixed flames

In earlier work (Mantel & Bilger, 1994) the structure of the turbulent premixed flame was investigated using statistics based on conditional averaging with the reaction progress variable as the conditioning variable. The DNS data base of Trouve and Poinsot (1994) was used in this investigation. Attention was focused on the conditional dissipation and conditional axial velocity in the flame with a view to modeling these quantities for use in the conditional moment closure (CMC) approach to analysis of kinetics in premixed flames (Bilger, 1993). Two remarkable findings were made: there was almost no acceleration of the axial velocity in the flame front itself; and the conditional scalar dissipation remained as high, or higher, than that found in laminar premixed flames. The first finding was surprising since in laminar flames all the fluid acceleration occurs through the flame front, and this could be expected also for turbulent premixed flames at the flamelet limit. The finding gave hope of inventing a new approach to the dynamics of turbulent premixed flames through use of rapid distortion theory or an unsteady Bernoulli equation. This could lead to a new second order closure for turbulent premixed flames. The second finding was contrary to our measurements with laser diagnostics in lean hydrocarbon flames where it is found that conditional scalar dissipation drops dramatically below that for laminar flamelets when the turbulence intensity becomes high. Such behavior was not explainable with a one-step kinetic model, even at non-unity Lewis number. It could be due to depletion of H2 from the reaction zone by preferential diffusion. The capacity of the flame to generate radicals is critically dependent on the levels of H2 present (Bilger, et al., 1991). It seemed that a DNS computation with a multistep reduced mechanism would be worthwhile if a way could be found to make this feasible. Truly innovative approaches to complex problems often come only when there is the opportunity to work close at hand with the (in this case numerical) experimental data. Not only can one spot patterns and relationships in the data which could be important, but one can also get to know the limitations of the technique being used, so that when the next experiment is being designed it will address resolvable questions. A three-year grant from the Australian Research Council has enabled us to develop a small capability at the University of Sydney to work on DNS of turbulent reacting flow, and to analyze data bases generated at CTR. Collaboration between the University of Sydney and CTR is essential to this project and finding a workable modus operandum for this collaboration, given the constraints involved, has been a major objective of the past year's effort. The overall objectives of the project are: (1) to obtain a quantitative understanding of the dynamics of turbulent premixed flames at high turbulence levels with a view to developing improved second order closure models; and (2) to carry out new DNS experiments on turbulent premixed flames using a carefully chosen multistep reduced mechanism for the chemical kinetics, with a view to elucidating the laser diagnostic findings that are contrary to the findings for DNS using one-step kinetics. In this first year the objectives have been to make the existing CTR data base more accessible to coworkers at the University of Sydney, to make progress on understanding the dynamics of the flame in this existing CTR data base, and to carefully construct a suitable multistep reduced mechanism for use in a new set of DNS experiments on turbulent premixed flames.

Bilger, R. W.↗
DOE OSTI2023

A database of synthetic inelastic neutron scattering spectra from molecules and crystals

Abstract Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Quality and uptake of antenatal and postnatal care in Haiti

Background: Despite improvement, maternal mortality in Haiti remains high at 359/100,000 live births. Improving access to high quality antenatal and postnatal care has been shown to reduce maternal mortality and improve newborn outcomes. Little is known regarding the quality and uptake of antenatal and postnatal care among Haitian women. Methods: Exit interviews were conducted with all pregnant and postpartum women seeking care from large health facilities (n = 10) in the Nord and Nord-Est department and communes of St. Marc, Verrettes, and Petite Rivière in Haiti over the study period (March-April 2015; 3–4 days/facility). Standard questions related to demographics, previous pregnancies, current pregnancy, and services/satisfaction during the visit were asked. Total number of antenatal visits were abstracted from charts of recently delivered women (n = 1141). Provider knowledge assessments were completed by antenatal and postnatal care providers (n = 39). Frequencies were calculated for descriptive variables and multivariable logistic regression was used to explore predictors of receiving 5 out of 10 counseling messages among pregnant women. Results: Among 894 pregnant women seeking antenatal care, most reported receiving standard clinical service components during their visit (97% were weighed, 80% had fetal heart tones checked), however fewer reported receiving recommended counseling messages (44% counselled on danger signs, 33% on postpartum family planning). Far fewer women were seeking postnatal care (n = 63) and similar service patterns were reported. Forty-three percent of pregnant women report receiving at least 5 out of 10 counseling messages. Pregnant women on a repeat visit and women with greater educational attainment had greater odds of reporting having received 5 out of 10 counseling messages (2nd visit: adjusted odds ratio [aOR] =1.70, 95% confidence interval [CI]: 1.09–2.66; 5+ visit: aOR = 5.44, 95% CI: 2.91–10.16; elementary school certificate: aOR = 2.06, 95% CI: 1.17–3.63; finished secondary school or more aOR = 1.97, 95% CI = 1.05–3.02). Chart reviews indicate 27% of women completed a single antenatal visit and 36% completed the recommended 4 visits. Conclusions: Antenatal and postnatal care uptake in Haiti is sub-optimal. Despite frequent reports of provision of standard service components, counseling messages are low. Consistent provision of standardized counseling messages with regular provider trainings is recommended to improve quality and uptake of care in Haiti.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Oxide Semiconductor Sensors for Monitoring Advanced Energy Conversion and Manufacturing Processes at High Temperature

To optimize the operation and functionality of high temperature systems such as slagging gasifiers, coal boilers and glass/steel smelters, it is important to monitor temperature, corrosion and erosion of the refractory used in such systems. Both thermocouple and failure sensors (and arrays of these) would be useful to monitor the health of any refractory or coatings in these systems. Many of such type of sensors are installed into the systems through open access ports within the refractory; however, there are some disadvantages of this approach where corrosive/erosive gas and molten materials can penetrate and compromise the system. The current work presents the development and performance of refractory with embedded high temperature sensors such as thermocouples, thermistors, and various spallation/crack monitoring sensors, which may be used within a variety of refractory brick in different high temperature processes and applications. The objective of our work is to develop high-temperature sensors composed of electroceramic materials that are chemically stable at high temperatures (750°-1500°C) and high pressures (up to 1000 psi) that can be used in monitoring temperature, corrosion and erosion process in refractory used in high energy systems. The high-temperature sensors investigated in this work were composed of various oxide composites directly embedded into the refractory oxides. The composites used for this work were synthesized by a mixed-oxide route. Metal oxides were inserted within a matrix material composed of refractory oxides (Al2O3, ZrO2, etc.). The physical and electrical properties were specifically manipulated by altering the level of percolation of the conductive species (metal oxides) within the refractory constituent (refractory oxide). An example of one of these embedded sensors consisted of an electroceramic-based thermocouple fabricated with two separate oxide composite compositions which were patterned to produce a couple within the interior of a refractory matrix. The thermocouple successfully displayed thermoelectric voltage trend (as a function of temperature), and the voltage was 220.0 mV near 1400 °C. In addition, corrosion tests on the refractory embedded sensors were performed. To evaluate corrosion in the refractory was exposed to high-temperature glass compositions over a 90 h period. The penetration of the glass through the refractory could be monitored by both an amperometric and voltametric based sensor. With this experiment, it was demonstrated that the embedded sensor could dynamically monitor the corrosion process, and thus, provide real-time feedback on both temperature and the refractory health.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1994

Coastal zone color scanner 'system calibration': A retrospective examination

During its lifetime the Coastal Zone Color Scanner (CZCS) produced approximately 66,000 images. These have been placed in an archive of 'raw' radiance (sensor counts) in a subsampled format that is easily accessible. They have also been processed to form global fields, at reduced resolution, of normalized water-leaving radiance, phytoplankton pigments, and diffuse attenuation coefficient. Using this archive, we have tried to characterize some aspects of the 'system calibration' for the 8-year lifetime of CZCS. Specifically, we have assumed that the sensitivity of the red band decayed in a simple manner similar to the well-known long-term degradation of the shorter-wavelength bands, and we examined the sensitivity of the green and yellow bands by computing the globally averaged water-leaving radiance, over 10-day periods, for all of the imagery. The results provided evidence that in addition to the long-term degradation, short-term (2 weeks to 1 month) variations in the radiometric sensitivity of these bands started in early fall 1981 and continued for the rest of the mission. In contrast, the data suggested the absence of such variations prior to August 1981. It is reasonable to believe that the sensitivity of the blue (and probably the red) band underwent such variations as well; however our methodology cannot be used to study the other bands. Thus, after these fluctuations began, the actual values of CZCS - estimated pigment concentrations at a given location should be viewed with skepticism; however, the global patterns of derived pigment concentrations should be valid. Had an extensive set of surface measurements of water-leaving radiance, e.r., from moored buoyes or drifters, had been available during the CZCS mission, these fluctuations could have been removed from the data set, and this would have greatly increased its value. The lessons learned from CZCS that is, the requirement of good radiometric calibration and stability and the necessity of 'sea truth' stations to monitor the performance of the system (sensor plus algorithms), are being applied to the sea-viewing wide-field-of-view senso (Sea WiFS) scheduled for launch in August 1993.

Evans, Robert H.↗
DOE OSTI2023

High-throughput feedback-enabled optogenetic stimulation and spectroscopy in microwell plates

Abstract The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, there is currently a lack of instrumentation to monitor such experiments in real time, necessitating repeated transfers of the samples to stand-alone analytical instruments, thus limiting the types of experiments that could be performed. Here we address this gap with the development of the optoPlateReader (oPR), an open-source, solid-state, compact device that allows automated optogenetic stimulation and spectroscopy in each well of a 96-well plate. The oPR integrates an optoPlate illumination module with a module called the optoReader, an array of 96 photodiodes and LEDs that allows 96 parallel light measurements. The oPR was optimized for stimulation with blue light and for measurements of optical density and fluorescence. After calibration of all device components, we used the oPR to measure growth and to induce and measure fluorescent protein expression in E. coli . We further demonstrated how the optical read/write capabilities of the oPR permit computer-in-the-loop feedback control, where the current state of the sample can be used to adjust the optical stimulation parameters of the sample according to pre-defined feedback algorithms. The oPR will thus help realize an untapped potential for optogenetic experiments by enabling automated reading, writing, and feedback in microwell plates through open-source hardware that is accessible, customizable, and inexpensive.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

An On-Demand Electric Transit Case Study of New Rochelle, New York

Here, this article characterizes the performance and ridership patterns of an on-demand transit (ODT) service utilizing lightweight electric vehicles (EVs) in New Rochelle, New York. Ridership sociodemographics, travel patterns (both temporal and spatiotemporal), and energy use from the service were explored using travel and survey data from September 2019 through December 2023. The ODT service was found to be used more by women (nearly 60%) and younger demographics (>65% under the age of 42), with peak use in the middle of the day and a grocery store as a top origin and destination. The service was utilized primarily for short trips (86% under 2 mi), with approximately one-third of riders using the ODT service to connect to a train or bus. The costs associated with fueling/charging were compared for different types of fleet vehicles, and the small, right-sized EVs were found to have annual charging costs that were roughly half of the refueling costs for conventional hybrid vans, and 24 times lower than a fleet of diesel buses. Evaluating the vehicle fleet and mapping current socio-spatial travel demand can inform system performance, guide service area development, and support future planning such as expansion to nearby communities and transit hubs. The findings in this case study suggest that on-demand electric transit may be a significant and growing space for advancing highly valued public mobility services. Public transport interventions that consider right-sized, electric, on-demand vehicles can help improve mobility access and reduce energy use and refueling costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Erosion-Corrosion Detection in Carbon Steel Pipe Loops using SRNLs Thickness and Mass Loss Measurement Coupons - 20464

Structural health of waste transfer infrastructure is of utmost importance to DOE and communities surrounding their active sites. A Fitness-for-Service (FFS) program for the Waste Transfer System has been implemented by the US Department of Energy (DOE) for the purposes of evaluating and quantifying the degradation of critical components. Currently, the method of approach is to section and evaluate pipelines that have been removed at end service. In order to augment data collection methods applied to making lifespan estimates of waste transfer system components, Florida International University (FIU) has been investigating new-technology based strategies for quantifying the rate of degradation. Present research considers the option of a coupon system installed on a section of pipe at points of interest that will provide easy access to high resolution measurements of erosion/corrosion rates during operation. Researchers at Savannah River National Laboratory (SRNL) have developed this novel solution for in situ erosion and corrosion measurements in many applicable locations such as tanks, pipes, ducts, and injection points. The coupons are approximately 12.7 mm (1/2 inch) in diameter and 25.4 mm (1 inch) in length and can be placed in the pipe sections using Swagelok compression fittings. The coupon design allows for monitoring of the total degradation resulting from corrosion and erosion. High-resolution Ultrasonic Thickness (UT) testing allows in-situ monitoring of both degradation mechanisms. When removed from the system mass loss resulting from corrosion and erosion may also be evaluated. Experimental testing at FIU implemented the SRNL coupon system in a 6.10 meter (20 foot) pipe loop system comprised of 50.8 mm (2 inch) and 76.2 mm (3 inch) pipe sections in order to replicate expected use cases at the sites. Operational conditions were emulated by pumping abrasive materials through the pipeline at full capacity and collecting measurements from the SRNL coupons. Initial testing was conducted by circulating water followed by a mixture of sand and water for uniform wear rates. Thickness changes and mass loss were measured, and the surface exposed to the process fluid was observed for visual evidence of characteristic wear patterns resulting from an erosive environment. The test matrix consisted of several hours of operation and using fine, medium and coarse grain sands. Test results were analyzed to check for all three parameters (mass loss/gain, thickness change and surface patters) which could provide estimates of the remaining useful life of the pipe sections. Thus, the research presents the findings of this evaluation of the SRNL coupons as a means for conducting high accuracy, cost effective in-situ analysis of pipeline and waste transfer systems for erosion and corrosion susceptibility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Enabling Co-Design of Multi-Layer Exascale Storage Architectures

Growing demands for computing power in applications such as energy production, climate analysis, computational chemistry, and bioinformatics have propelled computing systems toward the exascale: systems with 10 18 floating-point operations per second. These systems, to be designed and constructed over the next decade, will create unprecedented challenges in component counts, power consumption, resource limitations, and system complexity. Data storage and access are an increasingly important and complex component in extreme-scale computing systems, and significant design work is needed to develop successful storage hardware and software architectures at exascale. Co-design of these systems will be necessary to find the best possible design points for exascale systems. The goal of this work has been to enable the exploration and co-design of exascale storage systems by providing a detailed, accurate, and highly parallel simulation of exascale storage and the surrounding environment. Specifically, this simulation has (1) portrayed realistic application checkpointing and analysis workloads, (2) captured the complexity, scale, and multilayer nature of exascale storage hardware and software, and (3) executed in a timeframe that enables “what if'” exploration of design concepts. We developed models of the major hardware and software components in an exascale storage system, as well as the application I/O workloads that drive them. We used our simulation system to investigate critical questions in reliability and concurrency at exascale, helping guide the design of future exascale hardware and software architectures. Additionally, we provided this system to interested vendors and researchers so that others can explore the design space. We validated the capabilities of our simulation environment by configuring the simulation to represent the Argonne Leadership Computing Facility Blue Gene/Q system and comparing simulation results for application I/O patterns to the results of executions of these I/O kernels on the actual system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Substrate Engineered Interconnected Graphene Electrodes with Ultrahigh Energy and Power Densities for Energy Storage Applications

Supercapacitors combine the advantages of electrochemical storage technologies like high energy density batteries and high power density capacitors. At 5-10 W h Kg -1 , the energy densities of current supercapacitors are still significantly lower than energy densities of lead acid (20-35 W h Kg -1 ), Ni-metal hydride (40-100 W h Kg -1 ) and Li-ion (120-170 W h Kg -1 ) batteries. Recently, graphene based supercapacitors have shown energy density of 40-80 W h kg -1 . However, their performance is mainly limited due to the reversible agglomeration and restacking of individual graphene layers caused by π-π interactions. The restacking of graphene layers leads to significant decrease of ion-accessible surface area and the low capacitance of graphene based supercapacitors. Here, we introduce a microstructure substrate based method to produce fully delaminated and stable interconnected graphene structure using flash reduction of GO in a few seconds. With this structure, here we achieve the highest amount of volumetric capacitance obtained so far by any type of pure carbon based material. The affordable and scalable production method is capable of producing electrodes with energy density of 0.37 Wh cm -3 and power density of 416.6 W cm -3 . This electrode maintained more than 91 % of its initial capacitance after 5000 cycles. Moreover, combining with ionic liquid, this solvent free graphene electrode material is highly promising for on-chip electronics, micro supercapacitors as well as high power applications.

25 ENERGY STORAGE↗