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DOE OSTI2022

Measurement of isosteric heat of gas adsorption and Brunauer–Emmett–Teller (BET) surface area using a quartz crystal microbalance

The study of gas adsorption on a solid surface evaluates the affinity between sorbate gas and sorbent substrate and factors that contribute to this. This report presents a test platform for adsorption experiments of various gases on various solid surfaces. Controlled environmental conditions enable investigations in materials surface science and increase the consistency among adsorption data. The system utilizes a quartz crystal microbalance to perform gravimetric analysis of deposition and adsorption, enabling investigation of the interaction of gaseous molecules with solid surfaces. In this study, a quartz crystal microbalance as gas adsorption detector was integrated with an environmental chamber to create a versatile tool for gas adsorption experiments on thin films. Experimental operation of this apparatus was demonstrated via acquisition of the adsorption isotherms of cyclohexane vapor on a gold surface at 55 and 70 °C. The result indicated International Union of Pure and Applied Chemistry Type II adsorption. Consequentially, application of the Brunauer–Emmett–Teller model to the isotherm data subject to predefined criteria for linear region selection yielded a surface area of the sorbent of 0.53 cm2 at 55 °C. From the monolayer region of the isotherms, the isosteric heat of adsorption of the cyclohexane vapor on gold was calculated to be 37 kJ mol-1.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

SU-E-T-553: Monte Carlo Calculation of Proton Bragg Peak Displacements in the Presence of Al2O3:C Dosimeters

Purpose: The application of optically stimulated luminescence dosimeters (OSLDs) may be extended to clinical investigations verifying irradiated doses in small animal models. In proton beams, the accurate positioning of the Bragg peak is essential for tumor targeting. The purpose of this study was to estimate the displacement of a pristine Bragg peak when an Al2O3:C nanodot (Landauer, Inc.) is placed on the surface of a water phantom and to evaluate corresponding changes in dose. Methods: Clinical proton pencil beam simulations were carried out with using TOPAS, a Monte Carlo platform layered on top of GEANT4. Point-shaped beams with no energy spread were modeled for energies 100MV, 150MV, 200MV, and 250MV. Dose scoring for 100,000 particle histories was conducted within a water phantom (20cm × 20cm irradiated area, 40cm depth) with its surface placed 214.5cm away from the source. The modeled nanodot had a 4mm radius and 0.2mm thickness. Results: A comparative analysis of Monte Carlo depth dose profiles modeled for these proton pencil beams did not demonstrate an energy dependent in the Bragg peak shift. The shifts in Bragg Peak depth for water phantoms modeled with a nanodot on the phantom surface ranged between 2.7 to 3.2 mm. In all cases, the Bragg Peaks were shifted closer to the irradiation source. The peak dose in phantoms with an OSLD remained unchanged with percent dose differences less than 0.55% when compared to phantom doses without the nanodot. Conclusion: Monte Carlo calculations show that the presence of OSLD nanodots in proton beam therapy will not change the position of a pristine Bragg Peak by more than 3 mm. Although the 3.0 mm shift will not have a detrimental effect in patients receiving proton therapy, this effect may not be negligible in dose verification measurements for mouse models at lower proton beam energies.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

TU-F-CAMPUS-T-02: Risk Assessment of Scattered Neutrons for a Fetus From Proton Therapy of a Brain Tumor During Pregnancy

Purpose: To determine the scattered neutron dose and the resulting risk for a fetus from proton therapy for brain tumors during pregnancy. Methods: Using the Monte Carlo platform TOPAS, the ICRP reference parameters based anthropomorphic pregnancy phantoms for three stages (3-, 6-, 9-month) were applied to evaluate the scattered neutron dose and dose equivalent. To calculate the dose equivalent, organ specific linear energy transfer (LET) based quality factor was used. Treatment plans from both passive scattering (PS) and pencil beam scanning (PBS) methods were considered in this study. Results: For pencil beam scanning, the neutron dose equivalent in the soft tissue of the fetus increases from 1.53x10−{sup 3} to 2.84x10−{sup 3} mSv per treatment Gy with increasing stage of gestation. This is due to scattered neutrons from the patient as the main contaminant source in PBS and a decrease in distance between the soft tissue of the fetus and GTV with increasing stage of gestation. For passive scattering, neutron dose equivalent to the soft tissue of the fetus shows a decrease from 0.17 to 0.13 mSv per treatment Gy in different stages, while the dose to the brain shows little difference around 0.18 mSv per treatment Gy because scattered neutrons from the treatment head contribute predominantly in passive scattering. Conclusion: The results show that the neutron dose to the fetus assuming a prescribed dose of 52.2 Gy is negligible for PBS, and is comparable to the scattered dose (0–10 mSv) from a head and neck CT scan for PS. It can be concluded that the dose to fetus is far lower than the thresholds of malformation, SMR and lethal death. The excess relative risk of childhood cancer induction would be increased by 0.48 and 0.103 using the Oxford Survey of Childhood Cancers and Japanese atomic model, respectively. Changran Geng is supported by the Chinese Scholarship Council (CSC) and the National Natural Science Foundation of China (Grant No. 11475087)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Managing code transformations for better performance portability

Code optimization is an intricate task that is getting more complex as computing systems evolve. Managing the program optimization process, including the implementation and evaluation of code variants, is tedious, inefficient, and errors are likely to be introduced in the process. Moreover, because each platform typically requires a different sequence of transformations to fully harness its computing power, the optimization process complexity grows as new platforms are adopted. To address these issues, systems and frameworks have been proposed to automate the code optimization process. They, however, have not been widely adopted and are primarily used by experts with deep knowledge about underlying architecture and compiler intricacies. This article describes the requirements that we believe necessary for making automatic performance tuning more broadly used, especially in complex, long-lived high-performance computing applications. Besides discussing limitations of current systems and strategies to overcome these, we describe the design of a system that is able to semi-automatically generate efficient platform-specific code. In the proposed system, the code optimization is programmer-guided, separately from application code, on an external file in what we call optimization programming. The language to program the optimization process is able to represent complex collections of transformations and, as a result, generate efficient platform-specific code. A database manages different optimized versions of code regions, providing a pragmatic approach to performance portability, and the framework itself has separate components, allowing the optimized code to be used on systems without installing all of the modules required for the code generation. We present experiments on two different platforms to illustrate the generation of efficient platform-specific code that performs comparable to hand-optimized, vendor-provided code.

Computer Science↗

DOE OSTI2023

Renewable Energy Potential Model: Geothermal Supply Curves

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. The included paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results provided here should be considered with care due to the high uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for three scenarios: two hydrothermal (3.5km depth, USGS heat flow & SMU temperatures respectively) and one EGS (4.5km depth, SMU temperatures). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Reveal-CoV Diaagnostic Platform (Final Report)

LLNL designed and built a rapid, RT-LAMP-based molecular diagnostics platform as a potential tool to quickly diagnose COVID-19 in under one hour. This point-of-care testing approach involves an initial high temperature swab sample inactivation step followed by amplification of viral RNA using up to 5 control and pathogen-specific assays. Results are determined based on a discreet reaction color change from red to yellow but can also be determined using fluorescence detection. Testing of this prototype platform was conducted with synthetic viral RNA and dried, stabilized reagents. Buffer systems, swab selection, and assay stabilization formulations were evaluated for performance. Limits of detection were determined using RNA; however, testing was not performed with viable SARS-CoV-2 virus or clinical samples.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Cloud-Based Demonstration of the Eastern Interconnection Situational Awareness Monitoring System (ESAMS)

This report describes a cloud-based implementation and field demonstration of the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS). ESAMS was developed to support the detection and source localization of forced oscillations using synchrophasor measurements from tie-lines connecting areas served by different reliability coordinators (RCs), so that RCs could better coordinate their response to wide-area events. A previous effort had identified deployment barriers associated with hosting shared situational awareness tools at a single RC. To address these barriers, ESAMS was migrated to Amazon Web Services and evaluated in a six-month field demonstration. ISO New England (ISO-NE) and PJM streamed data to the platform using AWS Direct Connect and a site-to-site VPN, respectively. The resulting multi-utility measurement footprint enabled regional source localization across major portions of the U.S. Eastern Interconnection and supported routine identification of oscillation events. During the final three months of the trial, 24 events above 2 MW/MVAR were detected. The largest detected oscillation approached a 25 MW peak-to-peak amplitude, and the longest persisted intermittently for more than 11 hours. The demonstration also assessed operational considerations—including data transfer volumes, end-to-end latency, and cloud computing costs—and found that network and compute requirements were modest relative to typical cloud capabilities while providing performance comparable to prior on-premises deployments. Overall, the results indicate that cloud hosting can provide a practical path to shared interconnection-wide oscillation monitoring. The cloud ESAMS demonstration establishes a foundation for broader utility participation and for building future wide-area analytics that leverage measurements across organizational boundaries.

Follum, James D.↗

DOE OSTI2025

A Review of Offshore Methane Quantification Methodologies

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emissions from production platforms measured using downwind dispersion methods were 32 kg h−1 from 188 platforms; 118 kg h−1 from 104 platforms using mass balance methods; 284 kg h−1 from 151 platforms using aircraft remote sensing; and 19,088 kg h−1 from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depths moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantification methodologies.

Riddick, Stuart N. (ORCID:0000000316841843)↗

DOE OSTI2025

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.

Stanford, McKenna Wallace [Columbia Univ., New Yor↗

NASA NTRS1972

Remote sensing techniques in evaluating earth resources - A study of potential uses of remote sensing for Southeastern U.S.

Review of the results of a recent study of the potential uses of remote sensing in the Southeastern United States in evaluating resources. The use of remote sensing in the evaluation and management of earth resources is discussed, as well as the use of satellites and aircraft as remote sensing platforms. The specific needs to be satisfied by remote sensing in the Southeast region are considered, dwelling, in particular, on the use of remote sensing for land use mapping, forest inventory, water pollution monitoring, strip mine reclamation, air pollution, demonstration farms and forests, and reservoir ecology. A brief description is given of multispectral photographic and scanner data analysis techniques, to illustrate that regional information needs can be met with existing technological capability.

Shahrokhi, F.↗

NASA NTRS1991

Task decomposition for a multilimbed robot to work in reachable but unorientable space

Robot manipulators installed on legged mobile platforms are suggested for enlarging robot workspace. To plan the motion of such a system, the arm-platform motion coordination problem is raised, and a task decomposition is proposed to solve the problem. A given task described by the destination position and orientation of the end effector is decomposed into subtasks for arm manipulation and for platform configuration, respectively. The former is defined as the end-effector position and orientation with respect to the platform, and the latter as the platform position and orientation in the base coordinates. Three approaches are proposed for the task decomposition. The approaches are also evaluated in terms of the displacements, from which an optimal approach can be selected.

Su, Chau↗

NASA NTRS1990

Advances in dynamics and control of flexible spacecraft and space-based manipulations; Proceedings of the Symposium, ASME Winter Annual Meeting, Dallas, TX, Nov. 25-30, 1990

Consideration is given to control formulations for vibration suppression of an active structure in slewing motions, the use if distributed sensing in control of large flexible spacecraft, an improved shooting method for solving minimum-time maneuver problems, and nonlinear slew maneuver dynamics of large flexible spacecrafts. Attention is also given to initial experiments in trusterless locomotion control of a free-flying robot, dynamic analysis to evaluate viscoelastic passive damping augmentation for the Space Shuttle Remote Manipulator System, initial experiments in cooperative manipulation from a moving platform, and intelligent pipelined control architecture for remote robotic applications.

Joshi, Suresh M.↗

NASA NTRS2018

A Novel 3D DRAM Memory Cube Architecture for Space Applications

The first mainstream products in 3D IC design are memory devices where multiple memory tiers are horizontally integrated to offer manifold improvements compared with their 2D counterparts. Unfortunately, none of these existing 3D memory cubes are ready for harsh space environments. This paper presents a new memory cube architecture for space, based on vertical integration of Commercial Off-The-Shelf (COTS), 3D stacked, DRAM memory devices with a custom Radiation-Hardened-By-Design (RHBD) controller offering high memory capacity, robust reliability and low latency.Validation and evaluation of the ASIC controller will be conducted prior to tape-out on a custom FPGA-based emulator platform integrating the 3D-stack.

Yang-Scharlotta, Jean↗

NASA NTRSDate not supplied

Microstructural Characterization of Laser Powder Bed Fusion (L-PBF) Additively Manufactured Inconel 718 for Aerospace Application

Alloy 718 (Inconel 718) is used for aerospace applications because of its excellent corrosion resistance and mechanical properties. This alloy is particularly applicable in manufacturing components subjected to high temperatures in rocket engines, aero-engines, and gas turbines. Properties for this alloy when processing on systems from similar and different Laser Powder Bed Fusion (L-PBF) machines provide subtle differences due to process parameters, feedstock, and machine configurations. A series of sixteen L-PBF AM Inconel 718 geometric feature build plates have been evaluated for microstructure using optical microscopy. This study presents the details of the microstructure analysis concerning geometry and different machine platforms. Microstructural investigations of these samples included average grain width measurement for all the X-Y and Y-Z build layers and are accompanied by process parameters and powder characterization. The present work concludes with a discussion on the importance of captured differences among builds to understand the practical limitations among AM platforms.

Additive Manufacturing↗

NASA NTRSDate not supplied

Supporting Space Weather Modelling at the Community Coordinated Modeling Center (CCMC)

Space weather models are essential to our ability to understand and predict space weather events. Nonetheless, some of the most cutting-edge models may struggle to move past the initial research stage, remaining unknown and inaccessible to a wider research audience, thereby hindering validation, intercomparison and adoption of the models. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) closes this gap by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a growing archive of model run results. In this presentation, we will discuss current and planned capabilities in some of the model services at CCMC, including Runs-on-Request, Instant Runs, and Real-Time Continuous Runs. We will also review new models added to the extensive collection of space weather models hosted at CCMC. Finally, we will talk about our efforts at streamlining model delivery to CCMC, including support for containerized models and establishment of an open collaborative environment based on Amazon Web Services (AWS).

space weather↗

NASA NTRSDate not supplied

Enabling Collaborative Space Weather Research at the Community Coordinated Modeling Center (CCMC)

Space weather models have been actively developed by the international research community, covering extensive spatial and physical domains. Still, many of the ground-breaking models remain a granular effort, insulated from a wider research audience, particularly that in different domains, and possible end users. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) seeks to remove such barriers to collaboration and coordination by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a continuously updated archive of model run results. Moreover, the multi-disciplinary science support team at CCMC facilitates and enables collaboration across domains. In our presentation, we will discuss the space weather model services at CCMC, including Runs-on-Request, Real-Time Continuous Runs, and Instant Runs. We will also review new and updated models added to the extensive collection of space weather models hosted at CCMC. We will focus on trends in model, service, and science support utilization at CCMC as a proxy to the most pressing needs of the collaborative modeling community.

space weather↗

DOE OSTI2023

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗

DOE OSTI2024

A Bayesian Learning Approach to Wireless Outdoor Heatmap Construction using Deep Gaussian Process

We present a novel Bayesian learning approach to outdoor radio heatmap construction utilizing deep Gaussian process (GP). The proposed approach employs a two-layer hierarchy which consists of two cascaded Gaussian processes that are capable of modeling more complex input-output relations than standard single-layer Gaussian processes. Since deriving the exact model likelihood is challenging, a lower bound is optimized instead so that gradient descent-based methods can be performed to find out the optimal model parameters. Typically, inducing points are used in GPs to facilitate low-rank approximation of covariance (kernel) matrices for computation speedup. However, the inaccuracy induced by inducing points can accumulate when stacking multiple layers of GP which may hinder the performance of deep GP. Moreover, since inducing points need to be learned, having them at all layers of deep GP also incurs computational burden. To overcome the above challenges, in contrast to the canonical deep GP model, we use a modified architecture where a full standard GP resides in the first layer and inducing points are only introduced for the second layer. This modified architecture strikes a balance between model accuracy and training complexity. In the proposed model, the noise parameter of the first GP layer is also eliminated to improve the training efficiency as the noise parameter at the output of the second layer suffices to model the uncertainty in the output. The proposed approach is evaluated on real-world datasets, in the form of location-Received Signal Strength (RSS) pairs, collected from the Platform for Open Wireless Data-driven Experimental Research (POWDER) located at the campus of the University of Utah. Experiment results show that the proposed approach can achieve smaller prediction errors on various training and testing data configurations than DNN-based and GP-based methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗