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At least 973 records · Page 54

Field deployable pushbroom hyperspectral imaging polarimeter

Hyperspectral imaging polarimetry enables both the spectrum and its spectrally-resolved state of polarization to be measured. This information is important to identify material properties for various applications in remote sensing and agricultural monitoring. In this paper, we describe the design and performance of a ruggedized, field deployable Hyperspectral Imaging Polarimeter (HIP), designed for wavelengths spanning the visible to near infrared (450-800 nm). An entrance slit was used to sample the scene in a pushbroom scanning mode across a 30 degree vertical by 110 degree horizontal field of view. Furthermore, athermalized achromatic retarders were implemented in a channel spectrum generator to measure the linear Stokes parameters. The mechanical and optical layout of the system and its peripherals are provided, in addition to the results of the sensor's spectral and polarimetric calibration. Finally, field measurements are also provided and an error analysis conducted. With its present calibration, the sensor has an absolute polarimetric error of 2.5% RIVIS and a relative spectral error of 2.3% RMS.

47 OTHER INSTRUMENTATION↗

Illinois Express Quantum Network (IEQNET): metropolitan-scale experimental quantum networking over deployed optical fiber

The Illinois Express Quantum Network (IEQNET) is a program to realize metro-scale quantum networking over deployed optical fiber using currently available technology. IEQNET consists of multiple sites that are geographically dispersed in the Chicago metropolitan area. Each site has one or more quantum nodes (Qnodes) representing the communication parties in a quantum network. Q-nodes generate or measure quantum signals such as entangled photons and communicate the results via standard, classical, means. The entangled photons in IEQNET nodes are generated at multiple wavelengths, and are selectively distributed to the desired users via optical switches. Here we describe the network architecture of IEQNET, including the Internet-inspired layered hierarchy that leverages software-defined-networking (SDN) technology to perform traditional wavelength routing and assignment between the Q-nodes. Specifically, SDN decouples the control and data planes, with the control plane being entirely classical. Issues associated with synchronization, calibration, network monitoring, and scheduling will be discussed. An important goal of IEQNET is demonstrating the extent to which the control plane can coexist with the data plane using the same fiber lines. This goal is furthered by the use of tunable narrow-band optical filtering at the receivers and, at least in some cases, a wide wavelength separation between the quantum and classical channels. We envision IEQNET to aid in developing robust and practical quantum networks by demonstrating metro-scale quantum communication tasks such as entanglement distribution and quantum-state teleportation.

Chung, Joaquin↗

ReEDS™ (Regional Energy Deployment System) [SWR-20-36 and SWR-09-14]

The Regional Energy Deployment System (ReEDS™) is a free, open-access tool that empowers users to explore least-cost pathways for large-scale power sector transformation. NREL’s flagship energy capacity planning model for the North American electricity system allows users to examine the interactions between policy, technology, economics, and the environment when integrating renewables onto the grid from now through 2050.

Short, Walter↗

Urban Deployment Model (UDM) v1.0

The software, called the Urban Deployment Model (UDM), is an integrated set of tools for the simulation and analysis of static and mobile radiation detection systems in complex urban environments. The UDM includes a graphical user interface through which the workflow associated with setting up and executing a simulation may be established. The modular toolsets combine aspects of radiation transport, navigation, graph theory, optimization, and visualization to allow the complete end-to-end simulation of large scale, highly-distributed sensor networks.

Abgrall, Nicolas↗

Medium and Heavy-Duty Electric Vehicle Infrastructure - Load Operations and Deployment (HEVI-LOAD) v1.0

In order to support the California state goals to reduce the carbon and pollution emissions (AB2127), The goal of this project (HEVI-Pro) is to project the charging infrastructure needs by future medium- and heavy- duty electric vehicles, and assess optimal deployment the infrastructure in California and provide grid impacts analysis. The MHDV projections will also consider transportation system and electric system interaction with light duty vehicles. The project consists of 2 approaches in general: top-down approach that takes aggregated MHDV adoptions as the inputs and provide the county-level projections of charging load profile and infrastructure need, and the bottom-up approach that that incorporates more granular (temporal, spatial and duty-cycle-specific) behaviors of a variety of MHDVs into activity simulations/optimizations for further analysis.

Wang, Bin↗

Python Urban Deployment Model (PyUDM) v1.0.0

The Python Urban Deployment Model (PyUDM) is a simulation tool used to investigate networks of static radiation detectors in urban environments. PyUDM simulates traffic, stationary NaI gamma-ray detectors, and moving radioactive sources on simulated vehicles. The analyzed output of the simulations contain valuable insights into the performance of different configurations of urban radiological detector configurations such as their ability to detect sources moving through the environment. To accurately simulate radioactive material moving through urban environments, PyUDM combines Monte Carlo simulation tools, publicly available map and traffic data, and measured gamma-ray spectra from urban environments.

Rofors, Emil↗

ADOPT (Automotive Deployment Options Projection Tool) [SWR-17-13]

NREL's Automotive Deployment Options Projection Tool (ADOPT) is a vehicle consumer choice and stock model. ADOPT estimates the impact of vehicle technology improvements on future U.S. vehicle sales, energy use, and emissions. It provides consumer choice estimates based on questions such as: -How much impact do lower battery prices have on electric vehicle sales? -How quickly would the market adopt a co-optimized engine/fuel combination that achieves a 10% efficiency improvement? -How do fuel prices impact the electric vehicle/plug-in hybrid electric vehicle sales mix? -How does vehicle lightweighting impact powertrain sales? Approach- Starting with the majority of existing vehicle makes, models, and trims to fully represent the market, ADOPT applies numerous inputs-technology improvements, fuel prices, and vehicle purchase incentives-over time. ADOPT then estimates sales based on the variable weighted value of key attributes, including vehicle price, fuel cost per mile, acceleration, size, and range. ADOPT also considers consumer income level as well as regulations and standards that influence sales and average fuel economy. ADOPT incorporates NREL's FASTSim™ (Future Automotive Systems Technology Simulator, https://www.nrel.gov/transportation/fastsim.html) to apply specified technology improvements to vehicles over time, and to create new model options by combining high-selling powertrains and high-selling vehicle platforms. NREL has extensively validated the tool and its consumer preference trade-offs to ensure confidence in the results.

Brooker, Aaron↗

Code Description for "Brief Communication: Monitoring snow depth using small, cheap, and easy-to-deploy ground surface temperature sensors"

Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.

Bachand, Claire↗

Performance of optical sensors for cloud measurements deployed by the ARM Aerial Facility during ACE-ENA

During the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA), a variety of in situ optical sensors using shadow imaging, scattering and holography were deployed by the Atmospheric Radiation Measurement (ARM) Aerial Facility to determine cloud properties. Taking advantage of the wide, overlapping range of instrumentation, we compare in situ cloud data from several different measurement methods for droplets up to 100 µm. Further, data processing was tailored to the encountered conditions, leading to good agreement. Improvements include noise reduction for holography and better out-of-focus correction for shadow imaging. Comparison between direct liquid water content measurements and optical sensors showed better agreement at higher droplet number concentrations (>120/cm 3 ).

47 OTHER INSTRUMENTATION↗

Characterizing thermal-induced temporal drift in deployed quantum fiber networks

We study temperature-induced fiber-delay drifts affecting entanglement fidelity in deployed quantum systems. Using field data and simulations, we model timing uncertainties and evaluate their impact on coincidence detection, revealing critical challenges for robust quantum networks.

Alshowkan, Muneer [ORNL] (ORCID:0000000264293450)↗

Ancilla-assisted process tomography of a deployed fiber link

We perform ancilla-assisted process tomography over a deployed 1.6 km fiber-optic link using Bayesian inference, confirming a stable, high-fidelity polarization channel. Overall, our approach should offer value for in situ analyses of entanglement networks.

Rahman, Arefur [Arizona State University]↗

Entanglement-based quantum digital signatures over a deployed campus network

The quantum digital signature protocol offers a replacement for most aspects of public-key digital signatures ubiquitous in today’s digital world. A major advantage of a quantum-digital-signatures protocol is that it can have information-theoretic security, whereas public-key cryptography cannot. Here we demonstrate and characterize hardware to implement entanglement-based quantum digital signatures over our campus network. Over 25 hours, we collect measurements on our campus network, where we measure sufficiently low quantum bit error rates (<5% in most cases) which in principle enable quantum digital signatures at over 50 km as shown through rigorous simulation accompanied by a noise model developed specifically for our implementation. These results show quantum digital signatures can be successfully employed over deployed fiber. Moreover, our reported method provides great flexibility in the number of users, but with reduced entanglement rate per user. Finally, while the current implementation of our entanglement-based approach has a low signature rate, feasible upgrades would significantly increase the signature rate.

97 MATHEMATICS AND COMPUTING↗

Contact-dependent growth inhibition (CDI) systems deploy a large family of polymorphic ionophoric toxins for inter-bacterial competition

Contact-dependent growth inhibition (CDI) is a widespread form of inter-bacterial competition mediated by CdiA effector proteins. CdiA is presented on the inhibitor cell surface and delivers its toxic C-terminal region (CdiA-CT) into neighboring bacteria upon contact. Inhibitor cells also produce CdiI immunity proteins, which neutralize CdiA-CT toxins to prevent auto-inhibition. Here, we describe a diverse group of CDI ionophore toxins that dissipate the transmembrane potential in target bacteria. These CdiA-CT toxins are composed of two distinct domains based on AlphaFold2 modeling. The C-terminal ionophore domains are all predicted to form five-helix bundles capable of spanning the cell membrane. The N-terminal "entry" domains are variable in structure and appear to hijack different integral membrane proteins to promote toxin assembly into the lipid bilayer. The CDI ionophores deployed by E. coli isolates partition into six major groups based on their entry domain structures. Comparative sequence analyses led to the identification of receptor proteins for ionophore toxins from groups 1 & 3 (AcrB), group 2 (SecY) and groups 4 (YciB). Using forward genetic approaches, we identify novel receptors for the group 5 and 6 ionophores. Group 5 exploits homologous putrescine import proteins encoded by puuP and plaP, and group 6 toxins recognize di/tripeptide transporters encoded by paralogous dtpA and dtpB genes. Finally, we find that the ionophore domains exhibit significant intra-group sequence variation, particularly at positions that are predicted to interact with CdiI. Accordingly, the corresponding immunity proteins are also highly polymorphic, typically sharing only ~30% sequence identity with members of the same group. Competition experiments confirm that the immunity proteins are specific for their cognate ionophores and provide no protection against other toxins from the same group. The specificity of this protein interaction network provides a mechanism for self/nonself discrimination between E. coli isolates.

59 BASIC BIOLOGICAL SCIENCES↗

DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period

This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady geothermal field during PoroTomo deployment (2016-Mar-14 to 2016-Mar-26). There is one file corresponding to each day written in *.mat format for use with Matlab. The format for the binary Matlab .mat files are defined at: https://www.mathworks.com/help/pdf_doc/matlab/matfile_format.pdf. One such file includes the following variables: 'flist': list of raw DASH files used in the summation 'time_tag_mdt': sample time tag in datetime format with hours given in 24-hr format (yyyy/MM/dd HH:mm:ss.SSSSSSS) 'time_tag_uts': sample time tag in Unix time 'strain_rate_summed_over30s_in_radians_per_second': slow strain rates summed over 30 second intervals in units rad/s 'sample_standard_deviation_in_radians_per_second': corresponding sample standard deviation of slow strain rates in units rad/s The PoroTomo final technical report, raw DASH data, and software repository are also available through the links below.

15 GEOTHERMAL ENERGY↗

ALFA MHK Biological Monitoring Stationary Deployment - South Energy Test Site, Newport, Oregon

Acoustic backscatter data from a WBAT operating at 70kHz deployed at PMEC-SETS from April to September of 2016. 180 pings were collected at 1Hz every two hours, as part of the Advanced Laboratory and Field Arrays (ALFA) for Marine Energy project. Data was subject to preliminary processing (noise removal, a threshold of -75dB was applied, surface turbulence and data below 0.5m from the bottom was removed).

16 TIDAL AND WAVE POWER↗

MBARI WEC 2021 deployment

This dataset includes data from the Monterey Bay Aquarium Research Institute (MBARI) wave energy converter (WEC) and a nearby located Sofar Spotter buoy. The Monterey Bay Aquarium Research Institute has developed and deployed a small two-body point absorber wave energy device suitable to autonomous underwater vehicle, sensor system, and even aquaculture farm needs. For more information on the MBARI WEC see the research journal attached in the submission.

16 TIDAL AND WAVE POWER↗