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DOE OSTI2018

Xi-cam : a versatile interface for data visualization and analysis

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam 's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam 's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

Pandolfi, Ronald J. (ORCID:0000000308248548)↗

DOE OSTI2019

ParaOpt: Automated Application Parameterization and Optimization for the Cloud

The variety of instance types available on cloud platforms offers enormous flexibility to match the requirements of applications with available resources. However, selecting the most suitable instance type and configuring an application to optimally execute on that instance type can be complicated and time-consuming. For example, application parallelism flags must match available cores and problem sizes must be tuned to match available memory. As the search space of application configurations can be enormous, we propose an automated approach, called ParaOpt, to automatically explore and tune application configurations on arbitrary cloud instances. ParaOpt supports arbitrary applications, enables use of custom optimization methods, and can be configured with different optimization targets such as runtime and cost. We evaluate ParaOpt by optimizing genomics, molecular dynamics, and machine learning applications with four types of optimizers. We show with as few as 15 parameterized executions of an application, representing between 1.2%-26.7% of the search space, that ParaOpt is able to identify the optimal configuration in 32.7% of experiments and a near-optimal configuration in 83.2% of cases. As a result of using near-optimal configurations, ParaOpt reduces overall execution time by up to 85.8% when compared with using the default configuration.

Wu, Chaofeng↗

DOE OSTI2019

Convolutional Neural Networks for Hydrometeor Classification using Dual Polarization Doppler Radars

Traditional fuzzy logic hydrometeor classification algorithm is a common way to classify precipitation type from dual polarization doppler radar. We propose a deep learning-based method to estimate hydrometeors efficiently using observed radar variables such as horizontal reflectivity (Z H ), differential reflectivity (Z DR ), correlation coefficient (ρ HV ) and specific differential phase (K DP ) from National Weather Service NEXRAD collected at Vance AFB facility at the first elevation angle from January 1st, 2015 to July 31th, 2019. We stack matrices of values from these four polarimetric variables as one 3D array. Samples are preprocessed and divided into training, validation and test set with four target hydrometeor categories (Ice Crystals (IC), Dry Snow (DS), Light and/or Moderate Rain (RA) and Big Drops (rain) (BD)). We developed and optimized five Convolutional Neural Networks (CNNs) architectures and achieved an accuracy of 87.23% and 93.736% respectively using modified ResNet with two different input data selection strategies for hydrometeor classification. Training data selection strategies were important to ensure use of available samples in training for robust performance evaluated by applying the models to novel time period beyond what was use to train the model. Seasonal variation in atmospheric conditions lead to seasonal patterns of liquid vs solid forms of precipitation, that poses challenge for classifier and offer insights into domain specific approaches required for problem of hydrometeor identification. Computationally efficient and scalable approach for classification of hydrometeors offer opportunties to effectively use the large volumes of rich time series of radar observations that are becoming increasingly available.

Lu, Yuping↗

DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗

DOE OSTI2022

Evaluation of Horizon of Viability Optimization Engine for Sustained Power to Critical Infrastructure: Preprint

In the aftermath of increasingly frequent catastrophic events, a typical scenario is Critical Infrastructure (CI) units being supported by available backup sources with a weak power grid that can be intermittent or absent. Such a scenario is significantly challenging in the sense of reliable supply of power to CI units. In this article, an intelligent optimization scheme termed as Horizon of Viability (HoV) engine is developed to guarantee the viability of a sustained reliable supply of power to the CI units over a time-horizon. The proposed HoV engine generates a cost-optimal portfolio of the locally available generation sources and the loads over a time horizon using a mixed-integer convex programming problem. A Controller hardware-in-the-loop (CHIL) platform is developed to evaluate the control performance of the HoV engine. The experimental results corroborates the efficacy in maintaining the viability of the CI units after a grid interruption event. Further, the proposed HoV optimization scheme performs better compared to existing net-load management schemes in the literature.

disaster resiliency↗

DOE OSTI2023

A Medium-/Low-Voltage Joint State Estimator Through Linear Uncertainty Propagation

Traditionally, distribution system state estimations (DSSE) are challenged by the lack of measurements at both primary and secondary sides of the system. The widely available cable television (CATV) voltage sensors installed in low-voltage (LV) networks bring opportunities to achieve higher quality DSSE covering a broader area of the distribution network. This study proposes a medium-/low-voltage (MV/LV) joint distribution system state estimation approach using the untapped CATV measurements. It aims at addressing the need for system situational awareness at the grid edge while improving the estimation accuracy at both the primary and secondary sides compared to its disjointed counterpart. Linearized measurement functions and boundary condition uncertainty propagation rules are derived to ensure the computational efficiency and accuracy of the joint state estimator. Numerical experiments are conducted on an IEEE test feeder to demonstrate the efficacy of the proposed method and the value of CATV measurements.

joint state estimation↗

DOE OSTI2017

Experimental Evaluation of Load Rejection Over-Voltage from Grid-Tied Solar Inverters

This paper investigates the impact of load rejection over-voltage (LRO) from commercially available grid-tied photovoltaic (PV) solar inverters. LRO can occur when a local feeder or breaker opens and the power output from a distributed energy resource exceeds the load power. Simplified models of current controlled inverters can over-predict over-voltage magnitudes, thus it is useful to quantify testing. The load rejection event was replicated using a hardware testbed at the National Renewable Energy Laboratory (NREL), and a set of commercially available PV inverters was tested to quantify the impact of LRO for a range of generation-to-load ratios. The magnitude and duration of the over-voltage events are reported in this paper along with a discussion of characteristic inverter output behavior. The results for the inverters under test showed that maximum over-voltage magnitudes were less than 200 percent of nominal voltage, and much lower in many test cases. These research results are important because utilities that interconnect inverter-based DER need to understand their characteristics under abnormal grid conditions.

14 SOLAR ENERGY↗

DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

A complete electrical shock hazard classification system and its application

Current electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. As a result, this leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. We find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz power. This paper proposes a method of classifying all of the electrical shock hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Lastly, the new comprehensive electrical shock hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards.

42 ENGINEERING↗

DOE OSTI2016

Special Nuclear Material Characterization Using Digital 3-D Position Sensitive CdZnTe Detectors and High Purity Germanium Spectrometers

Special nuclear material (SNM) monitoring often requires high resolution gamma-ray spectroscopy for material characterization. Portable systems and rapid deployment are also highly valued for some applications. Deployable gamma-ray imaging spectrometers using pixelated CdZnTe semiconductor detectors have become commercially available within the past three years to meet these requirements. CdZnTe systems have demonstrated room-temperature energy resolutions below 0.5% FWHM at 662 keV using single pixel events and below 0.7% FWHM at 662 keV using all events. The systems are able to go from storage to measurement in less than two minutes. Special nuclear materials were measured at the Y-12 National Security Complex and at the Device Assembly Facility at the Nevada National Security Site. The use of a CdZnTe system to measure uranium enrichment was demonstrated and uranium spectral features were compared to a commercially available high purity germanium (HPGe) spectrometer. The use of passive gamma ray spectroscopy techniques to estimate plutonium grade using CdZnTe detectors was demonstrated for the first time.

CdZnTe detectors, gamma-ray imaging, gamma-ray spe↗

DOE OSTI2020

Sedimentation of ballasted cells-free EPS in meromictic Fayetteville Green Lake

Fayetteville Green Lake (FGL) is a recognized, extensively studied present-day model of the stratified Proterozoic Ocean. Nonetheless, biomass sedimentation in FGL remains hard to explain: Whilst virtually all sediment pigments belong to photosynthetic sulfur bacteria (PSB) from a chemocline, the isotopic carbon signature of the bulk biomass suggests its epilimnetic phytoplankton origin. Here we present experimental evidence that FGL Synechococci produce copious extracellular polysacchrides (EPS), which become impregnated with Ca, Mg and Na cations and are release to the environment as ballasted cell coverings. We propose that sedimentation of these cell-free EPS can constitute the bulk of pigment-less organic material in FGL sediment. Because increased availability of inorganic carbon (Ci) stimulates accumulation of ballasted EPS, we propose the universal role of cyanobacterial EPS in biomass sedimentation in the high-Ci Paleoproterozoic Ocean as well as in modern aquatic systems like FGL.

Kamennaya, Nina A.↗

DOE OSTI2022

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Abstract Projection of land use and land‐cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land‐use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well‐defined conservation goals while minimizing impacts to agriculture.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Direct Numerical Simulation of the Flow through a Randomly Packed Pebble Bed

The proposition for molten salt and high-temperature gas-cooled reactors has increased the focus on the dynamics and physics in randomly packed pebble beds. Research is being conducted on the validity of these designs as a possible contestant for the fourth-generation nuclear power systems. A detailed understanding of the coolant flow behavior is required in order to ensure proper cooling of the reactor core during normal and accident conditions. In order to increase the understanding of the flow through these complex geometries and enhance the accuracy of lower-fidelity modeling, high-fidelity approaches such as direct numerical simulation (DNS) can be utilized. Nek5000, a spectral-element computational fluid dynamics (CFD) code, was used to develop DNS fluid flow data. The flow domain consisted of 147 pebbles enclosed by a bounding wall. In the work presented, the Reynolds numbers ranged from 430 to 1050 based on the pebble diameter and inlet velocity. Characteristics of the flow domain such as volume averaged porosity, axial porosity, and radial porosity were studied and compared with correlations available in the literature. Friction factors from the DNS results for all Reynolds numbers were compared with correlations in the literature. The first- and second-order statistics show good agreement with the available experimental data. Turbulence length scales were analyzed in the flow. Reynolds stress anisotropy was characterized by utilizing invariant analysis. Overall, the results of the analysis in this study provide deeper understanding of the flow behavior and the effect of the wall in packed beds.

Yildiz, Mustafa Alper↗

DOE OSTI2021

Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics

Wind energy is one of the largest sources of renewable energy in the world. To further reduce the operations and maintenance (O&M) costs of wind farms, it is essential to be able to accurately pinpoint the root causes of different failure modes of interest. An example of such a failure mode that is not yet fully understood is white etching cracks (WEC). This can cause the bearing lifetime to be reduced to 5–10% of its design value. Multiple hypotheses are available in literature concerning its cause. To be able to validate or disprove these hypotheses, it is essential to have historic high-frequency measurement data (e.g., load and vibration levels) available. In time, this will allow linking to the history of the turbine operating data with failure data. This paper discusses the dynamic loading on the turbine during certain events (e.g., emergency stops, run-ups, and during normal operating conditions). By combining the number of specific events that each turbine has seen with the severity of each event, it becomes possible to assess which turbines are most likely to show signs of damage.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2013

Integrated Energy-Water Planning in the Western and Texas Interconnections

While long-term regional electricity transmission planning has traditionally focused on cost, infrastructure utilization, and reliability, issues concerning the availability of water represent an emerging issue. Thermoelectric expansion must be considered in the context of competing demands from other water use sectors balanced with fresh and non-fresh water supplies subject to climate variability. An integrated Energy-Water Decision Support System (DSS) is being developed that will enable planners in the Western and Texas Interconnections to analyze the potential implications of water availability and cost for long-range transmission planning. The project brings together electric transmission planners (Western Electricity Coordinating Council and Electric Reliability Council of Texas) with western water planners (Western Governors’ Association and the Western States Water Council). This paper lays out the basic framework for this integrated Energy-Water DSS.

electricity↗

DOE OSTI2014

Modification of the TASMIP x-ray spectral model for the simulation of microfocus x-ray sources

Purpose: The availability of accurate and simple models for the estimation of x-ray spectra is of great importance for system simulation, optimization, or inclusion of photon energy information into data processing. There is a variety of publicly available tools for estimation of x-ray spectra in radiology and mammography. However, most of these models cannot be used directly for modeling microfocus x-ray sources due to differences in inherent filtration, energy range and/or anode material. For this reason the authors propose in this work a new model for the simulation of microfocus spectra based on existing models for mammography and radiology, modified to compensate for the effects of inherent filtration and energy range. Methods: The authors used the radiology and mammography versions of an existing empirical model [tungsten anode spectral model interpolating polynomials (TASMIP)] as the basis of the microfocus model. First, the authors estimated the inherent filtration included in the radiology model by comparing the shape of the spectra with spectra from the mammography model. Afterwards, the authors built a unified spectra dataset by combining both models and, finally, they estimated the parameters of the new version of TASMIP for microfocus sources by calibrating against experimental exposure data from a microfocus x-ray source. The model was validated by comparing estimated and experimental exposure and attenuation data for different attenuating materials and x-ray beam peak energy values, using two different x-ray tubes. Results: Inherent filtration for the radiology spectra from TASMIP was found to be equivalent to 1.68 mm Al, as compared to spectra obtained from the mammography model. To match the experimentally measured exposure data the combined dataset required to apply a negative filtration of about 0.21 mm Al and an anode roughness of 0.003 mm W. The validation of the model against real acquired data showed errors in exposure and attenuation in line with those reported for other models for radiology or mammography. Conclusions: A new version of the TASMIP model for the estimation of x-ray spectra in microfocus x-ray sources has been developed and validated experimentally. Similarly to other versions of TASMIP, the estimation of spectra is very simple, involving only the evaluation of polynomial expressions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Prior-based artifact correction (PBAC) in computed tomography

Purpose: Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. Methods: The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form of a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. Results: The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. Conclusions: The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Comparison of 2D and 3D gamma analyses

Purpose: As clinics begin to use 3D metrics for intensity-modulated radiation therapy (IMRT) quality assurance, it must be noted that these metrics will often produce results different from those produced by their 2D counterparts. 3D and 2D gamma analyses would be expected to produce different values, in part because of the different search space available. In the present investigation, the authors compared the results of 2D and 3D gamma analysis (where both datasets were generated in the same manner) for clinical treatment plans. Methods: Fifty IMRT plans were selected from the authors’ clinical database, and recalculated using Monte Carlo. Treatment planning system-calculated (“evaluated dose distributions”) and Monte Carlo-recalculated (“reference dose distributions”) dose distributions were compared using 2D and 3D gamma analysis. This analysis was performed using a variety of dose-difference (5%, 3%, 2%, and 1%) and distance-to-agreement (5, 3, 2, and 1 mm) acceptance criteria, low-dose thresholds (5%, 10%, and 15% of the prescription dose), and data grid sizes (1.0, 1.5, and 3.0 mm). Each comparison was evaluated to determine the average 2D and 3D gamma, lower 95th percentile gamma value, and percentage of pixels passing gamma. Results: The average gamma, lower 95th percentile gamma value, and percentage of passing pixels for each acceptance criterion demonstrated better agreement for 3D than for 2D analysis for every plan comparison. The average difference in the percentage of passing pixels between the 2D and 3D analyses with no low-dose threshold ranged from 0.9% to 2.1%. Similarly, using a low-dose threshold resulted in a difference between the mean 2D and 3D results, ranging from 0.8% to 1.5%. The authors observed no appreciable differences in gamma with changes in the data density (constant difference: 0.8% for 2D vs 3D). Conclusions: The authors found that 3D gamma analysis resulted in up to 2.9% more pixels passing than 2D analysis. It must be noted that clinical 2D versus 3D datasets may have additional differences—for example, if 2D measurements are made with a different dosimeter than 3D measurements. Factors such as inherent dosimeter differences may be an important additional consideration to the extra dimension of available data that was evaluated in this study.

61 RADIATION PROTECTION AND DOSIMETRY↗