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Mitra, Bhaskar

Publications and source records attributed to Mitra, Bhaskar.

35 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here, in this work, we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO 2 exchange, soil CO 2 efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSC i ), C translocation (dC i ), and the biomass production efficiency (BPE i ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dC i and BPE i varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPE bgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil–plant–climate interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series

Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.

Mitra, Bhaskar↗
DOE OSTI2021

Irrigation Modernization Decision Support Engine

Irrigation systems are some of the oldest existing infrastructure in the United States. Increasing demands on water resources in combination with the age of these systems has resulted in a need to invest in the modernization of irrigation systems. Modernization activities are difficult to quantify, requiring expertise across multiple different domain areas. Traditionally, the scoping of a modernization project takes several years and requires significant financial investment before the potential of the project can be determined. The Irrigation Modernization Decision Support Engine allows a user to build out different scenarios. These scenarios allow for a course estimation of a project’s potential and the associated costs and benefits of pursuing the scenario. The design of the Decision Support Engine also allows for the easy sharing between different stakeholders, allowing for increased communication and understanding.

Elliott, ShilohN.↗
DOE OSTI2021

Fault location in High Voltage Multi-terminal dc Networks Using Ensemble Learning

Precise location of faults for large distance power transmission networks is essential for faster repair and restoration process. High Voltage direct current (HVdc) networks using modular multi-level converter (MMC) technology has found its prominence for interconnected multi-terminal networks. This allows for large distance bulk power transmission at lower costs. However, they cope with the challenge of dc faults. Fast and efficient methods to isolate the network under dc faults have been widely studied and investigated. After successful isolation, it is essential to precisely locate the fault. The post-fault voltage and current signatures are a function of multiple factors and thus accurately locating faults on a multi-terminal network is challenging. In this paper, we discuss a novel data-driven ensemble learning based approach for accurate fault location. Here we utilize the eXtreme Gradient Boosting (XGB) method for accurate fault location. The sensitivity of the proposed algorithm to measurement noise, fault location, resistance and current limiting inductance are performed on a radial three-terminal MTdc network designed in Power System Computer Aided Design (PSCAD)/Electromagnetic Transients including dc (EMTdc).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2021

Fault Location Using the Natural Frequency of Oscillation of Current Discharge in MTdc Networks

This paper discusses a novel offline-fault location approach using single ended measurements. The natural dissipation of the circuit parameters are considered for fault location. A relationship between the damped natural frequency of oscillation of the transmission line current and fault location is established. The hybrid dc circuit breaker (dcCB) interrupts the fault current, whereby the transmission line current attenuates under the absence of any driving voltage source. The line capacitance discharges into the fault at a specific frequency of oscillation and rate of attenuation. Utilizing this information, the fault location in a multi-terminal direct current (MTdc) network can be obtained. A three terminal radial model of a MTdc is used for performance evaluation of the proposed method using Power System Computer Aided Design (PSCAD)/Electromagnetic Transients including dc (EMTdc).

42 ENGINEERING↗
DOE OSTI2021

Adaptive Threshold-Based Zonal Isolation of Faults in a Multiterminal DC Using Local Measurements

Fast and accurate methods of fault detection and isolation are a pre-emptive measure in multiterminal dc (MTdc) systems. Zonal isolation of faults is necessary to prevent any misopertation of the dc breakers that can lead to a shutdown of the network. Existing techniques require fast-communication or data synchronization methods have their own disadvantages. This article proposes a method for efficient fault zone isolation without the need of a communication link that prevents any misoperation of the dc breakers in a radial MTdc. This method provides individual local measurement-based control to the hybrid dc circuit breakers (dcCB). Faults created outside the zone of protection for a breaker create a change in the rate of change of current or voltage leading to misoperation. To avoid detection using a fixed threshold, an adaptive threshold based approach is suggested that updates the threshold based on the present operating status. Sensitivity analysis by varying the current limiting inductance and fault location is performed. In conclusion, a three terminal radial model of an MTdc is used for zonal isolation using power system computer aided design/electromagnetic transients including dc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Developing a Decision Support Engine to Enable Irrigation Modernization - Poster

Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.

13 HYDRO ENERGY↗
DOE OSTI2019

Allometric relationships between primary size measures and sapwood area for six common tree species in snow-dependent ecosystems in the Southwest United States

High-elevation, snow-dependent, semiarid ecosystems across southwestern United States are expected to be vulnerable to climate change, including drought and fire, with implications for various aspects of the water cycle. To that end, much less is known about the dynamics of transpiration, an important component of the water cycle across this region. At the individual-tree scale, transpiration is estimated by scaling mean sap flux density by the hydroactive sapwood area (SA). SA also remains a key factor in effectively scaling individual tree water-use to stand level. SA across large spatial scales is normally established by relating SA of a few trees to primary size measures, e.g., diameter at breast height (DBH), tree height ( H ), or canopy diameter (CD). Considering the importance of SA in scaling transpiration, the primary objective of this study was therefore to establish six species-specific (aspen, maple, white fir, ponderosa pine, Douglas fir, Englemann spruce) allometric relationships between SA and three primary size measures (DBH, CD, or H ) across two high-elevation, snow-dependent, semiarid ecosystems in New Mexico and Arizona. Based on multiple statistical criteria (coefficient of determination, index of agreement, Nash–Sutcliffe efficiency) and ease of measurement in the forest, we identified DBH as the primary independent variable for estimating SA across all sites. Based on group regression analysis, we found allometric relationships to be significantly ( p < 0.05) different for the same species (ponderosa pine, Douglas-fir) across different sites. Overall, our allometric relationships provide a valuable database for estimating transpiration at different spatial scales from sap flow data in some of our most vulnerable ecosystems.

Forestry↗
DOE OSTI2019

Disentangling the Effects of Temperature, Moisture, and Substrate Availability on Soil CO 2 Efflux

Soil respiration ($R_s$), the largest carbon emission flux in ecosystems, is usually modeled as an empirically parameterized function of temperature, and sometimes water availability. The likely contribution by other factors, such as carbohydrate substrate supply from photosynthesis, has been recognized, but modeling capacity to use this information is limited. Wavelet transformations of the residuals of a seasonal Q 10 temperature response model indicated structure at different temporal scales. In this work, we hypothesize that this indicates the lack of explicit representation of relevant processes in the models. Using cross-spectral analysis, we found that time series of photosynthetically active radiation explained most of the diurnal variation, temperature, explained variability at multiple time scales (diurnal-synoptic), whereas volumetric soil water content correlated with variability in Rs at scales 15-30 days. The results suggest that the time domains of influence for different driving variables of $R_s$ are discrete, and largely nonoverlapping, and represent functional relationships between soil biological activity and its constraints. Analysis of phase angles showed that $R_s$ lagged photosynthetically active radiation by 1.5-3.0 hr. As this time lag was the same in both young and mature trees, with more than fivefold difference in transport distances, we hypothesize that this finding adds to the body of literature that support the pressure-concentration-wave model of carbohydrate availability in plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

AmeriFlux US-NC4 NC_AlligatorRiver

This is the AmeriFlux version of the carbon flux data for the site US-NC4 NC_AlligatorRiver. Site Description - The North Carolina Alligator River site was established to provide core measurements for understanding carbon cycling in natural coastal forested wetlands. It serves as a reference for NC1, NC2 and NC3, representing an ecosystem type that dominated the area prior to European settlement.

Noormets, Asko↗
DOE OSTI2018

Impact of Building-Level Motor Protection on Power System Transient Behaviors

Transmission and distribution system level protection strategies have been extensively investigated to advise better coordination of physical protection devices. A diversity of functional motors with dedicated protection schemes are popularized in increasing number of commercial, residential and industrial buildings. This paper focuses on implementing several most popular protection schemes on Eletro-Magnetic Transient Program (EMTP) simulation for three-phase and single-phase induction motors that exist in commercial buildings connected to typical distribution feeders. Voltage depressions are played in at the head of the feeder fully loaded with functional induction motors to investigate the behaviors of single-phase motor stalling, the action of motor protection and reconnection, and the impacts of device-level protection on system-level dynamics. Several distribution feeders are represented in standard IEEE 39-bus transmission system to simulate fault-induced delayed voltage recovery (FIDVR) and explore mitigation strategies by optimally configuring the building-level motor protection settings.

Liu, Yuan↗
DOE OSTI2018

AmeriFlux US-NC3 NC_Clearcut#3

This is the AmeriFlux version of the carbon flux data for the site US-NC3 NC_Clearcut#3. Site Description - The North Carolina Clearcut site #3 was set up to complement NC2, and continue in place of NC1. The previous rotation of loblolly pine was harvested in the spring of 2012, the site was prepared and replanted with 2-yr old seedlings in the winter of 2012/2013. Measurements were terminated in 2021 due to trees outgrowing the tower and infrastructure capability.

Noormets, Asko↗
DOE OSTI2016

AmeriFlux US-NC2 NC_Loblolly Plantation

This is the AmeriFlux version of the carbon flux data for the site US-NC2 NC_Loblolly Plantation. Site Description - The North Carolina Loblolly Pine site is located in a pine plantation amongst the mixed forests of the North Carolina lower coastal plain. During the late 19th and early 20th centuries the region was logged extensively. After a series of clearcuts, the land was transformed for agricultural practices. In 1967 and 1969, 4000 ha was sold to the Weyerhauser company for agriculture, preservation, and commercial logging of loblolly pines in a series of plantations. The fifth rotation stand surrounding the tower was established in 1992. The only significant natural disturbances during the measurement period was a severe drought that spanned the entire duration of the 2007 growing season. Consequently, the 2007 total amount of precipitation was 486 mm below the 30-year norm. In the same year, the plantation was thinned and fertilized. The stand was thinned in Oct 2009. The eastern half of the site was fertilized in January 2011, and the entire site was fertilized in October 2012.

Noormets, Asko↗