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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Improvements to the Hunter Dose tracking system

Since 1965, the Savannah River Site (SRS) has conducted deer hunts which are open to the general public. SRS performs field monitoring for cesium-137 (Cs-137) of each harvested animal to determine whether the animal may be released to the hunter. A new field system for measuring Cs-137 in the harvested animals has been developed. The system incorporates numerous enhancements compared to the original system. The original system was composed of two Ludlum Measurements scalar-driven 2 inch x 2 inch sodium iodide counters, while the new system is based on a single Ametek Ortec Digibase-driven 2 inch x 4 inch x 16 inch sodium iodide gamma spectrometer. The new system includes a series of easy-to-assemble stainless steel encapsulated lead shields. The combination of the larger detector size and lead shielding improved the detection limit of the new system by a factor of approximately three compared to the original system. This lower detection limit allows for a larger number of measurements to be directly compared to the laboratory results, in cases where animal portions have been sampled. The results from developing and using this system are presented as well as recommendations on improvements to the overall field monitoring of the SRS hunts.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Ceramic Proppant Design for In-situ Microbially Enhanced Methane Recovery

This project designed a new type of multi-functional lightweight proppant. The proppant is utilized as the conventional lightweight proppant but also transports microorganisms to coalbed reservoirs. The proppant is coated with a polymer which protects the methanogenic microorganisms and serves as a time-release delivery for methane generation. To produce the multifunctional proppant, we assigned five tasks: 1) culturing methanogenic microbes from natural carbon sources; 2) identifying optimized growth and methanogenesis conditions for the microbial consortia; 3) synthesizing the lightweight ceramic proppant; 4) encapsulating the consortia and proppant; and 5) demonstrating lab scale simulated performance by monitoring in-situ methane generation and hydraulic conductivity. Task 1) To evaluate the feasibility of ex-situ cultivation, natural microbial populations were collected from various hydrocarbon-rich environments and locations characterized by natural methanogenesis. Different rank coals, complex hydrocarbon sources, hydrocarbon seeps, and natural biogenic environments were incorporated in the sampling. Three levels of screening allowed selection of microbial populations, favorable nutrient amendments, sources of the microbial community, and quantification of methane produced from various coal types. Incubation periods of up to 24 weeks were evaluated at 23°C. Headspace concentrations of CH 4 and CO 2 were analyzed by gas chromatography. After a two-week incubation period of the most promising microbes, generated headspace gas concentrations reached 873,400 ppm for methane and 176,370 ppm for carbon dioxide. Task 2) A central composite design (CCD) was used to explore a broad range of operational conditions, examine the effects of the important environmental factors, such as temperature, pH and salt concentration, and query a feasible region of operation to maximize methane production from coal. Coal biogasification was optimal for this consortium at an initial pH value of 5.5, at 30 °C, and at a NaCl concentration 3.7 mg/cm 3 (i.e., 145,165 ppm). Task 3) To create the lightweight ceramic proppant, the kaolinite and iron oxide (Fe 2 O 3 ) mixture were sintered under reducing atmosphere varying partial pressures of oxygen from 1.7×10 -13 atm to 1.8×10-11 atm. The Fe 2 O 3 reduces to FeO and reacts with kaolinite decomposed to mullite to form Fe 2 SiO 4 , FeSiO 3 , and FeAl 2 O 4 . As a result the proppant develops large pores (~100 µm), giving it a low bulk density (1.43 g/cm 3 ), and high porosity (45.2 vol%) at P_(O_2 )of 1.8×10 -11 atm. The proppant sintered at P_(O_2 )of 1.7×10 -13 atm is characterized by smaller pores (26 µm), higher density (1.72 g/cm3) and lower porosity (37.5 vol%). Crush resistance testing at 9,000 psi yields 6.8 wt% fine particles increasing to 17.7 wt% in porous samples. Acid solubility varies from 5.5 wt% loss increasing to 12.9 wt% in porous samples. Task 4 and 5) The microbial consortia obtained from the optimized condition and lightweight proppant were encapsulated by calcium-alginate polymer. The encapsulation system, including microbes and a proppant, was stored at 20°C and 36°C. The sample stored at 36°C generated 7.1×[10] 3 ppm of methane at 670 h, whereas the sample incubated at 20°C generated 1.1×[10] 3 ppm of methane. Benchtop lab-scale bioreactors were constructed and showed with real-time measurements that, as the microbes produced methane, the pH decreased, and hydrogen and carbon dioxide gases were consumed. A calcium ion-selective sensor revealed the release mechanism of the microbes from encapsulation. The calcium ions interconnecting the alginate monomers were disassociated by counter cations such as protons and potassium ions. The counter cations bound to the carboxyl group on the alginate monomer, which thus lost its ionic interactions with the calcium ions, resulting in decomposition of the hydrogel structure. Furthermore, the conductivity was increased to ~700 mD-ft from ~530 mD-ft once the encapsulated sample was applied to the coal pack. The particle size of coal was reduced when the encapsulated sample was added to the coal. The reduced coal size implied that the microbes would consume the hydrocarbon in coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

dV/dt - Accelerating the Rate of Progress towards Extreme Scale Collaborative Science

This report introduces publications that report the results of a project that aimed to design a computational framework that enables computational experimentation at scale while supporting the model of “submit locally, compute globally”. The project focuses on estimating application resource needs, finding the appropriate computing resources, acquiring those resources,deploying the applications and data on the resources, managing applications and resources during run.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Modal Frequency Identification of a Cylindrical Object from Noisy Vibrational Response Measurements

The investigation of the vibrational response of a cylindrical object in a noisy environment (a pipe in air) to impact excitations provided by a cam-driven, hammer-like surface, randomly excited by an electric motor is of high interest—especially when potential anomalies can occur. This project encompasses all of the components from modeling to validation to controlled testing and signal processing in order develop a real-time system capable of on-board performance and monitoring.

42 ENGINEERING↗
DOE OSTI2019

Advanced Solar and Load Forecasting Incorporating HD Sky Imaging: BNL Phase II Activities (Final Report)

Over the last ten years, lower costs and government incentives for rooftop and utility scale solar photovoltaic (PV) systems have led to a rapid growth in the amount of power generated from this renewable energy source. For example, the cumulative PV generating capacity of 1,160 MW in New York State at the end of 2018 represents a growth of more than 4,000% over the past seven years and almost 400% over the past five years. But increased dependence on this inherently variable energy source introduces the need to anticipate, i.e., forecast, changes in energy production and manage them appropriately. Utilities and grid operators can then use this forecast information to balance changes and maintain stability of the electric grid by adding additional sources or diverting excess supplies for sale or storage, as needed. Current techniques based on persistence modeling are not accurate enough to provide reliable forecasts. With support from the U.S. Department of Energy’s Solar Energy Technology Office (DOE SETO) and the New York Power Authority (NYPA), Brookhaven National Laboratory (BNL), the National Center for Atmospheric Research (NCAR), and the Electric Power Research Institute (EPRI) formed a collaborative team to provide reliable forecasting over a range of time intervals. In addition, the forecasting area was scaled up to about 50 km2, a factor of 20 times larger than previously achieved, so that available solar irradiance could be forecast throughout an entire region including both large generating facilities and distributed rooftop solar arrays. In its role, BNL developed a technology for predicting changes in available solar energy from zero to 30 minutes ahead. This “nowcasting” approach uses inexpensive, off-the-shelf, high definition (HD) imagers with custom software to identify and track the movement of approaching clouds and predict their impact on available solar irradiance. The BNL Nowcasting model improves forecasting accuracy by 20 to 50% over current techniques. Forecasting reliability for low clouds (worst case scenario since they move over solar panels more rapidly than high clouds) was calculated to be 95% accurate for forecast periods of five minute ahead. Reliability decreases with longer forecast time intervals and was calculated to be about 80% for 10 minute forecasts, and about 70% for 20 minutes ahead. Clouds were still reliably tracked by the imager network at 60% accuracy for forecast lead times up to about 30 minutes ahead, and this was determined to be the practical nowcasting limit for low clouds in a network of this scale. This work represents the second phase of a multi-phase effort to develop and deploy solar forecasting at a regional scale so that contributions from distributed rooftop solar resources can be forecast along with solar generating facilities, giving utilities and stakeholders an accurate assessment of future energy production. Additional work is planned to operate the forecasting network in an area upstate New York to assess system reliability under diverse meteorological conditions and to monitor system performance over a full range of seasonal variability.

14 SOLAR ENERGY↗
DOE OSTI2019

Analysis of Multimodal Wearable Sensor Data to Characterize Social Groups and Influence in Organizations

This document reports the results of a 4-month study analyzing data provided to Los Alamos National Laboratory (LANL) by the performer teams for the Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) project. The MOSAIC performer teams monitored hundreds of volunteers from several organizations in their daily activities, using wearable sensors to capture data about those activities. The project also collected “ground truth” data on individual behavior and psychological state using survey instruments throughout the study. The LANL MOSAIC analysis team approached this data with the goal of capturing and analyzing social dynamics within organizations. We focused on two key analysis objectives: identifying and characterizing groups as the evolve over time, and identifying and modeling patterns of social influence.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

CORRTEX Analysis Techniques

Continuous Reflectometry for Radius versus Time Experiments, or CORRTEX, is a diagnostic that was developed during nuclear testing to measure the distance at which rock walls were disrupted by an explosive device as a function of the time at which disruption occurred. Distances recorded are dynamic measurements of cable length as the shockwaves from an explosive event crush the experiment cables, reducing their usable length. Applications of the CORRTEX diagnostic have been expanded in recent times to include instrumentation of the explosive device itself, to record phenomena such as the speed of the detonation wave in the explosive charge and the crushing or disassembly of material in the charge housing. The diagnostic has likewise been used to monitor explosive performance in rock blasting and oil well hole-clearing activities.

42 ENGINEERING↗
DOE OSTI2022

Earned Value Management Systems for Operations Activities

An earned value management system (EVMS), which monitors contractor performance, is a requirement for program and project management for all major acquisitions by the United States Federal Government with development effort: (i.e., an asset requiring management attention because of its importance to an agency’s mission; high development, operating, or maintenance costs; high risk and/or high return). As an area less explored in earned value management (EVM) practices, this paper will survey the application of an EVMS for operations activities defined as: (1) Non-capital asset activities that are projects (or project - like) with definable start and end dates, with discrete scopes of work, and measurable accomplishments; as well as (2) Routine or recurring facility or environmental operations. This paper will examine the use of an EVMS to evaluate performance of operations and maintenance activities required once construction of a capital asset is complete and being used as intended. Such activities include upgrades and maintenance in order for capital assets to meet their mission function over a life-cycle (through repair, replacement, etc.). This paper will provide background on this topic from the perspective of the Department of Energy (DOE) Environmental Management (EM) Program. In addition, it will provide material from a panel discussion provided by a group of experts from the October 2019 Office of Environmental Management Project Management Workshop, as well as material from subsequent research on this topic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Application of Heat Transfer Enhancement (HTE) System for Improved Efficiency of Power Plant Condensers

The mission of the National Energy Technology Laboratory (NETL), a U.S. laboratory under the Department of Energy, is to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future. Through the U.S. Department of Energy (DOE)/Fossil Energy’s (FE) Crosscutting Research Program, NETL funded Interphase Materials to develop and demonstrate a technology to improve power plant condenser efficiency. From 2018 through 2021, Interphase Materials developed THERMOPHASE, an advanced material applied to the condenser during plant operation to increase efficiency and lower fuel consumption, CO 2 emissions, and water withdrawal. THERMOPHASE was evaluated in controlled environments where improvements to heat transfer and a reduction in fouling were observed. THERMOPHASE was also applied to the main condenser of the Longview Power plant and changes to the plant performance were monitored. After two years following application of THERMOPHASE, a reduction in condenser back pressure of 0.26 ± 0.13 inHg was observed resulting in an estimated $3.35M in fuel savings, 136 million lbs. of decreased CO 2 emissions, and 1,287 million gallons reduced water withdrawal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

T-1072: Beam test for muon strips

Beam test for muon strips is an experiment to measure the efficiency, time resolution and longitudinal position resolution of scintillator strips for a muon system at future colliders. The muon system at future colliders is envisioned as several layers of position-sensitive detectors embedded in the iron flux-return yoke of the solenoidal magnet. The role of the muon system is primarily the identification of muons and track matching to the central tracker, besides serving as the tail catcher for the hadronic showers that penetrate beyond the hadron calorimetry. Previous tests performed at Fermilab with cosmic muons have shown that scintillators with wavelength-shifting (WLS) fibers and a SiPM readout offer promising performance (NIM A 823, 2016, pp.120-125). The purpose of the present beam tests is to determine the performance parameters with better accuracy. The measurement setup is schematically presented in Fig. 1. The length of the tested strips will vary between 1 m and 2 m. The scintillator strip to be tested will be placed horizontally perpendicular to the beam on a platform in the area behind the beam dump of MT6.2. Two fast scintillators S1 and S2 with vacuum PMT readout will be placed in front and after the tested strip in the beam. The distance between S1 and S2 is 1 m. One fast scintillator strip S3 will be placed in beam immediately in front of the tested strip, perpendicular to the tested strip. A rack with a CAMAC crate and two NIM crates will be used for the data acquisition. The data collection will be performed and monitored from a PC with USB connection to the CAMAC Crate controller.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Data distribution service-based interoperability framework for smart grid testbed infrastructure

This study presents the design and implementation of a communication and control infrastructure for smart grid operation. The proposed infrastructure enhances the reliability of the measurements and control network. The advantages of utilizing the data-centric over message-centric communication approach are discussed in the context of smart grid applications. The data distribution service (DDS) is used to implement a data-centric common data bus for the smart grid. This common data bus improves the communication reliability, enabling distributed control and smart load management. These enhancements are achieved by avoiding a single point of failure while enabling peer-to-peer communication and an automatic discovery feature for dynamic participating nodes. The infrastructure and ideas presented in this paper were implemented and tested on the smart grid testbed. A toolbox and application programing interface for the testbed infrastructure are developed in order to facilitate interoperability and remote access to the testbed. This interface allows control, monitoring, and performing of experiments remotely. Furthermore, it could be used to integrate multidisciplinary testbeds to study complex cyber-physical systems (CPS).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantum Key Distribution for Critical Infrastructures: Towards Cyber-Physical Security for Hydropower and Dams

Hydropower facilities are often remotely monitored or controlled from a centralized remote control room. Additionally, major component manufacturers monitor the performance of installed components, increasingly via public communication infrastructures. While these communications enable efficiencies and increased reliability, they also expand the cyber-attack surface. Communications may use the internet to remote control a facility’s control systems, or it may involve sending control commands over a network from a control room to a machine. The content could be encrypted and decrypted using a public key to protect the communicated information. These cryptographic encoding and decoding schemes become vulnerable as more advances are made in computer technologies, such as quantum computing. In contrast, quantum key distribution (QKD) and other quantum cryptographic protocols are not based upon a computational problem, and offer an alternative to symmetric cryptography in some scenarios. Although the underlying mechanism of quantum cryptogrpahic protocols such as QKD ensure that any attempt by an adversary to observe the quantum part of the protocol will result in a detectable signature as an increased error rate, potentially even preventing key generation, it serves as a warning for further investigation. In QKD, when the error rate is low enough and enough photons have been detected, a shared private key can be generated known only to the sender and receiver. We describe how this novel technology and its several modalities could benefit the critical infrastructures of dams or hydropower facilities. The presented discussions may be viewed as a precursor to a quantum cybersecurity roadmap for the identification of relevant threats and mitigation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Explosion Detection Using Smartphones: Ensemble Learning with the Smartphone High-Explosive Audio Recordings Dataset and the ESC-50 Dataset

Explosion monitoring is performed by infrasound and seismoacoustic sensor networks that are distributed globally, regionally, and locally. However, these networks are unevenly and sparsely distributed, especially at the local scale, as maintaining and deploying networks is costly. With increasing interest in smaller-yield explosions, the need for more dense networks has increased. To address this issue, we propose using smartphone sensors for explosion detection as they are cost-effective and easy to deploy. Although there are studies using smartphone sensors for explosion detection, the field is still in its infancy and new technologies need to be developed. We applied a machine learning model for explosion detection using smartphone microphones. The data used were from the Smartphone High-explosive Audio Recordings Dataset (SHAReD), a collection of 326 waveforms from 70 high-explosive (HE) events recorded on smartphones, and the ESC-50 dataset, a benchmarking dataset commonly used for environmental sound classification. Two machine learning models were trained and combined into an ensemble model for explosion detection. The resulting ensemble model classified audio signals as either “explosion”, “ambient”, or “other” with true positive rates (recall) greater than 96% for all three categories.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Optimizing Deep Geothermal Drilling for Energy Sustainability in the Appalachian Basin

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings.

Environmental Sciences & Ecology↗
DOE OSTI2020

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh–Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10 % accuracy. The limitation of the model and the required steps forward are discussed.

17 WIND ENERGY↗