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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Geomechanical modeling of distributed fiber-optic sensor measurements

Fiber-optic-based distributed acoustic sensors (DAS) are a new technology that can be deployed in a well and are continuously interrogated during operations. These sensors calculate the strain (or strain rate) at all points along the fiber and have been used extensively to monitor hydraulic stimulations. The data from these sensors indicate that they are sensitive to high-frequency signals associated with microseismicity and low-frequency signals associated with fracture growth. We have developed a set of idealized models to simulate these signals and to identify interpretation methods that may be used to estimate fracture location, geometry, and extent. We use a multiphysics code that includes rock physics, fluid flow, and elastic-wave propagation to generate synthetic DAS measurements from a set of simple models that mimic hydraulic fracturing. We then relate the signals observed in the synthetic DAS to specific features in the model such as fracture height, width, and aperture. Our results demonstrate that the synthetic DAS measurements may be used to determine field DAS measurements and to optimize the design of future sensor deployments for sensitivity to fracture attributes.

03 NATURAL GAS↗
DOE OSTI2018

The Low-Mass Limit: Dark Matter Detectors with eV-Scale Energy Resolution

The SuperCDMS SNOLAB experiment will be a 20-kg scale Si and Ge direct dark matter detection experiment designed to probe down to 300 MeV in dark matter (DM) mass through DM-nucleus scattering and 500 keV in DM electron scattering. In order to reach these low masses with appreciable sensitivity to dark matter, it needs to achieve very low energy resolution ($\le 10$ ev) for nuclear recoils in both detector materials, which will be achieved using a new detector design and operating mode, CDMS HV. This detector is designed to operate at a bias of 100V to convert charges liberated in our detector targets to into phonon energy in order to resolve individual electron-hole pairs. This has never before been achieved in a kg-scale detector. In this thesis, I cover three elements of the design of the CDMS HV detectors. I discuss the detector physics controlling how charges and phonons are generated in our detector crystals, comparing theory to results of recent experiments carried out at Stanford. I move on to describe the operating principles of our phonon-mediated charge readout, as well as the design of the CDMS HV detector. I then describe the performance tests of early CDMS HV prototypes in conjunction with the SuperCDMS SNOLAB electronics, and discuss the path towards achieving single electron-hole pair resolving detectors at the kg-scale given the performance obtained thus far. As a result of these tests, we were able to refine our noise and sensor dynamics models, and develop new metrics for diagnosing non-ideal sources of noise to aid in reducing coupling of the external environment to our detectors. In order to study the microphysics of phonon and charge production in our target crystals, we fabricated a number of gram-scale devices with various sensor designs in order to separate sensor and environmental effects from intrinsic crystal properties. These devices provided the first successful demonstrating of using voltage to amplify charge energ y by production of phonons (the Neganov-Trofimov-Luke effect! ) in order to resolve electron-hole pairs, and opened up a new regime of dark matter and photon science at the gram-scale that we are just beginning to explore. A first dark matter search was carried out with one of these gram-scale devices, producing world-leading limits on electron-recoiling dark matter between 0.5 and 5 MeV in dark matter mass for multiple form factors. This device achieved a phonon resolution of 10~eV, allowing a single gram-day of exposure to rival kg-days of exposure in the competing liquid-noble based electron-recoil search.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

‪A Novel Methodology for Longitudinal Studies of Home Thermal Comfort Perception and Behavior

Human-building interactions significantly influence building energy consumption and affect peak energy demand. For example, heating and cooling contribute 46% of daily peak residential energy demand. Grid-interactive efficient buildings (GEBs) can potentially increase energy-demand flexibility and accelerate the adoption of renewables. However, traditional demand response (DR) programs focused on shedding peak loads disregard the human-building interactions leading to occupant thermal frustration. Specifically, they do not model occupants’ ability to override thermostat controls, nor how indoor environmental conditions and sociocultural factors affect the timing and magnitude of overrides. Studies have found 20% of occupants override thermostat setpoints during DR events longer than 6 hours yet lack detail about the motivation that might guide more successful efforts. Balancing energy-demand flexibility with occupant thermal comfort requires understanding dynamic occupant behavior, the underlying psychophysiological drivers, in the context of homes. This paper presents methods for scalable longitudinal studies of residential occupant behavior dynamics to inform the development of psychophysiological occupant-centric building models. Smart sensors were installed to measure local environmental conditions in 20 homes in two regions of the United States. Just-in-time ecological momentary assessments (EMAs) provided qualitative data on occupant thermal comfort and local environmental conditions not captured in Internet-of-Things (IoT) based studies or existing datasets. Participant interviews provided insight into environmental attitudes, mental models, and the role of economics in comfort and behavior, which in turn may affect thermostat interactions. Based on these data, interventions in the next phase of the study will collect data and monitor occupant behavior during simulated DR events.

Kane, Michael↗
DOE OSTI2021

Performance Demonstration of Self-Powered Neutron Detectors for Steady-State Reactor Operations

The irradiation testing of sensors in reactors is a crucial step towards calibrating and qualifying sensors prior to their deployment in experiments. This report details the process toward qualifying and calibrating custom-designed rhodium-based self-power neutron detectors (Rh-SPNDs) for steady-state reactor irradiations. This process serves to both demonstrate the performance capabilities of Rh-SPNDs as well as to provide experimental data for development of a sensor sensitivity model. Two designs of Rh-SPNDs were tested in various reactors to demonstrate: detection resolution in a low neutron flux environment, a delayed-response compensation technique, output linearity in a large range of neutron flux, and measurement accuracy verified with dosimetry. The detection resolution and compensation technique was demonstrated in the AGN-201m reactor at Idaho State University. The irradiation confirmed the sensors’ capability to perform steady-state operations in a low neutron flux of ~2E8 n/cm 2 -sec. Sensor output linearity coupled with the delayed-response compensation was investigated at the neutron radiography reactor at Idaho National Laboratory. A Rh-SPND was irradiated to neutron fluxes ranging from 2E8 to 2E13 n/cm2-sec range. The measured data demonstrated a wide and linear range of operation with a measured linear sensitivity of 1.0129 ×10 -13 A/W with a correlation-squared value of r 2 =0.9927. The measurement accuracy was investigated at the Advanced Test Reactor Critical reactor. The SPNDs were inserted into a test vehicle with collocated flux wires. Two irradiations with different flux levels were performed, and the SPNDs relative measurement between the two irradiations was calculated to be 1.2613 ± 0.0153 for the small SPND design and 1.1809 ± 0.0108 for the large SPND design. Both SPND measurements fell between the co-axial dosimetry result, which reported 1.218 ± 0.047. Additionally, the preliminary MCNP model for calculating SPND sensitivity was developed in parallel to this work. Modeled neutron spectrum with measured magnitude was used for inputs to determine the simulated SPND output. The results showed an overestimation of signal strength by a factor of 5, which was expected because of model simplification. This leads to future modeling work to account for signal losses from additional physical properties, including high temperature environments for FY-21.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Mutual capacitance of liquid conductors in deformable tactile sensing arrays

Advances in highly deformable electronics are needed in order to enable emerging categories of soft computing devices ranging from wearable electronics, to medical devices, and soft robotic components. The combination of highly elastic substrates with intrinsically stretchable conductors holds the promise of enabling electronic sensors that can conform to curved objects, reconfigurable displays, or soft biological tissues, including the skin. Here, we contribute sensing principles for tactile (mechanical image) sensors based on very low modulus polymer substrates with embedded liquid metal microfluidic arrays. The sensors are fabricated using a single-step casting method that utilizes fine nylon filaments to produce arrays of cylindrical channels on two layers. The liquid metal (gallium indium alloy) conductors that fill these channels readily adopt the shape of the embedding membrane, yielding levels of deformability greater than 400%, due to the use of soft polymer substrates. We modeled the sensor performance using electrostatic theory and continuum mechanics, yielding excellent agreement with experiments. Using a matrix-addressed capacitance measurement technique, we are able to resolve strain distributions with millimeter resolution over areas of several square centimeters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning

Identification of capacitor switching transient location provides valuable insight into the state of the associated equipment. Machine learning (ML) models, and convolutional neural networks (CNNs) in particular, have demonstrated remarkable performance in signal location. However, ML models are data driven whose predictions are affected by noise in data and may also suffer from large extrapolation errors when applied to new conditions. Uncertainty quantification (UQ) is necessary to ensure model trustworthiness and avoid overconfident predictions in extrapolation. Here, in this work, we propose a novel UQ method, called PI3NN, to quantify prediction uncertainty of ML models and integrate the method with CNNs for transient source location. PI3NN calculates Prediction Intervals by training 3 Neural Networks and uses root-finding methods to determine the interval precisely. Additionally, PI3NN can identify out-of-distribution (OOD) data in a nonstationary condition to avoid overconfident prediction. Results indicate that with PI3NN, transient signals are not only correctly identified, but when said signals are subject to corruptions characteristic of an actual power monitoring system (e.g. non-ideal sensors), the model recognizes when it is uncertain about its predictions, effectively letting the user know when to accept or discard the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Modelling a Transition-Edge Sensor X-Ray Microcalorimeter Linear Array for Compton Profile Measurements and Energy Dispersive Diffraction

Transition-edge sensors (TES) are a type of superconducting detector that offers high energy resolution based on their sharp resistance-temperature feature in the superconducting-to-normal transition. TES X-ray microcalorimeters have typically been designed and used for spectroscopic applications. In this work, we present a design optimization for a TES X-ray microcalorimeter array for high-energy scattering and diffraction measurements. Specifically, Compton scattering provides information about the electron momentum distribution, while energy dispersive diffraction provides structural information about dense engineering materials. Compton scattering and energy dispersive diffraction experiments must be conducted in the very hard X-ray regime (~100 keV), demanding a high X-ray stopping power in the detector; therefore, an absorber with a large heat capacity is needed in conjunction with the TES. In addition, both applications would benefit from an array composed of parallel strips. We propose a design for a TES X-ray microcalorimeter optimized for such applications. In particular, we model the longitudinal position dependence due to the finite thermal diffusion time in the absorber.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Final Report - Sensor Development for Future e + e - Colliders

This project advances electromagnetic calorimeter sensor development for future electron-positron colliders, particularly the International Linear Collider (ILC). The ILC, under consideration for construction in Japan, will collide electrons and positrons at a 500 GeV baseline center-of-mass collision energy. The multi-volume ILC Technical Design Report describes two detector concepts, SiD and ILD, based on their “Detailed Baseline Design” documents. SiD and ILD are continuing to develop their technologies in anticipation of a positive decision from Japan in 2018. The ILC and its detectors will make unprecedented precision measurements relating to the Higgs boson and the top quark, and search for new phenomena that could be missed at the LHC, such as electroweak particles expected in some beyond the standard models. The sensor development covered by this project primarily pertains to the electromagnetic calorimeters (EMCal). This work continues conceptual work towards realistic modules. It is important to emphasize that the HEP sensor development on this project will enable applications beyond HEP. It does not include detector engineering. This proposal is a collaboration among one National Laboratory and four universities from Japan and two National Laboratories and four universities from the U.S.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

AVESTAR Center for Operational Excellence of Electricity Generation Plants

To address industry challenges in attaining operational excellence for electricity generation plants, the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has launched a world-class facility for Advanced Virtual Energy Simulation Training and Research (AVESTARTM). This presentation will highlight the AVESTARTM Center simulators, facilities, and comprehensive training, education, and research programs focused on the operation and control of high-efficiency, near-zero-emission electricity generation plants. The AVESTAR Center brings together state-of-the-art, real-time, high-fidelity dynamic simulators with full-scope operator training systems (OTSs) and 3D virtual immersive training systems (ITSs) into an integrated energy plant and control room environment. AVESTAR’s initial offering combines--for the first time--a “gasification with CO2 capture” process simulator with a “combined-cycle” power simulator together in a single OTS/ITS solution for an integrated gasification combined cycle (IGCC) power plant with carbon dioxide (CO2) capture. IGCC systems are an attractive technology option for power generation, especially when capturing and storing CO2 is necessary to satisfy emission targets. The AVESTAR training program offers a variety of courses that merge classroom learning, simulator-based OTS learning in a control-room operations environment, and immersive learning in the interactive 3D virtual plant environment or ITS. All of the courses introduce trainees to base-load plant operation, control, startups, and shutdowns. Advanced courses require participants to become familiar with coordinated control, fuel switching, power-demand load shedding, and load following, as well as to problem solve equipment and process malfunctions. Designed to ensure work force development, training is offered for control room and plant field operators, as well as engineers and managers. Such comprehensive simulator-based instruction allows for realistic training without compromising worker, equipment, and environmental safety. It also better prepares operators and engineers to manage the plant closer to economic constraints while minimizing or avoiding the impact of any potentially harmful, wasteful, or inefficient events. The AVESTAR Center is also used to augment graduate and undergraduate engineering education in the areas of process simulation, dynamics, control, and safety. Students and researchers gain hands-on simulator-based training experience and learn how the commercial-scale power plants respond dynamically to changes in manipulated inputs, such as coal feed flow rate and power demand. Students also analyze how the regulatory control system impacts power plant performance and stability. In addition, students practice start-up, shutdown, and malfunction scenarios. The 3D virtual ITSs are used for plant familiarization, walk-through, equipment animations, and safety scenarios. To further leverage the AVESTAR facilities and simulators, NETL and its university partners are pursuing an innovative and collaborative R&D program. In the area of process control, AVESTAR researchers are developing enhanced strategies for regulatory control and coordinated plant-wide control, including gasifier and gas turbine lead, as well as advanced process control using model predictive control (MPC) techniques. Other AVESTAR R&D focus areas include high-fidelity equipment modeling using partial differential equations, dynamic reduced order modeling, optimal sensor placement, 3D virtual plant simulation, and modern grid. NETL and its partners plan to continue building the AVESTAR portfolio of dynamic simulators, immersive training systems, and advanced research capabilities to satisfy industry’s growing need for training and experience with the operation and control of clean energy plants. Future dynamic simulators under development include natural gas combined cycle (NGCC) and supercritical pulverized coal (SCPC) plants with post-combustion CO2 capture. These dynamic simulators are targeted for use in establishing a Virtual Carbon Capture Center (VCCC), similar in concept to the DOE’s National Carbon Capture Center for slipstream testing. The VCCC will enable developers of CO2 capture technologies to integrate, test, and optimize the operation of their dynamic capture models within the context of baseline power plant dynamic models. The objective is to provide hands-on, simulator-based “learn-by-operating” test platforms to accelerate the scale-up and deployment of CO2 capture technologies. Future AVESTAR plans also include pursuing R&D on the dynamics, operation, and control of integrated electricity generation and storage systems for the modern grid era. Special emphasis will be given to combining load-following energy plants with renewable and distributed generating supplies and fast-ramping energy storage systems to provide near constant baseload power.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Four-Stage Multi-Physics Simulations to Assist Temperature Sensor Design for Industrial-Scale Coal-Fired Boiler

The growth of renewable energy sources presents a pressing challenge to the operation and maintenance of existing fossil fuel power plants, given that fossil fuel remains the predominant fuel source, responsible for over 60% of electricity generation in the United States. One of the main concerns within these fossil fuel power plants is the unpredictable failure of boiler tubes, resulting in emergency maintenance with significant economic and societal consequences. A reliable high-temperature sensor is necessary for in situ monitoring of boiler tubes and the safety of fossil fuel power plants. In this study, a comprehensive four-stage multi-physics computational framework is developed to assist the design, optimization installation, and operation of the high-temperature stainless-steel and quartz coaxial cable sensor (SSQ-CCS) for coal-fired boiler applications. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. With the simulation-guided sensor installation plan, the newly designed SSQ-CCSs have been employed for field testing for more than 430 days. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

42 ENGINEERING↗
DOE OSTI2013

Real-time catheter tracking for high-dose-rate prostate brachytherapy using an electromagnetic 3D-guidance device: A preliminary performance study

Purpose: In order to increase the accuracy and speed of catheter reconstruction in a high-dose-rate (HDR) prostate implant procedure, an automatic tracking system has been developed using an electromagnetic (EM) device (trakSTAR, Ascension Technology, VT). The performance of the system, including the accuracy and noise level with various tracking parameters and conditions, were investigated. Methods: A direct current (dc) EM transmitter (midrange model) and a sensor with diameter of 1.3 mm (Model 130) were used in the trakSTAR system for tracking catheter position during HDR prostate brachytherapy. Localization accuracy was assessed under both static and dynamic analyses conditions. For the static analysis, a calibration phantom was used to investigate error dependency on operating room (OR) table height (bottom vs midposition vs top), sensor position (distal tip of catheter vs connector end of catheter), direction [left-right (LR) vs anterior-posterior (AP) vs superior-inferior (SI)], sampling frequency (40 vs 80 vs 120 Hz), and interference from OR equipment (present vs absent). The mean and standard deviation of the localization offset in each direction and the corresponding error vectors were calculated. For dynamic analysis, the paths of five straight catheters were tracked to study the effects of directions, sampling frequency, and interference of EM field. Statistical analysis was conducted to compare the results in different configurations. Results: When interference was present in the static analysis, the error vectors were significantly higher at the top table position (3.3 {+-} 1.3 vs 1.8 {+-} 0.9 mm at bottom and 1.7 {+-} 1.0 mm at middle, p < 0.001), at catheter end position (3.1 {+-} 1.1 vs 1.4 {+-} 0.7 mm at the tip position, p < 0.001), and at 40 Hz sampling frequency (2.6 {+-} 1.1 vs 2.4 {+-} 1.5 mm at 80 Hz and 1.8 {+-} 1.1 at 160 Hz, p < 0.001). So did the mean offset errors in the LR direction (-1.7 {+-} 1.4 vs 0.4 {+-} 0.5 mm in AP and 0.8 {+-} 0.8 mm in SI directions, p < 0.001). The error vectors were significantly higher with surrounding interference (2.2 {+-} 1.3 mm) vs without interference (1.0 {+-} 0.7 mm, p < 0.001). An accuracy of 1.6 {+-} 0.2 mm can be reached when using optimum configuration (160 Hz at middle table position). When interference was present in the dynamic tracking, the mean tracking errors in LR direction (1.4 {+-} 0.5 mm) was significantly higher than that in AP direction (0.3 {+-} 0.2 mm, p < 0.001). So did the mean vector errors at 40 Hz (2.1 {+-} 0.2 mm vs 1.3 {+-} 0.2 mm at 80 Hz and 0.9 {+-} 0.2 mm at 160 Hz, p < 0.05). However, when interference was absent, they were comparable in the both directions and at all sampling frequencies. An accuracy of 0.9 {+-} 0.2 mm was obtained for the dynamic tracking when using optimum configuration. Conclusions: The performance of an EM tracking system depends highly on the system configuration and surrounding environment. The accuracy of EM tracking for catheter reconstruction in a prostate HDR brachytherapy procedure can be improved by reducing interference from surrounding equipment, decreasing distance from transmitter to tracking area, and choosing appropriated sampling frequency. A calibration scheme is needed to further reduce the tracking error when the interference is high.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

High Speed Data Acquisition for Real Time Feedback in a Light Duty Engine Combustion-Mode Switching Application

The paper describes the integration of a high-speed data acquisition and diagnostics controller used in an advanced engine platform. The controller enables ultra-low emissions and new benchmarks of engine efficiency while running a Gasoline Compression Ignition (GCI) cycle on a 2.2L, 4-cylinder engine. The system enables real-time combustion feedback and vibration analysis in engines. The paper focuses on: (1) the development of an interpolative sampling algorithm for transposition of time acquired data to the crank angle domain using a production crank sensor (60-2 tooth wheel); (2) the control unit, high-speed data acquisition, communication rates between the dedicated data acquisition and base controller to ensure cycle-to-cycle feedback; and, (3) validation exercises using cylinder pressure measurements. Here, the study shows how the algorithm resolves cylinder pressure information over an engine cycle, validating its robustness across acquisition rates of 50 and 200 kHz, with crank angle resolutions of 0.5° and 0.1°. Results show that the 50 kHz, 0.5° hardware yield combustion phasing and torque estimates within 0.1° and 1% torque of those attained with the 200 kHz, 0.1° hardware. Finally, study shows the dedicated controller and communication speeds allow for next-cycle fuel injection correction for speeds above 5000 rpm.

42 ENGINEERING↗
DOE OSTI2015

Wireless Sensor Node Power Profiling Based on IEEE 802.11 and IEEE 802.15.4 Communication Protocols. Modeling and Simulation

Most wireless sensor network (comprising of thousands of WSNs) applications require operation over extended periods of time beginning with their deployment. Network lifetime is extremely critical for most applications and is one of the limiting factors for energy-constrained networks. Based on applications, there are wide ranges of different energy sources suitable for powering WSNs. A battery is traditionally used to power WSNs. The deployed WSN is required to last for long time. Due to finite amount of energy present in batteries, it is not feasible to replace batteries. Recently there has been a new surge in the area of energy harvesting were ambient energy in the environment can be utilized to prolong the lifetime of WSNs. Some of the sources of ambient energies are solar power, thermal gradient, human motion and body heat, vibrations, and ambient RF energy. The design and development of TEGs to power WSNs that would remain active for a long period of time requires comprehensive understanding of WSN operational. This motivates the research in modeling the lifetime, i.e., power consumption, of a WSN by taking into consideration various node and network level activities. A WSN must perform three essential tasks: sense events, perform quick local information processing of sensed events, and wirelessly exchange locally processed data with the base station or with other WSNs in the network. Each task has a power cost per unit tine and an additional cost when switching between tasks. There are number of other considerations that must also be taken into account when computing the power consumption associated with each task. The considerations includes: number of events occurring in a fixed active time period and the duration of each event, event-information processing time, total communication time, number of retransmission, etc. Additionally, at the network level the communication of information data packets between WSNs involves collisions, latency, and retransmission, which result in unanticipated power losses. This report focuses rigorous stochastic modeling of power demand for a schedule-driven WSN utilizing Institute of Electrical and Electronics Engineers 802.11 and 802.15.4 communication protocols. The model captures the generic operation of a schedule-driven WSN when an external event occurs, i.e., sensing, following by processing, and followed by communication. The report will present development of an expression to compute the expected energy consumption per operational cycle of a schedule-driven WSN by taking into consideration the node level activities, i.e., sensing and processing, and the network level activities, i.e., channel access, packet collision, retransmission attempts, and transmission of a data packet.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Validation of an inverse model of zone air heat balance

Our work introduces the validation method and results of an inverse model of zone air heat balance. The inverse model, implemented in EnergyPlus and published in a previous article [1], calculates highly uncertain model parameters such as internal thermal mass and infiltration airflow by inversely solving the zone air heat balance equation using the easy-to-measure zone air temperature data. The paper provides technical details of validation from the experiments using LBNL's Facility for Low Energy eXperiment in Buildings (FLEXLAB) that measures zone air temperature under the controlled experiment of two levels of internal mass and four levels of infiltration airflow. The simulation results of the zone infiltration airflow and internal thermal mass from the inverse model agree well with the measured data from the FLEXLAB experiments. The validated inverse model in EnergyPlus can be utilized to enhance the energy modeling of existing buildings that enables energy performance assessments for energy efficiency improvements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Whole building retrofit using vacuum insulation panels and energy performance analysis

Vacuum insulation panels (VIPs), due to their high thermal performance, provide an attractive alternative to traditional building insulation materials, especially as an option for retrofitting old, poorly insulated buildings. This article describes the complete retrofit of all exterior walls of a single-story building in a cold climate using VIPs. A recently-developed low-cost VIP, called modified atmosphere insulation (MAI), was used in this study. Two buildings of near-identical construction were studied, with one remaining unaltered and serving as the baseline while the other served as the retrofit building. The VIPs or MAI panels proved to be a feasible and durable option for retrofitting building envelopes. Thermal performance of both buildings was analyzed using in-situ temperature and heat flow sensors. Numerical models of the two buildings were created, benchmarked using experimental data and used for predictions of annual energy savings due to the addition of MAI panels to the exterior walls. The models predicted significant reduction in the annual heating energy consumption in the retrofitted building compared to the baseline building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A generalized machine learning workflow to visualize mechanical discontinuity

Accurate detection and mapping of mechanical discontinuity in materials has widespread industrial and research applications. Herein, we developed a generalized machine-learning framework for visualizing single mechanical discontinuity embedded in material of any composition, velocity, density, porosity, and size with limited data. The proposed visualization of discontinuity requires accurate estimations of the length, location, and orientation of the embedded discontinuity by processing multipoint wave-transmission measurements. k-Wave simulator is used to create a large dataset of elastic waveforms recorded during multi-point wave-transmission measurements through materials containing single mechanical discontinuity. k-Wave simulator considers the wave attenuation, dispersion, and mode conversion in wave motion. Discrete wavelet transform (DWT) and statistical feature extraction are essential for data preprocessing prior to the data-driven model development. DWT also minimizes the effect of noise. Using hyper-parameter tuning and cross validation, gradient boosting regression can visualize the mechanical discontinuity with an accuracy of 0.85, in terms of coefficient of determination. A double-layered neural network-based regression has better performance with an accuracy of 0.95. Use of convolutional neural network converts the predictive task from a waveform processing to an image processing problem. Convolutional neural network achieved a generalization performance of 0.91. The proposed generalized workflow requires robust simulation of wave propagation, signal processing, feature engineering, and model evaluation. Sensors closest to the source and those located opposite the source are the most significant for the desired visualization. Notably, the sensors closest to the source capture the non-linear associations, whereas the sensor on the border opposite to the source capture the linear associations between the measured waveforms and the properties of the mechanical discontinuity.

42 ENGINEERING↗
DOE OSTI2020

Coherent electrical control of a single high-spin nucleus in silicon

Nuclear spins are highly coherent quantum objects. In large ensembles, their control and detection via magnetic resonance is widely exploited, for example, in chemistry, medicine, materials science and mining. Nuclear spins also featured in early proposals for solid-state quantum computers and demonstrations of quantum search and factoring algorithms. Scaling up such concepts requires controlling individual nuclei, which can be detected when coupled to an electron. However, the need to address the nuclei via oscillating magnetic fields complicates their integration in multi-spin nanoscale devices, because the field cannot be localized or screened. Control via electric fields would resolve this problem, but previous methods relied on transducing electric signals into magnetic fields via the electron–nuclear hyperfine interaction, which severely affects nuclear coherence. In this work, we demonstrate the coherent quantum control of a single 123 Sb (spin-7/2) nucleus using localized electric fields produced within a silicon nanoelectronic device. The method exploits an idea proposed in 1961 but not previously realized experimentally with a single nucleus. Our results are quantitatively supported by a microscopic theoretical model that reveals how the purely electrical modulation of the nuclear electric quadrupole interaction results in coherent nuclear spin transitions that are uniquely addressable owing to lattice strain. The spin dephasing time, 0.1 seconds, is orders of magnitude longer than those obtained by methods that require a coupled electron spin to achieve electrical driving. These results show that high-spin quadrupolar nuclei could be deployed as chaotic models, strain sensors and hybrid spin-mechanical quantum systems using all-electrical controls. Integrating electrically controllable nuclei with quantum dots could pave the way to scalable, nuclear- and electron-spin-based quantum computers in silicon that operate without the need for oscillating magnetic fields.

42 ENGINEERING↗