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DOE OSTI2022

Nonlocal subpicosecond delay metrology using spectral quantum interference

Precise knowledge of position and timing information is critical to support elementary protocols such as entanglement swapping on quantum networks. While approaches have been devised to use quantum light for such metrology, they largely rely on time-of-flight (ToF) measurements with single-photon detectors and, therefore, are limited to picosecond-scale resolution owing to detector jitter. In this work, we demonstrate an approach to distributed sensing that leverages phase modulation to map changes in the spectral phase to coincidence probability, thereby overcoming the limits imposed by single-photon detection. By extracting information about the joint biphoton phase, we measure a generalized delay—the difference in signal–idler arrival, relative to local radio frequency (RF) phase modulation. For nonlocal ranging measurements, we achieve (2$σ$) precision of ±0.04 ps and for measurements of the relative RF phase, (2$σ$) precision of ±0.7°. We complement this fine timing information with ToF data from single-photon time-tagging to demonstrate absolute measurement of time delay. By relying on off-the-shelf telecommunications equipment and standard quantum resources, this approach has the potential to reduce overhead in practical quantum networks.

42 ENGINEERING↗

DOE OSTI2016

Simulating Fragmentation and Fluid-Induced Fracture in Disordered Media Using Random Finite-Element Meshes

Fracture and fragmentation are extremely nonlinear multiscale processes in which microscale damage mechanisms emerge at the macroscale as new fracture surfaces. Numerous numerical methods have been developed for simulating fracture initiation, propagation, and coalescence. In this paper, we present a computational approach for modeling pervasive fracture in quasi-brittle materials based on random close-packed Voronoi tessellations. Each Voronoi cell is formulated as a polyhedral finite element containing an arbitrary number of vertices and faces. Fracture surfaces are allowed to nucleate only at the intercell faces. Cohesive softening tractions are applied to new fracture surfaces in order to model the energy dissipated during fracture growth. The randomly seeded Voronoi cells provide a regularized discrete random network for representing fracture surfaces. The potential crack paths within the random network are viewed as instances of realizable crack paths within the continuum material. Mesh convergence of fracture simulations is viewed in a weak, or distributional, sense. The explicit facet representation of fractures within this approach is advantageous for modeling contact on new fracture surfaces and fluid flow within the evolving fracture network. Finally, applications of interest include fracture and fragmentation in quasi-brittle materials and geomechanical applications such as hydraulic fracturing, engineered geothermal systems, compressed-air energy storage, and carbon sequestration.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2012

Recovery Act: A Measurement -- Management Technology for Improving Energy Efficiency in Data Centers and Telecommunication Facilities (Final Technical Report)

Data center (DC) electricity use is increasing at an annual rate of over 20% and presents a concern for the Information Technology (IT) industry, governments, and the society. A large fraction of the energy use is consumed by the compressor cooling to maintain the recommended operating conditions for IT equipment. The most common way to improve the DC efficiency is achieved by optimally provisioning the cooling power to match the global heat dissipation in the DC. However, at a more granular level, the large range of heat densities of today's IT equipment makes the task of provisioning cooling power optimized to the level of individual computer room air conditioning (CRAC) units much more challenging. Distributed sensing within a DC enables the development of new strategies to improve energy efficiency, such as hot spot elimination through targeted cooling, matching power consumption at rack level with workload schedule, and minimizing power losses. The scope of Measurement and Management Technologies (MMT) is to develop a software tool and the underlying sensing technology to provide critical decision support and control for DC and telecommunication facilities (TF) operations. A key aspect of MMT technology is integration of modeling tools to understand how changes in one operational parameter affect the overall DC response. It is demonstrated that reduced ordered models for DC can generate, in less than 2 seconds computational time, a three dimensional thermal model in a 50 kft 2 DC. This rapid modeling enables real time visualization of the DC conditions and enables "0what if" scenarios simulations to characterize response to "disturbances". One such example is thermal zone modeling that matches the cooling power to the heat generated at a local level by identifying DC zones cooled by a specific CRAC. Turning off a CRAC unit can be simulated to understand how the other CRAC utilization changes and how server temperature responds. Several new sensing technologies were added to the existing MMT platform: (1) air contamination (corrosion) sensors, (2) power monitoring, and (3) a wireless environmental sensing network. All three technologies are built on cost effective sensing solutions that increase the density of sensing points and enable high resolution mapping of DCs. The wireless sensing solution enables Air Conditioning Unit (ACU) control while the corrosion sensor enables air side economization and can quantify the risk of IT equipment failure due to air contamination. Validation data for six test sites demonstrate that leveraging MMT energy efficiency solutions combined with industry best practices results in an average of 20% reduction in cooling energy, without major infrastructure upgrades. As an illustration of the unique MMT capabilities, a data center infrastructure efficiency (DCIE) of 87% (industry best operation) was achieved. The technology is commercialized through IBM System and Technology Lab Services that offers MMT as a solution to improve DC energy efficiency. Estimation indicates that deploying MMT in existing DCs can results in an 8 billion kWh savings and projection indicates that constant adoption of MMT can results in obtainable savings of 44 billion kWh in 2035. Negotiations are under way with business partners to commercialize/license the ACU control technology and the new sensor solutions (corrosion and power sensing) to enable third party vendors and developers to leverage the energy efficiency solutions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Additive Manufacturing of Sensors and Components for Non-Destructive Evaluation Applications

Additively manufactured machine components were designed for use in non-destructive evaluations. Additive manufacturing (3D printing) enables rapid production of simple or complex objects at a low cost for use in many fields of research and industry. 3D printed components were used to optimize an eddy current array probe to inspect various complex shaped objects, such as gears. Preliminary eddy current inspections were conducted to test the functionality and compatibility of the 3D printed components to the array probe and existing system. These were done by wrapping replica 3D printed gears with aluminum foil. The results were as expected, rough, uneven surface of the aluminum foil. Calibration scans were also executed to enable proper measurement of defect size in metal structures. For use in waveguide-based distributive sensing technologies, additively manufactured custom waveguides were designed for use in liquid environments to collect pressure and flow data. Waveguides were designed with membranes, thin sections of the walls, which would be pressed inward due to fluid pressure. Waveguide models continue to be developed and revised for most functional utility in liquid environments.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Distributed Wireless Antenna Sensors for Boiler Condition Monitoring

Monitoring the operational conditions of coal-fired boilers is an important task that could bring tremendous benefits, including in-situ process control, real-time health assessment of structural components, improved heat transfer efficiency, reduced downtime, etc. Moreover, in-situ distributed sensing of the boiler conditions would provide large scale in-situ measurement data that will help us gain fundamental understandings of the combustion and heat transfer processes as well as enable the developments of new simulation tools, which could eventually lead to better design and more efficient operation of the boilers. The objectives of this research were to (a) develop wireless passive antenna sensors without electronics; (b) demonstrate multi-modality sensing using a signal antenna sensor; and (c) fabricate the antenna sensor from high-temperature materials. In this project, we have demonstrated that an antenna sensor or sensor array without any electronics can be wirelessly interrogated from a distance. In addition, a low-cost compact wireless sensor interrogator was developed for dynamic interrogation of the passive antenna sensor. We validated that a dual-frequency antenna sensor is capable of simultaneous strain and temperature measurements or temperature and ash accumulation measurements; all parameters are relevant to boiler condition monitoring. By measuring the temperature and ash accumulation height simultaneously, the dielectric constant of the ash as well as its temperature dependency can also be characterized. This capability could lead to potential applications of the antenna sensor for combustion process monitoring based on the ash composition. We also investigated different techniques of fabricating the antenna sensor using high-temperature materials such as alumina substrate and platinum paste and characterized the thermal response of the antenna sensor. A linear relationship between the antenna resonant frequency and the temperature change was validated.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

VOLTTRON Modular Framework: Enabling flexible and scalable deployment solutions

VOLTTRON ™ is an open-source platform for distributed sensing and control. The platform provides services for collecting and storing data from buildings and devices and provides an environment for developing applications which interact with that data. The platform allows developers to build out their use cases by utilizing these frameworks and integrating new capabilities. To simplify the deployment of systems built on VOLTTRON, a new way of organizing the codebase is being explored. This document details these efforts through a new code repository layout for the VOLTTRON platform and services, and how this new layout provides targeted deployments using standard python deployment packages (wheels). In addition, this paper will discuss the development of third-party agents and how they can be integrated within the VOLTTRON ecosystem. Finally, we will discuss core platform development and direction for the modularized version of VOLTTRON.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Development of Optical Fiber-Based Sensors for Nuclear Microreactor Structural Health Monitoring

This report provides an experimental assessment of two different optical fiber–based acoustic sensors that are being investigated for application in nuclear microreactors to enhance structural health monitoring capabilities. Optical fibers are resilient in high-temperature and high-radiation environments, have a small sensor footprint, are immune to electromagnetic interference, and are capable of spatially distributed sensing. The two sensors investigated here are (1) Fabry–Pérot Cavities (FPCs) between two copper-coated fibers, embedded in nickel capillary tubes and (2) type-I fiber Bragg grating (FBG) arrays contained within metal capillary tubes. These sensors can be interrogated using low-coherence interferometry or swept wavelength interferometry, respectively, to measure the resonant frequencies of the components or systems to which these sensors are bonded. The FPC developed herein has been subjected to temperatures up to nearly 800°C while tack-welded to a tubular test specimen. Even at the highest temperatures, the measured resonant frequencies compared well with those obtained using an accelerometer that was bonded to an unheated portion of the specimen. The FBG array was tested in multiple bonding configurations to a tubular test specimen, all at room temperature, with the understanding that high temperature (i.e., type II) FBGs could be used to obtain similar data at high temperatures; the FBG array data were validated with noncontact laser vibrometry, which is being used at Los Alamos National Laboratory to relate acoustic signatures to component stresses and/or structural defects. The goal of this work is to identify the most promising techniques that are also compatible with operation in a microreactor environment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Integrated Boiler Management through Advanced Condition Monitoring and Component Assessment

The objective of this project, supported by the U.S. Department of Energy (USDOE) under DEFE0031683, is to develop, demonstrate, and support technology transfer of an integrated boiler management system inclusive of distributed sensing and near real-time damage assessment tools to provide for the first highly accurate condition monitoring system for boiler components.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Persistent DynAMICS

Persistent DynAMICS is a lightweight software platform that enables distributed sensing systems to operate as a unified, responsive network. It integrates with existing sensors, data systems, and processing tools as an overlay, without requiring hardware replacement or increasing user burden. As data is collected, the system identifies situations that require additional attention and directs selected sensors to gather more information. For example, if a sensor detects an unusual condition along a pipeline, the system can task nearby sensors or different sensing modalities to confirm the event and focus data collection where it is needed. To support this, the platform forms temporary groups of sensors that work together to address specific objectives. Once complete, these groups are dissolved and resources are reassigned as needed. Communication is handled through an integrated messaging framework with client and server components, enabling reliable operation and data continuity even in low-bandwidth or intermittent connectivity environments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Initial Feasibility Assessment and Broader Strategy Development for Fiber Integration via Advanced Manufacturing

Structural health monitoring is critical for ensuring the operational safety and cost-competitiveness of the developing advanced reactor designs. The extreme operational envelopes of these advanced architectures, having operating temperatures ranging 400°C–1,000°C and heightened displacement damage doses, render conventional commercially available piezoelectric transducers and resistive strain gauges unviable. Optical fiber sensors present an attractive solution for advanced radiation-hardened instrumentation due to their high thermal stability and distributed sensing capabilities. However, their deployment in embedded applications can be hindered by the severe thermomechanical strain driven by the coefficient of thermal expansion mismatch between fused silica glass and structural metal alloys like stainless steel (e.g., SS316L).

36 MATERIALS SCIENCE↗

DOE OSTI2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗

DOE OSTI2015

Geographic Visualization of Power-Grid Dynamics

The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.

Sukumar, Sreenivas R.↗

DOE OSTI2022

System and method for monitoring a reactor system using optical fiber based sensors

A method of monitoring operation of a reactor system includes causing a chemical reaction to occur within an assembly of the reactor system, and measuring a chemical composition of one or more reactants of the chemical reaction with spatial resolution at a plurality of points along a path within the assembly using a sensor system structured to implement distributed sensing. The sensor system includes an optical fiber sensing member provided at least partially within the assembly, wherein the optical fiber sensing member comprises a functionalized optical fiber based sensor device structured to exhibit a change in one or more optical properties in response to changes in the chemical composition of the one or more reactants.

Chen, Peng K.↗

DOE OSTI2017

Neutron-Gamma flux and Dose calculations in a Pressurized Water Reactor (PWR)

The Institute of Radiological Protection and Nuclear Safety (IRSN) acts as technical support to the French nuclear safety authorities. In this context, one of its missions is to improve nuclear safety through the enhancement of knowledge regarding operating nuclear power reactors. The issues concerning the aging and the characterisation of the reactor vessel require knowledge of the neutron and gamma radiation environment on the vessel and beyond. Since few years, ENEA (Energia Nucleare e Energie Alternative, i.e. Nuclear Energy and Alternative Energy agency) and IRSN collaborate on Monte-Carlo simulations and Variance Reduction Techniques (VRT), which are used to determine neutron and gamma spectra in and out of the core. Additionally, IRSN participates in the DISCOMS project, which stands for 'Distributed Sensing for Corium Monitoring and Safety', aiming at examining the status of the third barrier of confinement, in order to define possible mitigation strategies in case of a severe accident, namely: i) reactor pressure vessel breakthrough and corium relocation outside the vessel, ii) reactor pit concrete erosion and iii) corium cooling. One of the IRSN tasks in the frame of the DISCOMS project is to provide the radiation level in terms of neutron and gamma doses and flux energy spectra at various locations. This paper summarizes the study performed on the radiation transport in the Tihange-I Belgian nuclear reactor and contributes to several issues requiring the knowledge of the radiation environment in and outside the reactor vessel. This paper gives an overview of the work presented at the ICRS-13 and RPSD-2016 conference (for more details see the proceedings paper)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

High-Fluence Active Irradiation and Combined Effects Testing of Sapphire Optical Fiber Distributed Temperature Sensors - ASI Project Summary

The goal of this work is to investigate the performance of sapphire optical fiber temperature sensors and develop clad sapphire optical fibers for in-pile instrumentation. This work tests the distributed sensing performance of sapphire sensors by using optical backscatter reflectometry methods under combined radiation/temperature effects and high fluence. A series of irradiations will be completed to evaluate the effect of irradiation on sapphire optical fiber temperature sensors and to determine an operational limit for the sensors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2010

Imaging Fluid Flow in Geothermal Wells Using Distributed Thermal Perturbation Sensing

The objective of Task 2 is to develop a numerical method for the efficient and accurate analysis of distributed thermal perturbation sensing (DTPS) data for (1) imaging flow profiles and (2) in situ determination of thermal conductivities and heat fluxes. Numerical forward and inverse modeling is employed to: (1) Examine heat and fluid flow processes near a geothermal well under heating and cooling conditions; (2) Demonstrate ability to interpret DTPS thermal profiles with acceptable estimation uncertainty using inverse modeling of synthetic temperature data; and (3) Develop template model and analysis procedure for the inversion of temperature data collected during a thermal perturbation test using fiber-optic distributed temperature sensors. This status report summarizes initial model developments and analyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Integration of Simulated and Real Distributed Acoustic Sensor Measurements to Develop AI Enhanced Intelligent Sensing Operations

Distributed acoustic sensors (DAS) have shown remarkable success in monitoring critical civil, energy and transportation assets over long distances and under harsh environmental conditions. Integration of artificial intelligence (AI) technologies with DAS can extend their operational capabilities from conventional tasks (e.g., vibration frequency detection) to more advanced intelligent tasks like anomaly detection. However, these AI technologies often require large labeled/ annotated DAS measurements datasets of the assets in both normal and anomalous operating conditions. This data acquisition task can be both time consuming and costly. This work develops a generative adversarial network based unsupervised domain adaptation framework to build intelligent DAS operational capabilities.

Venketeswaran, Abhishek↗