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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 OSTI2021

HFTS-2 Completions Design and State-of-the-Art Diagnostics Results

Various completion schemes were tested as part of the Hydraulic Fracture Test Site-2 (HFTS-2) project. The wells were instrumented with permanent fiber optic (FO) cable, and unique near-wellbore and far-field region surveys were acquired to evaluate spatial and temporal hydraulic fracture characteristics. The state-of-the-art diagnostics included substantial monitoring of both the well stimulation and longer-term production performance. The objective was to evaluate and improve stimulation distribution effectiveness (SDE) for different completion designs based on the diagnostics results. A hydraulic fracturing (HF) profile (i.e., proppant/fluid allocation among clusters) was obtained using near-wellbore Distributed Acoustic Sensing (DAS) data acquired during stimulation. Statistical analysis provided a quantitative assessment of SDE for the different completion designs. A novel workflow was developed to assess time-lapse fracture property changes at the cluster and stage levels based on Distributed Strain Sensing (DSS) data acquired during the production phase. These time-lapse fracture property changes were compared with the HF profile. Based on the statistical analysis, Rate Per Cluster (RPC) during proppant slurry placement appears to be a primary completion design variable, rather than the typical Rate Per Perf (RPP). If RPC was not maintained at a certain level, the likelihood of uneven distribution increased dramatically. The stage configurations that created low RPC while maintaining high RPP did not show improved SDE. The strain change results based on DSS data during the production phase indicated near-wellbore fracture property changes (e.g., aperture changes during well shut-in and flow periods) and aligned well with near-wellbore DAS signals acquired during stimulation. More importantly, fracture property changes based on DSS data acquired during two tests over a 7-month period show high consistency and good alignment with the near-wellbore HF profile. This workflow quantitatively evaluates SDE for different completion designs using diagnostic results and could help optimize completion strategy for future development projects. Here, the analysis and interpretation of results demonstrate the technical feasibility of using permanent fiber optic cable for stimulation and production monitoring and indic

58 GEOSCIENCES↗
DOE OSTI2024

Simulation Analysis of Mode Hopping Impacts on OFDR Sensing Performance

This article examines the impacts of mode hopping on the sensing performance of optical frequency domain reflectometry (OFDR) and explores the potential for developing economical OFDR interrogators employing low-cost distributed feedback (DFB) lasers. By conducting numerical simulations, this study reveals that mode hopping has minimal effects on distance sensing measurements in free space due to the limited duration of beat interference signal at the incorrect frequency within the coherence length. Additionally, the simulations indicate that mode hopping only slightly affects the distributed strain sensing of OFDR, resulting in an error range of less than ±1µε when 100µε is applied to the sensing fiber. These findings highlight the potential of using low-cost DFB lasers with a 1-nm wavelength sweep range and a 1-MHz linewidth as tunable laser sources in OFDR while maintaining reliable and accurate sensing performance.

Wang, Qirui (ORCID:0000000336532984)↗
DOE OSTI2021

Phase Demodulation by Frequency Chirping in Coherence Microwave Photonic Interferometry

This paper presents a signal processing method to demodulate the optical interference phase of cascaded individual optical fiber intrinsic Fabry-Perot interferometric (IFPI) sensors in a coherent microwave-photonic interferometry (CMPI) distributed sensing system. The new method utilizes the chirp effect of electro-optic modulator (EOM) to create a quasi-quadrature optical interference phase shift between two adjacent pulses which correspond to two adjacent reflection points in the time domain. The phase shift can be controlled by adjusting the bias voltage that is applied to the EOM. The interference phase is calculated by elliptically fitting the phase shift. The interference phase change is proportional to the optical path difference (OPD) change of the interferometer, and the sign can be used to differentiate the increase or decrease of the OPD. The method is demonstrated for distributed strain sensing, showing good linearity, high resolution and large dynamic range.

42 ENGINEERING↗
DOE OSTI2025

Utah FORGE: 16B(78)-32 RFS DSS Strain Change Rate vs. Depth During 16A(78)-32 Stimulation

This dataset contains strain change rate versus depth data acquired using a Rayleigh frequency shift (RFS) distributed strain sensing (DSS) system during hydraulic stimulation of well 16A(78)-32 at the Utah FORGE site in April 2024. The data were collected from an optical fiber installed in the annulus of production well 16B(78)-32, approximately 300 feet from the injection well. The dataset includes tabulated strain data and an explanation of the methodology used to generate the frac log, which integrates strain change rate signals over selected time windows to identify fracture events.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Pilot-Scale Validation of Distributed Optical Fiber Sensors for Underground Pipeline Monitoring

Distributed fiber optic sensing is a cutting-edge technology that has found extensive applications in the monitoring of Ensuring the safety, integrity, and operational efficiency of underground product pipelines is vital for maintaining the nation’s critical infrastructure. Monitoring parameters such as hoop strain, pressure, and acoustic vibrations is key to detecting potential leaks, intrusions, or structural issues. Distributed optical fiber sensor (DOFS) systems provide a compelling solution for continuous, real-time monitoring over long distances. This paper details the development and pilot-scale implementation of DOFS systems for underground pipeline monitoring, evolving from a proof-of-concept stage. Multiple custom-designed DOFS interrogator units—such as optical frequency-domain reflectometry (OFDR), Brillouin optical time-domain analysis (BOTDA), and multimodal interferometer-based fiber acoustic sensors—were employed to measure key parameters like hoop strain, pressure, and acoustic vibrations. The underground product pipeline's outer diameter is 30 inches, the wall thickness is 1.28 inches, and the 3-foot depth. The fiber deployment strategies, and sensing data acquisition methods for these systems are discussed. The results demonstrate the effectiveness of DOFS in detecting hoop strain, temperature changes, and acoustic vibrations, showcasing their potential for real-time monitoring and enhancing pipeline safety.

distributed fiber sensing↗
DOE OSTI2024

Utah FORGE: Neubrex Well 16B(78)-32 Fiber Optics Reports - Stimulation and Circulation, 2024

This zip file contains reports discussing the use of fiber optics during well 16B(78)-32 stimulation and circulation tests in the summer of 2024. The reports cover the collection of strain rate and temperature change data during these well events. Theory, methods, and initial data visualizations are included in the reports, highlighting the value of these data types.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: Well 16A(78)-32 Hydraulic Fracturing Stage 8 Crosswell Strain FDI and Microseismic Presentations - April 2024

This is a pair of PowerPoint presentations from Neubrex Energy Services (US), LLC. The presentations review work done in April 2024 on crosswell strain fracture driven interactions (FDI) and microseismic event monitoring during hydraulic fracturing in stage 8 of Utah FORGE well 16A(78)-32. Well 16B(78)-32 was the monitoring well and was where the data for these presentations were collected.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

PW2 Pumping: March 18 thru March 22, 2020

Processed Coherence-length-gated Microwave Photonics Interferometry (CMPI) distributed vertical strain on March 18 through March 22, 2020 at the hydromechanical test facility located at the Clemson University Simpson Station research facility in Central, South Carolina, USA. This includes ambient data in addition to a pumping test performed between 14:31-20:31 EST on 3/22/2020 from Pumping Well 2 (PW2). These data are from a strain ribbon that was deployed in the vadose zone at approximately 34.670130°N, -82.729524°E from the ground surface to a depth of 8m in saprolite containing weak reflectors pairs were placed every 0.85 m along the fiber. Each weak reflector pair forms a 15 cm cavity strain meter. Strain unit: meters/meter (strain). Sampling rate 0.1 Hz. Each column corresponds to the strain data taken at a depth d from the ground surface. c1: d = 1.00m c2: d = 1.85m c3: d = 2.70m c4: d = 3.55m (large demodulation error) c5: d = 4.40m c6: d = 5.25m c7: d = 6.10m (large demodulation error) c8: d = 6.95m

Distributed Strain Sensing↗
DOE OSTI2025

Monitoring strain evolution in water-sand systems using distributed acoustic sensing for geohazard early warning

Rainfall-driven hazards such as landslides, debris flows, and earthen dam failures often arise when water changes the internal strain within sand. This study evaluates the ability of distributed acoustic sensing to monitor these strain changes in real time. We embed a fiber-optic cable in a sand-filled glass cylinder and run controlled dry- and wet-sand experiments to measure how strain develops as water infiltrates, saturates, and drains from the sand. The sensing system detects uneven water movement in dry sand and enables millimeter-scale estimates of infiltration rates, and in wet sand it tracks rising water levels, delayed strain peaks after saturation, and abrupt strain shifts during drainage. These results show that fiber-optic sensing captures subtle strain evolution throughout the full water-sand interaction cycle. The study demonstrates that fiber-optic sensing offers promising potential for real-time and cost-effective monitoring and early warning of rainfall-induced geohazards.

58 GEOSCIENCES↗
DOE OSTI2022

Improving OFDR Distributed Fiber Sensing by Fibers With Enhanced Rayleigh Backscattering and Image Processing

This article investigates using optical fibers with enhanced backscattering profiles to improve distributed fiber sensor performance and reduce instrumentation costs. Using a femtosecond (fs) laser direct writing technique, the Rayleigh backscattering profile of a standard telecom fiber was enhanced by more than 40 dB to improve the signal-to-noise ratio (SNR) for optical frequency domain reflectometry (OFDR). The enhanced backscattering signals enable effectively distributed strain measurements using a low-cost tunable laser (TL). Median filtering is applied to denoise cross correlation results to further improve measurement outcomes. Results presented in this article show that a TL with a 1-nm tuning range, which is far less than the tuning range used in commercial OFDR interrogators, can perform effectively distributed strain measurements using sensing fibers with enhanced backscattering profiles. The sensing fiber with over 40-dB backscattering enhancement achieved 4.8-cm spatial resolution in strain measurements with a root mean square accuracy of less than 2.70 με when 10–50 με were exerted to the sensing fiber. In conclusion, results presented in this article reveal both the potential and limitations of sensing fibers with enhanced backscattering for OFDR-based distributed fiber sensors.

42 ENGINEERING↗
DOE OSTI2023

Characterization of Aquifer Poroelastic Response to Impulse and Oscillatory Well Pressure Using Distributed Acoustic Sensing

Abstract The storage of fluids in the subsurface is critical for a broad spectrum of applications including managed aquifer recharge, storage of liquefied carbon dioxide and hydrogen, geothermal heat extraction and exploitation of hydrocarbon. It is surprising then, that there has been relatively little measurement of the vertical distribution of poroelastic storage in geologic formations as compared with permeability. We present experiments in which fluid was injected into an important regional aquifer and the depth‐dependent strain response measured using fiber optic distributed acoustic sensing. The formation expansion and contraction in response to fluid injection were several 100 nanostrain. Strain, and the implied storage distribution, was highly localized in specific strata and demonstrated complex, hydromechanical behavior. This new window into fluid‐geomechanical coupling undermines some typically use models and observations currently in practice, but provides potential for complete representation and prediction of fluid storage in the subsurface.

58 GEOSCIENCES↗
DOE OSTI2025

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗
DOE OSTI2026

Neural Network‐Based Methods for Ocean Surface Wave Measurement Using Submarine Distributed Acoustic Sensing (DAS)

Two new data-driven models for estimating ocean surface waves from distributed acoustic sensing (DAS) submarine cable strain rate are developed using supervised machine learning on a 10-day data set collected offshore of Oliktok Point, Alaska. The new models were trained on target data from seafloor pressure moorings at three sites spaced evenly along 27.1 km of cable and were benchmarked against an empirical transfer function method previously used to estimate waves from DAS. A model which uses convolutional neural networks to transform 2-km frequency-wavenumber strain spectra to seafloor pressure spectra outperforms the benchmark in wave height prediction (RMSE of 0.15 vs. 0.41 m) and period prediction (0.29 vs. 0.37 s) when evaluated on a held-out test data set. When applied to a DAS data set collected on the same cable 2 years prior, the CNN-based model maintained similar significant wave height performance (RMSE = 0.23 m) relative to available satellite altimetry data. A two-hidden-layer, fully connected neural network which transforms 1-D strain spectra to seafloor pressure spectra also outperforms the benchmark in wave height prediction (RMSE of 0.19 vs. 0.41 m), but does not generalize as well to the prior data. Regression-based machine learning is useful for estimating waves from DAS data when the pressure-strain relationship varies temporally and spatially across different wave conditions. Models can be applied to DAS data to measure waves with higher spatial resolution and longer temporal coverage than traditional methods, which often measure waves only at a single point.

Davis, Jacob R. [Univ. of Washington, Seattle, WA ↗
DOE OSTI2024

Multi-functional cementitious materials with ultra-high damage tolerance and self-sensing ability

Cementitious materials having high damage tolerance and self-sensing ability are described herein. These materials may replace conventional concrete to serve as a major material component for infrastructure systems with greatly improved resistance to cracking, reinforcement corrosion, and other common deterioration mechanisms under service conditions, and prevents fracture failure under extreme events. These materials can also be used for the repair, retrofitting or rehabilitation of existing concrete structures or infrastructure systems. Furthermore, these materials may offer capacity for distributed and direct sensing of cracking, straining and deterioration with spatially continuous resolution wherever the material is located, without relying on installation of sensors. The present invention relates to multifunctional cementitious structural or infrastructure materials that integrate self-sensing with damage tolerance for improving safety, extending service life, and health monitoring of structures, components, and infrastructure systems.

Li, Mo↗
DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor systems play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond tens of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Optimizing Raman pump and probe wave profiles ensures the robustness of Brillouin scattering signals, effectively countering attenuation-induced losses. Additionally, enhancing weak Brillouin signals by strategically placing EDFAs at optimal fiber locations keeps sensor sensitivity high. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. In summary, this research has shown a holistic exploration of extending BOTDA’s distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗
DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor system play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. Nonetheless, challenges emerge as distances grow due to signal attenuation and noise interference resulting in measurement errors. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond 10’s of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. This approach proves particularly advantageous in BOTDA systems, where accurate measurement of Brillouin scattering signals is paramount for long-range sensing, while concurrently safeguarding high spatial resolutions. In summary, this research has shown a holistic exploration of extending BOTDA's distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗
DOE OSTI2025

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗