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At least 1,117 records · Page 62

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗

Direct reuse of graphite and lithium nickel manganese cobalt oxide (NMC) recovered from ultrafast-laser ablation debris in Li-ion battery electrodes

Here we demonstrate that debris collected from the ultrafast-laser ablation of graphite anodes can be directly reused in a lithium-ion battery with little to no negative effects on electrochemical performance. Further, we show that while post-ablation NMC (LiNi 0.33 Mn 0.33 Co 0.33 O) cathode debris will require additional processing before being incorporated into an electrode, its critical materials (nickel, manganese, and cobalt) are not lost during ablation and can be recovered for recycling. Pre- and post-ablation materials are characterized with a suite of diagnostics, including SEM, TEM, X-ray CT, EDS, and XRD, to study changes in material morphology, composition and crystal structure. Graphite exhibited little to no morphological or compositional changes and a slight annealing of its crystal structure. NMC underwent profound morphological and crystallographic changes, but retained its elemental composition. Finally, post-ablation materials were re-manufactured into electrodes and cycled vs lithium metal. Graphite showed equal or better capacity and Coulombic efficiency compared to pre-ablation electrodes, while the post-ablation NMC exhibited severely reduced electrochemical performance. Furthermore, we discuss the outlook for application of this work to advanced manufacturing lines that produce next-generation, laser-patterned electrodes.

25 ENERGY STORAGE↗

Ion Velocity Characterization of the 12.5-kW Advanced Electric Propulsion System Engineering Hall Thruster

During development testing of the 12.5-kW Advanced Electric Propulsion System engineering unit Hall thruster, which is magnetically shielded, a laser-induced fluorescence test was performed. During this test, a third medium-energy ion population was found near the inner front pole cover in addition to two low-energy counter-streaming ion populations that were found in previous testing. This newly found ion population matched in characteristics with the single population found near the outer front pole cover. The measured characteristics of the medium-energy ions matched the behavior expected of them if they were energized by a plasma wave with magnetized electrons, such as a lower hybrid wave. Comparison of the data from this test to prior tests showed that this engineering thruster had very similar ion characteristics as the precursor laboratory thruster. The acceleration zone was found to move upstream with increasing background pressure, decreasing anode flowrate, and increasing magnetic field strength. For the low-energy ions, the energy of the ions arriving at the inner pole did not vary noticeably with background pressure but did increase with increasing magnetic field strength and decreasing anode flow rate. For the medium-energy ions, the energy of the ions increased with decreasing background pressure, decreasing anode flow rate, and increasing magnetic field strength. Testing at different cathode flow fraction showed that the energy of the low-energy ions from the cathode decreased with increasing cathode flow.

Electric propulsion↗

A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems

Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will eventually lead to a range of HVAC system failures, resulting in excessive energy consumption and maintenance costs. Here, to avoid HVAC malfunctioning, fault detection diagnostic (FDD) is utilized as a common practice. Machine learning methods have lately received considerable interest for FDD analysis of HVAC systems due to their high detection accuracy. Meanwhile, HVAC malfunctions are regarded as rare occurrences, hence normal operating data samples are much more accessible than data samples in faulty and malfunctioning conditions. The dominating frequency of normal operation in HVAC datasets has also led to heavily biased classification algorithms within the literature. Moreover, the focus of previous literature has been on increasing the accuracy of the models which leads to a high number of false positives (misleading alarms) in the system. In order to enhance the performance of diagnostic procedures and fill the mentioned gaps, this study proposes a novel data-driven framework. A bi-level machine learning framework is developed for diagnosing faults in air handling units (AHUs) and rooftop units (RTUs) based on principal component analysis (PCA), time series anomaly detection, and random forest (RF). It is shown that PCA can reduce the dataset dimension with one principal component accounting for 95% of data variance. Also, the random forest could classify the faults with 89% precision for single-zone AHU, 85% precision for RTU, and 79% for multi-zone AHU. By proposing this framework, three persistent challenges are addressed: (I) minimizing false positives; (II) accounting for data imbalance; and (III) normal condition monitoring of equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Low thrust chemical rocket technology

An on-going technology program to improve the performance of low thrust chemical rockets for spacecraft on-board propulsion applications is reviewed. Improved performance and lifetime is sought by the development of new predictive tools to understand the combustion and flow physics, introduction of high temperature materials and improved component designs to optimize performance, and use of higher performance propellants. Improved predictive technology is sought through the comparison of both local and global predictions with experimental data. Predictions are based on both the RPLUS Navier-Stokes code with finite rate kinetics and the JANNAF methodology. Data were obtained with laser-based diagnostics along with global performance measurements. Results indicate that the modeling of the injector and the combustion process needs improvement in these codes and flow visualization with a technique such as 2-D laser induced fluorescence (LIF) would aid in resolving issues of flow symmetry and shear layer combustion processes. High temperature material fabrication processes are under development and small rockets are being designed, fabricated, and tested using these new materials. Rhenium coated with iridium for oxidation protection was produced by the Chemical Vapor Deposition (CVD) process and enabled an 800 K increase in rocket operating temperature. Performance gains with this material in rockets using Earth storable propellants (nitrogen tetroxide and monomethylhydrazine or hydrazine) were obtained through component redesign to eliminate fuel film cooling and its associated combustion inefficiency while managing head end thermal soakback. Material interdiffusion and oxidation characteristics indicated that the requisite lifetimes of tens of hours were available for thruster applications. Rockets were designed, fabricated, and tested with thrusts of 22, 62, 440 and 550 N. Performance improvements of 10 to 20 seconds specific impulse were demonstrated. Higher performance propellants were evaluated: Space storable propellants, including liquid oxygen (LOX) as the oxidizer with nitrogen hydrides or hydrocarbon as fuels. Specifically, a LOX/hydrazine engine was designed, fabricated, and shown to have a 95 pct theoretical c-star which translates into a projected vacuum specific impulse of 345 seconds at an area ratio of 204:1. Further performance improvment can be obtained by the use of LOX/hydrogen propellants, especially for manned spacecraft applications, and specific designs must be developed and advanced through flight qualification.

Schneider, Steven J.↗

Comparison of Expert Vocabulary Usage Patterns Between Mental Health and Nonmental Health Clinicians When Diagnosing Pediatric Anxiety Disorders

Objective: To compare the utilization patterns of expert vocabulary (EVo) in diagnosing pediatric anxiety between mental health and non-mental health clinical notes from electronic health records to understand the role of Evo in informing classification and decision-making in anxiety diagnoses. Study design: We conducted a retrospective study using a cohort less than age 25 from Cincinnati Children's Hospital including 897 685 patients with 61 586 446 notes. We analyzed EVo, collected from mental health clinicians, in both mental and nonmental health notes. We compared classification accuracy using EVo-based patient-level embedding from all clinical notes, mental-health notes, and nonmental health notes for 2 tasks: 1) pre-vs postdiagnosis anxiety patients, and 2) prediagnosis anxiety vs nonanxiety patients. Results: EVo usage was highest in prediagnosis anxiety, lower in nonanxiety, and lowest in post-diagnosis. Classification models using EVo features from all, mental-health, and non-mental health notes showed similar F1 scores for prediagnosis anxiety (0.70 ± 0.2 for 2 categories). For anxiety vs nonanxiety classification, all clinical and nonmental health notes had better F1 scores than mental-health notes (above 0.90 for 3 categories). There was a notable difference in class-wise performance across both tasks. Conclusions: There are significant differences in anxiety EVo use between mental health and nonmental health clinicians. Despite less anxiety-specific terminology, non-mental health notes still captured key aspects of patient presentations, emphasizing the importance of including all clinicians' notes in analysis. EVo's utility for anxiety classification is most effective in prediagnostic phases, suggesting the need for a dedicated diagnostic lexicon and further study before incorporating EVo into classification models.

feature engineering↗

Diagnostic and predictive capabilities of the TCR digital platform

The Transformational Challenge Reactor program is leveraging additive manufacturing technologies to fabricate the nuclear components required to assemble a microreactor core. Compared with traditional manufacturing processes, additive manufacturing allows for direct observation of the interior of the component during manufacturing. This unique capability promises significant possibilities for creating a new paradigm for nuclear component qualification by leveraging in-situ process data. This report describes FY21 efforts to predict material tensile properties based on data collected during the laser powder bed fusion printing process. The primary focus of this report is the test campaign designed to generate the large quantities of training data required to implement artificial intelligence algorithms that can predict these material properties. Preliminary prediction results and a demonstration of the overall data collection, analysis, and visualization pipeline are also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗

GEMINI Case Study

Sandia's GEMINI-Scout Mine Rescue Robot is an unmanned ground vehicle designed to enter potentially hazardous environments to explore, assess, and evaluate dangerous situations first responders may face when conducting a rescue mission. GEMINI is approximately four feet long and two feet tall, which enables the robot to maneuver through small locations on rough terrains caused by earthquakes, fires, or radiological incidents. GEMINI uses track propulsion to climb stairs, travel through gravel and sand pits, pivot in place, and traverse 45-degree climbs with few problems. Furthermore, the vehicle's dual tracked-chassis design allows it to operate in hostile, dark, muddy, high-temperature, and explosive debris-strewn environments, while maintaining efficient ground mobility. The mobility and modularity of the vehicle allow for easy integration of sensors to conduct gas and temperature sensing and offers pan/tilt, zoom color, and thermal camera video streaming capabilities. The vehicle is also able to carry a payload of about 50 pounds of batteries and can handle an additional 200 pounds of payload, whether for additional diagnostics, supplies, or clothing for those trapped in an effected area. GEMINI is remotely operated through a wireless connection and an onboard computer running a customized embedded control application, which directly communicates to all onboard components except for the audio and video systems. When line of sight is not possible, operators use a shockresistant fiber optic cable to ensure continuous functionality of the vehicle. This allows for direct local control of the vehicle, which streams collected data back to the operator for enhanced situational awareness. In addition, the vehicle incorporates safety features such as explosion proof housing to ensure safe electronic operations in hazardous gas or flooded environments; a four-channel video link and two-way audio to ensure located survivors can communicate with operators; and an MSHA-approved multi-gas sensor to monitor air quality.

42 ENGINEERING↗

Notes on Asay Foil Analysis

As is the norm for momentum diagnostic analyses (i.e., both piezopin and Asay foil measurements), we begin by assuming all particles are created instantaneously at the moment of shock breakout; that all particles move collinearly through a perfect vacuum from source to sensor with a long mean free path to scattering (i.e., so that particle velocities and areal masses do not change in flight); and that the particles collide perfectly inelastically with the sensor. We also assume the foil supports have a negligible effect on the trajectory, as has been demonstrated experimentally, and the foil is sufficiently thin that corrections for thick-plate effects (e.g., time delays between particle impacts on the collecting side and velocity changes on the probe side) can be disregarded. We seek an exact analytic treatment of an ideal system that perfectly embodies these characteristics.

36 MATERIALS SCIENCE↗

Refinement of Objective Motion Cueing Criteria Investigation Based on Three Flight Tasks

The objective of this paper is to refine objective motion cueing criteria for commercial transport simulators based on pilots' performance in three flying tasks. Actuator hardware and software algorithms determine motion cues. Today, during a simulator qualification, engineers objectively evaluate only the hardware. Pilot inspectors subjectively assess the overall motion cueing system (i.e., hardware plus software); however, it is acknowledged that pinpointing any deficiencies that might arise to either hardware or software is challenging. ICAO 9625 has an Objective Motion Cueing Test (OMCT), which is now a required test in the FAA's part 60 regulations for new devices, evaluating the software and hardware together; however, it lacks accompanying fidelity criteria. Hosman has documented OMCT results for a statistical sample of eight simulators which is useful, but having validated criteria would be an improvement. In a previous experiment, we developed initial objective motion cueing criteria that this paper is trying to refine. Sinacori suggested simple criteria which are in reasonable agreement with much of the literature. These criteria often necessitate motion displacements greater than most training simulators can provide. While some of the previous work has used transport aircraft in their studies, the majority used fighter aircraft or helicopters. Those that used transport aircraft considered degraded flight characteristics. As a result, earlier criteria lean more towards being sufficient, rather than necessary, criteria for typical transport aircraft training applications. Considering the prevalence of 60-inch, six-legged hexapod training simulators, a relevant question is "what are the necessary criteria that can be used with the ICAO 9625 diagnostic?" This study adds to the literature as follows. First, it examines well-behaved transport aircraft characteristics, but in three challenging tasks. The tasks are equivalent to the ones used in our previous experiment, allowing us to directly compare the results and add to the previous data. Second, it uses the Vertical Motion Simulator (VMS), the world's largest vertical displacement simulator. This allows inclusion of relatively large motion conditions, much larger than a typical training simulator can provide. Six new motion configurations were used that explore the motion responses between the initial objective motion cueing boundaries found in a previous experiment and what current hexapod simulators typically provide. Finally, a sufficiently large pilot pool added statistical reliability to the results.

motion simulation↗

Calibration and characterization of the line-VISAR diagnostic at the HED-HIBEF instrument at the European XFEL

In dynamic-compression experiments, the line-imaging Velocity Interferometer System for Any Reflector (VISAR) is a well-established diagnostic used to probe the velocity history, including wave profiles derived from dynamically compressed interfaces and wavefronts, depending on material optical properties. Knowledge of the velocity history allows for the determination of the pressure achieved during compression. Such a VISAR analysis is often based on Fourier transform techniques and assumes that the recorded interferograms are free from image distortions. In this paper, we describe the VISAR diagnostic installed at the HED-HIBEF instrument located at the European XFEL along with its calibration and characterization. It comprises a two-color (532, 1064 nm), three-arm (with three velocity sensitivities) line imaging system. We provide a procedure to correct VISAR images for geometric distortions and evaluate the performance of the system using Fourier analysis. We finally discuss the spatial and temporal calibrations of the diagnostic. As an example, we compare the pressure extracted from the VISAR analysis of shock-compressed polyimide and silicon.

47 OTHER INSTRUMENTATION↗

The Diagnostics of the External Plasma for the Plasma Rocket

Three regions of plasma temperature/energy are being investigated to understand fully the behavior of the plasma created by the propulsion device and the operation of the RPA. Each type of plasma has a RPA associated with it; i.e. a thermal RPA, a collimated RPA, and a high temperature RPA. Through the process of developing the thermal and collimated RPAs, the proper knowledge and experience has been gained to not only design a high temperature RPA for the plasma rocket, but to understand its operation, results, and uncertainty. After completing a literature search for, reading published papers on, and discussing the operation of the RPA with electric propulsion researchers, I applied the knowledge gained to the development of a RPA for thermal plasma. A design of a thermal RPA was made which compensates for a large Debye length and low ionized plasma. From this design a thermal RPA was constructed. It consists of an outer stainless steel casing, a phenolic insulator (outgases slightly), and stainless steel mesh for the voltage screens. From the experience and knowledge gained in the development of the thermal RPA, a RPA for collimated plasma was developed. A collimated RPA has been designed and constructed. It compensate for a smaller Debye length and much higher ionization than that existing in the thermal plasma. It is 17% of the size of the thermal RPA. A stainless steel casing shields the detector from impinging electrons and ions. An insulating material, epoxy resin, was utilized which has a negligible outgassing. This material can be molded in styrofoam and machined quite nicely. It is capable of withstanding moderately high temperatures. Attached to this resin insulator are inconel screens attached by silver plated copper wire to a voltage supply. All the work on the RPAs and thermal ion source, I performed in the University of Alabama in Huntsville's (UAH) engineering machine shop.

Karr, Gerald R.↗

Production of Medically Desirable Radioisotopes in the EIRENE Molten Salt Reactor

Radioisotopes play a vital role in nuclear medicine, enabling the performance of diagnostic procedures such as Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), in addition to innovative targeted therapies for selectively delivering cytotoxic radiation doses to tumor cells while minimizing damage to healthy tissue [1]. Beta emitting radionuclides such as 90Y and 131I find wide use in radio-immunotherapy, with the radiopharmaceuticals 90Y-ibritumomab tiuxetan (Zevalin®) and 131I-tositumomab (Bexxar®) having received FDA approval for treatment of non-Hodgkin’s lymphoma through targeting the CD20 surface receptor, which is commonly expressed in many B cell non-Hodgkin’s lymphoma subtypes [2, 3]. 90Y has also been successfully applied for treatment of brain tumors [4, 5] and liver cancer [6]. The favorable chelation chemistry of 90Y enables its use with a variety of ligands for the development of radiopharmaceuticals suitable for targeting different carcinoma types [1].

42 - ENGINEERING↗

Niowave Ancillary Systems – FY21: In Partial Fulfillment of the Deliverable Requirement for Niowave Ancillary Systems Support by LANL

Niowave Inc. produces medical radioisotopes within the US. Lead-bismuth eutectic (LBE) is irradiated using an electron beam to produce neutrons that are used in the production of Molybdenum-99 (Mo-99). The medical community relies on a steady supply of Mo-99 which is primarily used in medical diagnostic imaging. The irradiation of LBE results in high temperatures within the molten metal, this work focusses on the design of ancillary systems associated with the liquid metal system. The LBE is initially at a temperature of 200°C and flows over a steel plate to create a waterfall. The electron beam is then aimed at the waterfall to generate neutrons. The peak temperatures of the LBE post irradiation depend on the beam energy of the LINAC. For a 15 MeV and 20 kW beam, the temperatures can range between 300°C and 350°C. The LBE is cycled through the system to create a closed loop that requires the post-irradiation LBE to be cooled back to 200°C. This work focuses on the heat exchanger and condenser system responsible for the cooling of the post-irradiation LBE.

36 MATERIALS SCIENCE↗

End-of-Test Performance and Wear Characterization of NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test

The NASA's Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to quantify the thruster propellant throughput capability. Testing was recently completed in February 2014, with the thruster accumulating 51,184 hours of operation, processing 918 kg of xenon propellant, and delivering 35.5 MN-s of total impulse.As part of the test termination procedure, a comprehensive performance characterization was performed across the entire NEXT throttle table. This was performed prior to planned repairs of numerous diagnostics that had become inoperable over the course of the test. After completion of these diagnostic repairs in November 2013, a comprehensive end-of-test performance and wear characterization was performed on the test article prior to exposure to atmosphere. These data have confirmed steady thruster performance with minimal degradation as well as mitigation of numerous life limiting mechanisms encountered in the NSTAR design. Component erosion rates compare favorably to pretest predictions based on semi-empirical models used for the thruster service life assessment. Additional data relating to ion beam density profiles, facility backsputter rates, facility backpressure effects on thruster telemetry, and modulation of the neutralizer keeper current are presented as part of the end-of-test characterization. Presently the test article for the NEXT LDT has been exposed to atmosphere and placed within a clean room environment, with post-test disassembly and inspection underway.

wear tests↗

Developing time-resolved x-ray diffraction diagnostics at the National Ignition Facility (invited)

As part of a program to measure phase transition timescales in materials under dynamic compression, we have designed new x-ray imaging diagnostics to record multiple x-ray diffraction measurements during a single laser-driven experiment. Our design places several ns-gated hybrid CMOS (hCMOS) sensors within a few cm of a laser-driven target. The sensors must be protected from an extremely harsh environment, including debris, electromagnetic pulses, and unconverted laser light. Another key challenge is reducing the x-ray background relative to the faint diffraction signal. Building on the success of our predecessor (Target Diffraction In Situ), we implemented a staged approach to platform development. First, we built a demonstration diagnostic (Gated Diffraction Development Diagnostic) with two hCMOS sensors to confirm we could adequately protect them from the harsh environment and also acquire acceptable diffraction data. This allowed the team to quickly assess the risks and address the most significant challenges. Here, we also collected scientifically useful data during development. Leveraging what we learned, we recently developed a much more ambitious instrument (Flexible Imaging Diffraction Diagnostic for Laser Experiments) that can field up to eight hCMOS sensors in a flexible geometry and participate in back-to-back shots at the National Ignition Facility (NIF). The design also allows for future iterations, such as faster hCMOS sensors and an embedded x-ray streak camera. The enhanced capabilities of the new instrument required a much more complex design, and the unexpected issues encountered on the first few shots at NIF remind us that complexity has consequences. Our progress in addressing these challenges is described herein, as is our current focus on improving data quality by reducing x-ray background and quantifying the uncertainties of our diffraction measurements.

36 MATERIALS SCIENCE↗

Novel Proppant Logging Technique for Infill Drilling of Unconventional Shale Wells

Summary During the development of an unconventional play, wells are drilled and completed in batches, and depending on the development plans, current and expected energy market trends, as well as other developmental considerations, new wells are drilled and hydraulically fractured later near existing producing laterals. This creates challenges in terms of optimizing resource recovery and reducing interwell communication. A novel approach is proposed that utilizes systematic composite sampling and analysis of drilling mud returns to look for and quantitatively identify sand particles. The workflow involves cleaning, drying, and segregation of samples into sizes of interest to us (size distribution of pumped proppant in offset parent wells). These samples are imaged at a very high resolution and analyzed for grains using characteristic optical imaging properties to classify proppant sand particles using computer vision algorithms. Further analysis, such as elemental compositional analysis, is used to validate the results from the imaging workflow. We present a case study from the Permian Basin, where a new child well was used as a test case to prove this technology at the Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin. We introduce new proppant parameters that help identify sustained proppant zones vs. localized propped fractures. We have used additional diagnostics and data collected at the test site to validate observations from the proppant log and have successfully interpreted significantly propped vs. unpropped zones. A key finding from this test has been the significant proppant transport distances observed away from parent wells. Observable proppant was found at a lateral distance of approximately 425 m for one set of parent wells and more than 915 m for another set of parent wells. While a major limitation of this technique is the sampling rate, given adequate sampling, the proposed technology represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling infill wells. It provides us with unique opportunities to better understand the current state of the reservoir being targeted, including zones that are likely highly drained relative to others, and how the planned hydraulic fracturing of child wells can be improved.

Energy & Fuels↗