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At least 1,423 records · Page 79

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

Wideband Reconfigurable Harmonically Tuned GaN SSPA for Cognitive Radios

The paper presents the architecture of a wideband reconfigurable harmonically-tuned Gallium Nitrate (GaN) Solid State Power Amplifier (SSPA) for cognitive radios. When interfaced with the physical layer of a cognitive communication system, this amplifier topology offers broadband high efficiency through the use of multiple tuned input/output matching networks. This feature enables the cognitive radio to reconfigure the operating frequency without sacrificing efficiency. This paper additionally presents as a proof-of-concept the design, fabrication, and test results for a GaN inverse class-F type amplifier operating at X-band (8.4 GHz) that achieves a maximum output power of 5.14-W, Power Added Efficiency (PAE) of 38.6, and Drain Efficiency (DE) of 48.9 under continuous wave (CW) operation.

Cognitive↗

Vector-based feedback of continuous wave radiofrequency compression cavity for ultrafast electron diffraction

The temporal resolution of ultrafast electron diffraction at weakly relativistic beam energies (⁠≲100 keV) suffers from space-charge induced electron pulse broadening. We describe the implementation of a radio frequency (RF) cavity operating in the continuous wave regime to compress high repetition rate electron bunches from a 40.4 kV DC photoinjector for ultrafast electron diffraction applications. Active stabilization of the RF amplitude and phase through a feedback loop based on the demodulated in-phase and quadrature components of the RF signal is demonstrated. This scheme yields 144 ± 19 fs RMS temporal resolution in pump–probe studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Meteorological support for space operations: Review and recommendations

The current meteorological support provided to NASA by NOAA, Air Weather Service, and other contractors is reviewed and suggestions are offered for its improvement. These recommendations include improvement in NASA's internal management organizational structure that would accommodate continued improvement in operational weather support, installation of new observing systems, improvement in analysis and forecasting procedures, and the establishment of an Applied Research and Forecasting Facility.

Source record↗

Thermal monitoring, measurement, and control system for a Volatile Condensable Materials (VCM) test apparatus

A thermal monitoring and control concept is described for a volatile condensable materials (VCM) test apparatus where electric resistance heaters are employed. The technique is computer based, but requires only proportioning ON/OFF relay control signals supplied through a programmable scanner and simple quadrac power controllers. System uniqueness is derived from automatic temperature measurements and the averaging of these measurements in discrete overlapping temperature zones. Overall control tolerance proves to be better than + or - 0.5 C from room ambient temperature to 150 C. Using precisely calibrated thermocouples, the method provides excellent temperature control of a small copper VCM heating plate at 125 + or - 0.2 C over a 24 hr test period. For purposes of unattended operation, the programmable computer/controller provides a continual data printout of system operation. Real time operator command is also provided for, as is automatic shutdown of the system and operator alarm in the event of malfunction.

Ives, R. E.↗

ISS Payload Operations Training During the COVID-19 Pandemic: Impacts and Solutions

Introduction: The onset and the protracted duration of the COVID-19 pandemic brought a dramatic and rapid transformation to almost every aspect of humanity in 2020. The world’s space agencies and their missions were not immune to the unpredictable and wide-sweeping changes. One discipline principally affected was mission operations and the various groups supporting that critical function. Mission support teams, especially for complex and crewed missions like the International Space Station (ISS) were forced to rapidly rethink how and where control center staff performed their vital work. Operations training – an essential element to mission ops, had unique hurdles to overcome. Operations training is responsible for preparing astronaut crews for their scientific missions, providing recurring proficiency and currency material to flight controllers, as well as ensuring new team members are ready to join their colleagues on console. Every element of training was impacted by COVID restrictions. From orientation and introductory classes for new controllers, training for scientists and payload developers, to simulations and advanced lessons, critical On the Job Training (OJT) and final evaluations; all aspects faced new challenges. Operations trainers at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, were forced to rethink, retool, and become more efficient with trainees and training resources in order to continue supporting payload operations on the ISS. Impacts and Barriers to Operations Training: The pandemic started in the United States in early March 2020. Immediately, NASA mandated that the support for ISS real-time operations was critical. As a result, physical access to the ISS Payload Operations Center was restricted to only those people supporting console operations. Thus, use of on-site NASA facilities and any trainer to trainee face-to-face interaction was not authorized. Trainers and trainees had to quickly shift to 100% remote learning. In the short term, this was not a problem since NASA had already prepared Information Technology (IT) resources that facilitated remote access to mission resources like classes, documents and teleconferences. However, instructors quickly discovered the classes that they were accustomed to delivering in a large classroom environment did not translate well to remote teaching. The lack of non-verbal communication with the class became a major barrier to instruction. Another significant hurdle to operations training was the mandate that all simulations could only be held remotely. The logistics of planning and executing even small simulations proved to be challenging, almost impossible, due to IT technology and public internet limitations. With simulations essentially stopped, as well as the restrictions on most OJT training, trainees were essentially stopped in their advancement towards certification. An additional barrier that had to be overcome was the formal documentation of the curriculum objectives. Even though NASA had been deliberately transitioning to electronic documents for years, some organizations were still relying on “pen and ink” documents to formalize training completion. The logistics of implementing secure and controlled e-signature documents in a standardized, NASA approved format had to be addressed. Lesson Learned and Efficiencies: Once the various limitations were identified, ISS trainers at MSFC discussed, proposed, and prioritized new options and techniques. Transitioning to all electronic learning materials and certifications was a relevantly easy fix. Teaching courses to large and diverse groups took additional shifts in the NASA training paradigm. Likewise, methods and procedures for preparing astronauts for their missions were forced to be revised. Simulation supervisors and their teams were also forced to find more efficient techniques to provide realistic training experience. Communication and approvals from management was essential. In every case, the ISS payload operations instructors found novel and efficient solutions to all functions listed above. This paper will discuss the factors and solutions payloads operations trainers found to keep scientific research on the ISS flying forward to mission success.

ISS Operations↗

Operando measurement of lattice strain in internal combustion engine components by neutron diffraction

Significance Internal combustion engine components experience extreme thermomechanical cycling during operation, and the continuing need to improve engine efficiency while maintaining or improving reliability drives the development of lightweight materials with improved thermal and mechanical integrity. Understanding the behavior of new materials in dynamic operation requires operando characterization tools, but conventional in situ measurements of material behavior during real engine operation are very limited, and no practical means exist to replicate such extreme dynamics for ex situ study. In this work, we demonstrate that the penetrating power of neutrons can provide noninvasive measurement of lattice strains inside components of a firing engine, enabling the operando study of complex load states and thermal gradients throughout the solid materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Orbital Express Advanced Video Guidance Sensor

In May 2007 the first US fully autonomous rendezvous and capture was successfully performed by DARPA's Orbital Express (OE) mission. Since then, the Boeing ASTRO spacecraft and the Ball Aerospace NEXTSat have performed multiple rendezvous and docking maneuvers to demonstrate the technologies needed for satellite servicing. MSFC's Advanced Video Guidance Sensor (AVGS) is a primary near-field proximity operations sensor integrated into ASTRO's Autonomous Rendezvous and Capture Sensor System (ARCSS), which provides relative state knowledge to the ASTRO GN&C system. This paper provides an overview of the AVGS sensor flying on Orbital Express, and a summary of the ground testing and on-orbit performance of the AVGS for OE. The AVGS is a laser-based system that is capable of providing range and bearing at midrange distances and full six degree-of-freedom (6DOF) knowledge at near fields. The sensor fires lasers at two different frequencies to illuminate the Long Range Targets (LRTs) and the Short Range Targets (SRTs) on NEXTSat. Subtraction of one image from the other image removes extraneous light sources and reflections from anything other than the corner cubes on the LRTs and SRTs. This feature has played a significant role for Orbital Express in poor lighting conditions. The very bright spots that remain in the subtracted image are processed by the target recognition algorithms and the inverse-perspective algorithms, to provide 3DOF or 6DOF relative state information. Although Orbital Express has configured the ASTRO ARCSS system to only use AVGS at ranges of 120 m or less, some OE scenarios have provided opportunities for AVGS to acquire and track NEXTSat at greater distances. Orbital Express scenarios to date that have utilized AVGS include a berthing operation performed by the ASTRO robotic arm, sensor checkout maneuvers performed by the ASTRO robotic arm, 10-m unmated operations, 30-m unmated operations, and Scenario 3-1 anomaly recovery. The AVGS performed very well during the pre-unmated operations, effectively tracking beyond its 10-degree Pitch and Yaw limit-specifications, and did not require I-LOAD adjustments before unmated operations. AVGS provided excellent performance in the 10-m unmated operations, effectively tracking and maintaining lock for the duration of this scenario, and showing good agreement between the short and long range targets. During the 30-m unmated operations, the AVGS continuously tracked the SRT to 31.6 m, exceeding expectations, and continuously tracked the LRT from 8.8 m out to 31.6 m, with good agreement between these two target solutions. After this scenario was aborted at a 10-m separation during remate operations, the AVGS tracked the LRT out 54.3 m, until the relative attitude between the vehicles was too large. The vehicles remained apart for eight days, at ranges from 1 km to 6 km. During the approach to remate in this recovery operation, the AVGS began tracking the LRT at 150 m, well beyond the OE planned limits for AVGS ranges, and functioned as the primary sensor for the autonomous rendezvous and docking.

Howard, Ricky↗

Multiband Reconfigurable Harmonically Tuned Gallium Nitride (GaN) Solid-State Power Amplifier (SSPA) for Cognitive Radios

The paper presents the architecture of a wideband reconfigurable harmonically-tuned Gallium Nitride (GaN) Solid State Power Amplifier (SSPA) for cognitive radios. When interfaced with the physical layer of a cognitive communication system, this amplifier topology offers broadband high efficiency through the use of multiple tuned input/output matching networks. This feature enables the cognitive radio to reconfigure the operating frequency without sacrificing efficiency. This paper additionally presents as a proof-of-concept the design, fabrication, and test results for a GaN inverse Class-F type amplifier operating at X-band (8.4 GHz) that achieves a maximum output power of 5.14-W, Power Added Efficiency (PAE) of 38.6 percent, and Drain Efficiency (DE) of 48.9 percent under continuous wave (CW) operation.

Cognitive↗

Open Circuit Resonant (SansEC) Sensor for Composite Damage Detection and Diagnosis in Aircraft Lightning Environments

Composite materials are increasingly used in modern aircraft for reducing weight, improving fuel efficiency, and enhancing the overall design, performance, and manufacturability of airborne vehicles. Materials such as fiberglass reinforced composites (FRC) and carbon-fiber-reinforced polymers (CFRP) are being used to great advantage in airframes, wings, engine nacelles, turbine blades, fairings, fuselage and empennage structures, control surfaces and coverings. However, the potential damage from the direct and indirect effects of lightning strikes is of increased concern to aircraft designers and operators. When a lightning strike occurs, the points of attachment and detachment on the aircraft surface must be found by visual inspection, and then assessed for damage by maintenance personnel to ensure continued safe flight operations. In this paper, a new method and system for aircraft in-situ damage detection and diagnosis are presented. The method and system are based on open circuit (SansEC) sensor technology developed at NASA Langley Research Center. SansEC (Sans Electric Connection) sensor technology is a new technical framework for designing, powering, and interrogating sensors to detect damage in composite materials. Damage in composite material is generally associated with a localized change in material permittivity and/or conductivity. These changes are sensed using SansEC. Unique electrical signatures are used for damage detection and diagnosis. NASA LaRC has both experimentally and theoretically demonstrated that SansEC sensors can be effectively used for in-situ composite damage detection.

Wang, Chuantong↗

Behavioral Health and Performance Operations at the NASA Johnson Space Center: A Comprehensive Program that Addresses Flight and Spaceflight Duty Adaptability

NASA astronauts on active status require medical certification for aircraft flying duties as well as readiness for long duration spaceflight training, launch to the International Space Station (ISS), and mission continuation during spaceflight operations. Behavioral fitness and adaptability is an inherent component of medical certification at NASA and requires a unique approach that spans the professional life-span of all active astronauts. TOPIC: This presentation will address the Behavioral Health and Performance (BHP) operations program at the Johnson Space Center. Components of BHP operations include astronaut selection, as well as annual, elective, preflight, inflight, and postflight BHP assessments. Each aspect of the BHP operations program will be discussed, with a focus on behavioral fitness determination and resultant outcomes. Specifically, astronaut selection generates a rating of suitability for long duration spaceflight as well as psychiatric qualification; annual, preflight and postflight BHP assessments provoke a decision regarding the presence of any aeromedical concerns; and inflight assessment requires a conclusion pertaining to mission impact. The combination of these elements provide for a unique, comprehensive approach to flight and spaceflight adaptability. APPLICATIONS: Attendees will understand the differing facets of NASA's comprehensive BHP operations program that occurs over the course of an astronaut's career and be able to compare and contrast this to the Adaptability Rating for Military Aviation (ARMA) and proposed models presented by others on this panel.

Beven, G. E.↗

Naval Reactors Facility Environmental Monitoring Report (CY2020)

This report presents the results of the radiological and non-radiological environmental monitoring programs for 2020 at the Naval Reactors Facility (NRF). Current operations at NRF are in compliance with applicable regulations governing use, emission, and disposal of solid, liquid, and gaseous materials. The results obtained from the environmental monitoring programs verify that releases to the environment from operations at NRF did not have any adverse effect on human health or the environment. Evaluation of the environmental data confirms that the operation of NRF continues to have no adverse effect on the environment or the health and safety of the general public. Furthermore, a conservative assessment of radiation exposure to the general public as a result of NRF operations demonstrated that the maximum potential dose received by any member of the public was well below the most restrictive dose limits prescribed by the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the Nuclear Regulatory Commission.

54 ENVIRONMENTAL SCIENCES↗

Naval Reactors Facility Environmental Monitoring Report (CY2019)

This report presents the results of the radiological and non-radiological environmental monitoring programs for 2019 at the Naval Reactors Facility (NRF). Current operations at NRF are in compliance with applicable regulations governing use, emission, and disposal of solid, liquid, and gaseous materials. The results obtained from the environmental monitoring programs verify that releases to the environment from operations at NRF did not have any adverse effect on human health or the environment. Evaluation of the environmental data confirms that the operation of NRF continues to have no adverse effect on the environment or the health and safety of the general public. Furthermore, a conservative assessment of radiation exposure to the general public as a result of NRF operations demonstrated that the maximum potential dose received by any member of the public was well below the most restrictive dose limits prescribed by the US Department of Energy (DOE) and the Nuclear Regulatory Commission.

54 ENVIRONMENTAL SCIENCES↗

Sample-efficient verification of continuously-parameterized quantum gates for small quantum processors

Most near-term quantum information processing devices will not be capable of implementing quantum error correction and the associated logical quantum gate set. Instead, quantum circuits will be implemented directly using the physical native gate set of the device. These native gates often have a parameterization (e.g., rotation angles) which provide the ability to perform a continuous range of operations. Verification of the correct operation of these gates across the allowable range of parameters is important for gaining confidence in the reliability of these devices. In this work, we demonstrate a procedure for sample-efficient verification of continuously-parameterized quantum gates for small quantum processors of up to approximately 10 qubits. This procedure involves generating random sequences of randomly-parameterized layers of gates chosen from the native gate set of the device, and then stochastically compiling an approximate inverse to this sequence such that executing the full sequence on the device should leave the system near its initial state. We show that fidelity estimates made via this technique have a lower variance than fidelity estimates made via cross-entropy benchmarking. This provides an experimentally-relevant advantage in sample efficiency when estimating the fidelity loss to some desired precision. We describe the experimental realization of this technique using continuously-parameterized quantum gate sets on a trapped-ion quantum processor from Sandia QSCOUT and a superconducting quantum processor from IBM Q, and we demonstrate the sample efficiency advantage of this technique both numerically and experimentally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lubricant impacts on piston deposit formation in the Enterprise marine diesel research engine

The impact of lubricant formulation on piston deposits was studied using the Enterprise, a reduced-scale, single-cylinder, two-stroke crosshead marine diesel research engine. The Enterprise engine was specially designed for marine diesel lubricant research, with a custom reduced-scale cylinder lubricant injection system and extensive instrumentation of thermal boundary conditions on both the liner and piston. Lubricant conditions typical of full-scale marine diesel engines are obtained by matching mean piston speed, liner temperature profile, and combustion metrics to realistic values.Piston deposit thicknesses were measured after a set period of operation, with a focus on lubricant-based deposits on the lands and ring grooves, using both optical and contact-based measurement techniques. Engine operation for each lubricant was conducted according to a standardized protocol, with precise control of engine speed and load, cylinder lubricant injection rate, coolant temperatures, and system oil temperature; the liner and piston temperatures are continuously monitored during operation. After operation with each lubricant was completed, the engine was disassembled, and the piston and ring deposits were characterized. The piston was then thoroughly cleaned, and the lubricant system flushed, between each lubricant formulation being evaluated. The impacts on piston deposits of the lubricants being evaluated can thus be accurately quantified and are described herein.

Kaul, Brian↗

Benchmark for Fuel Shuffling and Depletion for Pebble-Bed Reactors

Pebble bed reactors have specific operational characteristics when their fuel-cycle and fueling operations are considered. They are specifically distinguished by other type of nuclear reactor designs by their online fuel recycling scheme, where the fuel elements that have not yet reached discharge burnup can be reloaded and recycled continuously during normal operation. The fuel in a pebble bed reactor is not stationary and stochastically moves through the core once or several times during its lifetime, which allows them to operate without requiring a large excess reactivity hold for the burnup. However, this characteristic of pebble bed reactors introduces challenges in simulation, as each pebble can take many different trajectories through the core, its composition depends on the details of the irradiation history that is unique to its aggregated path through the core. For predicting the safety performance characteristics, such as source term, maximum fuel temperatures and fuel failure rates, etc., it is important to accurately incorporate the movement of pebbles through the core during their lifetime in a multi-physics simulation together with other phenomena. The equilibrium core analysis for pebble bed reactors are performed with multi-physics tools including fuel depletion in a multi pass reload coupled to the fuel movement. Currently, there are only a few legacy multi-physics simulation tools that can implement the pebble flow characteristics and perform equilibrium core analysis for pebble bed reactors. However, there are development efforts on-going under Department of Energy's Nuclear Energy Advanced Modelling and Simulation program and also in private industry for including these capabilities into their modelling and simulation tools. Any new development in the modelling and simulation tools needs to be validated by using tools such as experiments, analytical solutions or code-to-code benchmarks. In this work, a code-to-code benchmark for the equilibrium core analysis capability of pebble bed reactors was developed. Multiple cases were identified to capture different fuel cycle strategies that can be used in PBRs. The results of each case are presented in terms of overall equilibrium core characteristics: the discharge burnup; spatial burnup distribution; spatial isotopic distributions; axial and radial neutron flux distributions and power history of fuel elements per pass through the core for both a prototypical pebble bed High Temperature Gas-cooled Reactor and a prototypical pebble bed Fluoride-salt cooled High temperature Reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗