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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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A system includes a particulate matter (PM) filter with an upstream end for receiving exhaust gas, a downstream end and zones. The system also includes a heating element. A control module selectively activates the heating element to inductively heat one of the zones.
Fact sheet about combining artificial intelligence with variable flow control, direct temperature measurement, and best practices that can reduce cooling energy use by up to 50%.
A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy.
A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.
A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.
LANSCE User Facility is seeing continuing support and investments. The investment will sustain reliable facility operations well into the next decade. As a result, the LANSCE User Facility will continue to be a premier Neutron Science Facility at the Los Alamos National Laboratory.
The SLAC P2 MARX Modulator consists of 32 cells charged in parallel by a -4 kV supply and discharged in series to provide a -120 kV 140 amp 1.7 millisecond pulse. Each cell has a 350 uF main storage capacitor. The voltage on the capacitor will droop approximately 640 volts during each pulse. Each cell will have a boost supply that can add up to 700 V to the cell output. This allows the output voltage of the cell to remain constant within 0.1% during the pulse. The modulator output voltage control is determined by the -4 kV charging voltage. A voltage divider will measure the modulator voltage on each pulse. The charging voltage will be adjusted by the data from previous pulses to provide the desired output. The boost supply in each cell consists of a 700 V buck regulator in series with the main capacitor. The supply uses a lookup table for PWM control. The lookup table is calculated from previous pulse data to provide a constant cell output. The paper will describe the modulator and cell regulation used by the MARX modulator. Measured data from a single cell and three cell string will be included.
This report presents the Technical Program Plan for FY 2018 for the Department of Energy Light Water Reactor Sustainability Program – Advanced Instrumentation, Information, and Control (II&C) Systems Technologies research pathway. A summary of the vision and strategy is provided to explain how this program addresses key issues and barriers for implementing digital instrumentation and control technologies in domestic nuclear power plants. The report describes 20 pilot projects that have been formulated to develop and validate enabling technologies over a 16 year period that will result in digital alternatives to the legacy analog II&C systems in place today. This will allow much needed modernization of these systems to address reliability and obsolescence problems, as well as serve as a platform for substantial operational improvement. The report further describes key project resources and cooperative relationships, including the Electric Power Research Institute, the Nuclear Energy Institute (NEI), the Institute of Nuclear Power Operations (INPO)the Nuclear Energy Institute )NEI), the Institute of Nuclear Power Operations (INPO), the IFE Halden Reactor Project, the Nuclear Regulatory Commission, and industry suppliers, that are instrumental to the success of the program. The report also lists the schedule for all program products, including the titles and report numbers for all published reports under this program.
A transition from analog instrumentation and control (I&C) technologies to digital I&C technologies is taking place for license renewals of existing nuclear power plants and for operating licenses of new advanced reactors. This transition necessitates research on risk and economic assessments of digital I&C technologies to ensure the long-term safety and reliability of vital systems, reduce uncertainty in licensing costs in addition to timeline, support integration of digital I&C systems in the plant, and find the most efficient technology upgrades. Adding redundancy within systems or components is a common means of improving design safety; however, it can also make designs more prone to common-cause failures (CCFs). Introducing diversity into redundant systems or components is a way to mitigate and possibly eliminate CCFs, but it also increases plant complexity and may be costly. The balance between redundancy and diversity remains a challenge for digital I&C systems. This study performs sensitivity and importance analyses for four design architectures of two digital I&C systems—the reactor-trip system and the engineered safety features actuation system. For each system, two architectures are examined, including a redundant, non-diverse configuration and a redundant, diverse configuration. The sensitivity analysis will provide insights on the impact of introducing diversity to system reliability. The importance results will help identify risk-significant and risk-sensitive components and failure modes, which may be good candidates for future design improvement.
Traditionally the methods to increase firearms accuracy, particularly at distance, have concentrated on barrel isolation (free floating) and substantial barrel wall thickening to gain rigidity. This barrel stiffening technique did not completely eliminate barrel movement but the problem was significantly reduced to allow a noticeable accuracy enhancement. This process, although highly successful, came at a very high weight penalty. Obviously the goal would be to lighten the barrel (firearm), yet achieve even greater accuracy. Thus, if lightweight barrels could ultimately be compensated for both their static and dynamic mechanical perturbations, the result would be very accurate, yet significantly lighter weight, weapons. We discuss our development of a barrel reference sensor system that is designed to accomplish this ambitious goal. Our optical fiber-based sensor monitors the barrel muzzle position and autonomously compensates for any induced perturbations. The reticle is electronically adjusted in position to compensate for the induced barrel deviation in real time.
Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, but the set of tools for developing and designing HMIs is still in its infancy. Here we propose that Microsoft Windows Presentation Foundation (WPF) is well suited for many roles in the research and development of HMIs for process control.
Prospects for the development of electric vehicles are considered. Recommendations are made regarding the organization of production by means of up-to-date control and information technologies. To ensure that a manufacturing enterprise remains flexible and competitive in an era of rapidly changing customer requirements, an appropriate information module must be developed and integrated with the enterprise’s information system.
A mathematical model of a gas-turbine unit with a free power turbine is presented. The model can be used to study the start-ups and emergency operation of the unit. Alternatives of the automatic start-up algorithm are considered, and the optimal one for a DYa-59L gas-turbine unit is found.
Materials of the works of several authors who have investigated the effect of turbine-operating regime on the stability of HPP with surge tanks are presented. Anumber of new results are obtained. Analytical relationships that can be used in stability calculations for a number of coefficients are compared with a large amount of actual data.
The excitation regulation system of the ASK-100-4 asynchronous compensator is described. The main modes of operation of the compensators in the Beskudnikovo substation of the 'Mosenergo' JSC are considered. The results of an investigation of an actual sample of an AER-ASC automatic excitation regulator on a computer bench, operating in real time, are presented.
This revised AMO steam tip sheet on installing automatic blowdown controls provide how-to advice for improving industrial steam systems using low-cost, proven practices and technologies.
Navigating through the complex tapestry of technological advancements, "Response Strategy for Hyperparameter attacks of Digital Twin Machine Learning Model in Nuclear Power Plants" stands at the intersection of cybersecurity and nuclear power plant operations, embarking on a journey through the intricacies of securing digital twins against malicious cyber activities. As nuclear power plants progressively integrate digital twin technology and machine learning models to optimize operations and ensure system reliability, they inadvertently expose themselves to a new spectrum of vulnerabilities, notably in the realm of hyperparameter attacks. Hyperparameters, integral in machine learning model tuning and optimal performance of digital twins, have emerged as a target for adversaries aiming to destabilize the predictive capabilities and therefore, the operational accuracy of these digital entities within critical infrastructures like nuclear plants. This paper, therefore, meticulously threads the needle through the development of a robust response strategy, poised to shield these digital reflections against calculated hyperparameter manipulations, ensuring that the digital twin can effectively and securely function as a reliable proxy for its physical counterpart. The ensuing sections delve into the orchestrated maelstrom of multi-rate time-changing intelligent coordinated hyperparameter attacks and the implementation of event-triggered predictive control, laying down a structured, predictive, and responsive framework that safeguards the nexus where the digital and physical realms of nuclear power plants coalesce. The operational integrity of digital twins in nuclear power plants depends critically on the security of machine learning hyperparameters. This study makes two different contributions. First, a decision-based idea known as a multi-rate time changing intelligent coordinated hyperparameter attack is put forth. In this attack, many hyperparameters are repeatedly changed using both random and intelligent optimal techniques by the attacker. These assaults introduce varied rates at different attack steps, compromise various amounts of hyperparameters, and improve stealth and flexibility. Second, a technique is developed for event triggered predictive control to rapidly respond to potential hyperparameter attacks. This control integrates a sliding window framework, retaining a history of previous data points and employing linear regression to predict the next data point from the current dataset. The control gain K is determined using the Lyapunov-Krasovskii method, and subsequently, an action is developed. Finally, the outcome of the simulation demonstrates the viability of the proposed method for defending nuclear power plant digital twins from hyperparameter attacks.
The copolymer of the vinyl chloride-maleic anhydride and silver nano- and microparticle (70 wt %) composition is offered as a conductive adhesive for fixing various chips on the dielectric substrate. The wiring volume resistivity is up to 3.1×10{sup −8} Ohm×m. The adhesive strength of the silver-containing polymer composition (70% of Ag) applied under a shear on the dielectric substrate is 106 N/mm{sup 2}. Adhesive layers obtained from these substances have a high thermal conductivity up to λ = 199.93 W/m×K that depends on the amount of Ag in the polymer composition.