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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 Simulation of a Reactor, Built Using CrowPis, which are simple and accessible programmable systems of various electronics, as ground stations and a Box containing heaters as the reactor. The goal of this project is to learn various skills and to demonstrate the feasibility of a simulated reactor, utilizing a PID control and wireless connectivity.
We report the results of analytical transmission electron microscopy studies of defects associated with potentialinduced degradation (PID) of a laboratory stressed multicrystalline silicon mini-module. Shunt defects were first identified using dark lock in thermography (DLIT) and scanning electron microscopy (SEM) electron beam induced current (EBIC) imaging. Transmission electron microscopy (TEM) crosssection samples were then prepared of selected shunt defects using conventional focused ion beam (FIB) lift out techniques and examined by TEM and scanning transmission electron microscopy (STEM). The defects were identified as {111} planar defects and compositional mapping of the defects revealed elevated levels of both Na, expected from previous work, and also surprisingly O at some of the defect cores.
A position sensor or controller generates a response signal in existing armature windings of an actuator and detects the response signal to determine the position of the armature. To generate the response signal, the actuator includes a sensor excitation winding near the armature. Two sensor excitation windings can be provided, above and below the armature, to cancel out z components and thus allow for a variable gap. The sensor excitation winding or windings are supplied with an excitation signal to induce the response signal in the armature windings. The response signal is derived by differentially amplifying and frequency filtering a raw output of the armature windings. The response signal is demodulated to determine position. If a position controller rather than a mere sensor is desired, the position signal can be buffered, PID compensated, amplified, and fed back to the armature windings.
The Proton Improvement Project-2 centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line, a critical system that defines the ideal path for the particle beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40°C. The system utilizes an aluminum 36”x36”x0.5” heat plate powered by a MOSFET-based control circuit, delivering approximately 460 W of thermal energy through a resistor array. Real-time temperature feedback is provided by a PT100 Resistance Temperature Detector (RTD), which interfaces with a Proportional–Integral–Derivative (PID) control algorithm to maintain closed-loop temperature regulation. The control signal actively modulates the gate voltage of an N channel MOSFET, dynamically adjusting power delivery in response to deviations from the temperature setpoint. Simulations and LTspice models validate the functionality and responsiveness of the circuit under varying conditions. The prototype has successfully demonstrated stable thermal control, paving the way for integration into the PIP-II infrastructure. The final design will feature an expanded resistor array, as well as communication with a PLC for continuous data acquisition and diagnostics. This work directly supports Fermilab’s broader mission by contributing to the stability and reliability of core accelerator systems, enhancing the precision of particle beam delivery for future physics experiments.
Here we present a method for calculating the TCO sheet resistance of complete thin film modules using EL imaging. The method uses the characteristic decay of the junction voltage over the width of a cell stripe to derive four simple analytic equations for the TCO sheet resistance and the internal and contact resistances. Experimentally, only the module dark JV curve, Jsc-Voc curve, and electroluminescence imaging is required. Unlike previous methods, the internal and contact resistances of the modules are accounted for, and the method does not require curve fitting. The TCO sheet resistances of four 10cm x 10cm amorphous silicon modules are calculated and show excellent agreement with the experimentally measured values.
A fundamental change in the analysis for the accelerated stress testing of thin-film modules is proposed, whereby power changes due to metastability and other effects that may occur due to the thermal history are removed from the power measurement that we obtain as a function of the applied stress factor. In this work, initial thermal treatment of the module is performed before application of the independent variable stress of system voltage so that any temperature-dependent processes (e.g., diffusion) that affect the module power are largely activated beforehand. Secondly, the power of reference modules normalized to an initial state-undergoing the same thermal and light exposure history but without the applied stress factor such as humidity or voltage bias-is subtracted from that of the stressed modules. For better understanding and appropriate application in standardized tests, the method is demonstrated and discussed for potential-induced degradation testing in view of the paralleloccurring but unrelated physical mechanisms that can lead to confounding power changes in the module.
The Belle II barrel region is instrumented with the Time of Propagation (TOP) particle identification system. Due to its mechanical design, the individual TOP modules do not overlap, leaving a gap of around 2 cm between them in the azimuthal direction. This leads to a 6%–9% drop in acceptance, depending on the track’s momentum. We propose a solution to remedy these gaps by instrumenting them with fast silicon detectors to directly measure the time-of-flight of traversing particles. We present here a simulation study discussing the performance requirements and the possible sensor technologies, and we demonstrate that such a project could be realized with novel, fast monolithic CMOS sensors, or alternatively AC-LGAD sensors, both of which are expected to reach MIP timing resolutions of down to 50 ps or better.
The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle.
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The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.
The Proton Improvement Plan 2 (PIP-II) centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line. It is a critical system that defines the ideal path for the beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40 C. Utilizing an actively regulated heating system, a metal-oxide-semiconductor field-effect transistor (MOSFET) based power control circuit which provides input to a controller; forming a closed-loop system that maintains the desired setpoints with high precision.
This paper presents a control co-design (CCD) framework tailored to the hydraulic and mechanical subsystems of hydropower systems, aimed at enhancing their dynamic performance and responsiveness to grid demands. Conventional sequential design approaches often fall short in capturing the coupled interactions between plant dynamics and control objectives. The proposed CCD methodology enables simultaneous optimization of key hydro plant parameters - such as governor settings, penstock characteristics, and valve control - with the control system architecture. Results indicate that both CCD and sequential design approaches achieve comparable transient and steady-state performance, with minor discrepancies arising from differences in their optimized parameters. However, CCD demonstrates a distinct advantage by tripling the water time constant (Tw) while maintaining similar dynamic performance to the sequential approach. This increase in Tw enables optimization of penstock dimensions, as it is directly influenced by penstock design, thereby contributing to overall cost optimization.
To expand the functional capabilities of industrial controllers for systems subject to external disturbances, developments to date are reviewed, and an approach permitting the generation of control signals on the basis of predictions is proposed and tested. The benefits of this approach are assessed. It is best used for large industrial equipment and systems in manufacturing and the oil and gas industry.
The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.
UAM vehicles represent a unique challenge in acoustics because there are a limited number of full-scale datasets that can be used to calibrate and validate prediction models. In addition, acoustics is considered more often in the early design loop as a higher priority concern in UAM vehicle design, whereas with traditional vehicles, acoustics is typically addressed with post-design constraints. This paper will present an approach in design optimization of a proprotor in two flight conditions, hover, and forward flight, with several acoustic objective functions that simulate community response. An adjoint-capable vortex-lattice method (VLM), implemented in VSPAERO, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). In addition, a wing is placed near the proprotor to simulate installation effects on a vehicle’s wing. The influence of rotation rate, chord distribution, twist angle, and sweep on installation, broadband noise, and choice of perception constraint from the design optimization will be shown.
This paper will present an approach in design optimization of a proprotor in a forward flight condition with several acoustic objective functions that simulate community response. An adjoint-capable blade element momentum theory (BEMT), implemented in CCBlade.jl, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). The influence of broadband noise, observer location, and choice of perception constraint on optimized values of rotation rate, chord distribution, and twist angle will be shown. It is determined that broadband self-noise is an influential source noise mechanism in the design optimization when frequency weighting is used to predict the noise at an out-of-plane observer position.
This paper will present an approach in design optimization of a proprotor in a forward flight condition with several acoustic objective functions that simulate community response. An adjoint-capable blade element momentum theory (BEMT), implemented in CCBlade.jl, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). The influence of broadband noise, observer location, and choice of perception constraint on optimized values of rotation rate, chord distribution, and twist angle will be shown. It is determined that broadband self-noise is an influential source noise mechanism in the design optimization when frequency weighting is used to predict the noise at an out-of-plane observer position.