Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cavity optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-objective optimization of CEBAF heat load management and trip rates using AI/ML

The goal of this project is to investigate the use of RL to simultaneously optimize the cryogenic heat load and trip rate of the CEBAF linacs and make it generic to solve multi-objective problems that will enable its application at other Department of Energy (DOE) facilities with similar challenges. The existing approach optimizes the gradient distribution to minimize the trip rate and does not take into account the total heat load. A secondary objective of the project is the develop a framework to correct cavity quality curves (Q-curves) or RF-heat to Gradient relation curves for individual cavities. These curves are currently obtained using historical measurements and may have changed their behavior due to various events. Correction in these curves will allow us to accurately approximate the total RF heat generated by the linacs which is critical for the optimization.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization

Purpose: Robust optimization leads to intensity-modulated proton therapy (IMPT) plans that are less sensitive to uncertainties and superior in terms of organs-at-risk (OARs) sparing, target dose coverage, and homogeneity compared to planning target volume (PTV)-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to both targets and OARs and is also able to compensate for perturbations in dose distributions within targets and OARs caused by uncertainties. In contrast, the traditional PTV-based optimization considers only setup uncertainties and adds a margin only to targets but no margins to the OARs. It also ignores range uncertainty. The purpose of this work is to determine if robustly optimized plans are superior to PTV-based plans simply because the latter do not assign margins to OARs during optimization. Methods: The authors retrospectively selected from their institutional database five patients with head and neck (H and N) cancer and one with prostate cancer for this analysis. Using their original images and prescriptions, the authors created new IMPT plans using three methods: PTV-based optimization, optimization based on the PTV and planning risk volumes (PRVs) (i.e., 'PTV+PRV-based optimization'), and robust optimization using the 'worst-case' dose distribution. The PRVs were generated by uniformly expanding OARs by 3 mm for the H and N cases and 5 mm for the prostate case. The dose-volume histograms (DVHs) from the worst-case dose distributions were used to assess and compare plan quality. Families of DVHs for each uncertainty for all structures of interest were plotted along with the nominal DVHs. The width of the 'bands' of DVHs was used to quantify the plan sensitivity to uncertainty. Results: Compared with conventional PTV-based and PTV+PRV-based planning, robust optimization led to a smaller bandwidth for the targets in the face of uncertainties {l_brace}clinical target volume [CTV] bandwidth: 0.59 [robust], 3.53 [PTV+PRV], and 3.53 [PTV] Gy (RBE){r_brace}. It also resulted in higher doses to 95% of the CTV {l_brace}D{sub 95%}: 60.8 [robust] vs 59.3 [PTV+PRV] vs 59.6 [PTV] Gy (RBE){r_brace}, smaller D{sub 5%} (doses to 5% of the CTV) minus D{sub 95%} {l_brace}D{sub 5%}- D{sub 95%}: 13.2 [robust] vs 17.5 [PTV+PRV] vs 17.2 [PTV] Gy (RBE){r_brace}. At the same time, the robust optimization method irradiated OARs less {l_brace}maximum dose to 1 cm{sup 3} of the brainstem: 48.3 [robust] vs 48.8 [PTV+PRV] vs 51.2 [PTV] Gy (RBE); mean dose to the oral cavity: 22.3 [robust] vs 22.9 [PTV+PRV] vs 26.1 [PTV] Gy (RBE); maximum dose to 1% of the normal brain: 66.0 [robust] vs 68.0 [PTV+PRV] vs 69.3 [PTV] Gy (RBE){r_brace}. Conclusions: For H and N cases studied, OAR sparing in PTV+PRV-based optimization was inferior compared to robust optimization but was superior compared to PTV-based optimization; however, target dose robustness and homogeneity were comparable in the PTV+PRV-based and PTV-based optimizations. The same pattern held for the prostate case. The authors' data suggest that the superiority of robust optimization is not due simply to its inclusion of margins for OARs, but that this is due mainly to the ability of robust optimization to compensate for perturbations in dose distributions within target volumes and normal tissues caused by uncertainties.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Helium refrigeration systems for super-conducting accelerators

Many of the present day accelerators are based on superconducting technology which requires 4.5-K or 2-K helium refrigeration systems. These systems utilize superconducting radio frequency (SRF) cavities and/or superconducting magnets which are packaged into vacuum vessels known as cryo-modules (CM’s). Many of the present day accelerators are optimized to operate primarily at around 2-K, requiring specialized helium refrigeration systems which are cost intensive to produce and to operate. Some of the cryogenic refrigeration system design considerations for these challenging applications are discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Effect of emitters on quantum state transfer in coupled cavity arrays

Over the last decade, conditions for perfect state transfer in quantum spin chains have been discovered and their experimental realizations addressed, as have their extensions to more complex geometries of coupled cavity-emitter arrays. In this paper we further consider such studies and situations in which quantum state transfer can occur with high fidelity, even when the cavity-cavity coupling rates and cavity-emitter interaction rates are comparable. This is accomplished through the development and use of a Monte Carlo approach to the inverse eigenvalue problem, which allows the determination of coupling rates which optimize quantum state transfer fidelity and subsequent time evolution of the polariton wave function through exact diagonalization of the resulting Jaynes-Cummings-Hubbard Hamiltonian. The effect of inhomogeneous emitter locations is also evaluated. Furthermore, our key results include the demonstration that our methodology can be used successfully to establish Hamiltonian parameters for high-fidelity state transfer in more general lattice geometries and excitation number sectors, and also a determination of the effects of fluctuations in those parameters about their optimal values.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Small-Molecule CD4-Mimics: Structure-Based Optimization of HIV-1 Entry Inhibition

We report the optimization, based on computational, thermodynamic, and crystallographic data, of a series of small-molecule ligands of the Phe43 cavity of the envelope glycoprotein gp120 of human immunodeficiency virus (HIV) has been achieved. Importantly, biological evaluation revealed that the small-molecule CD4 mimics (4–7) inhibit HIV-1 entry into target cells with both significantly higher potency and neutralization breadth than previous congeners, while maintaining high selectivity for the target virus. Their binding mode was characterized via thermodynamic and crystallographic studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Selective binding of choline by a phosphate-coordination-based triple helicate featuring an aromatic box

In nature, proteins have evolved sophisticated cavities tailored for capturing target guests selectively among competitors of similar size, shape, and charge. The fundamental principles guiding the molecular recognition, such as self-assembly and complementarity, have inspired the development of biomimetic receptors. In the current work, we report a self-assembled triple anion helicate (host 2) featuring a cavity resembling that of the choline-binding protein ChoX, as revealed by crystal and density functional theory (DFT)-optimized structures, which binds choline in a unique dual-site-binding mode. Here, this similarity in structure leads to a similarly high selectivity of host 2 for choline over its derivatives, as demonstrated by the NMR and fluorescence competition experiments. Furthermore, host 2 is able to act as a fluorescence displacement sensor for discriminating choline, acetylcholine, l-carnitine, and glycine betaine effectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Design of a 140 GHz waveguide notch filter for millimeter-wave receiver module protection in fusion plasma diagnostics

A carefully designed waveguide-based millimeter-wave notch filter, operating at 140 GHz, safeguards plasma diagnostic instruments from gyrotron leakage. Here, utilizing cylindrical cavity resonators with aperture coupling, the filter efficiently resonates 140 GHz wave-power into the TE 11p mode, optimizing various geometrical parameters for practical fabrication and high-yield production. Thorough thermal analysis ensures its ability to handle power. The filter achieves outstanding performance with over 90 dB rejection at 140 GHz while providing low insertion loss over the passband (110–138 GHz), which is ideally suited for system-on-chip approach F-band diagnostic system applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

A NEW DIFFERENTIAL AND ERRANT BEAM CURRENT MONITOR FOR THE SNS* ACCELERATOR

A new Differential and errant Beam Current Monitor (DBCM) is being implemented for both the Spallation Neutron Source's Medium Energy Beam Transport (MEBT) and the Super Conducting Linac (SCL) accelerator sections. These new current monitors will abort the beam when the difference between two toroidal pickups exceeds a threshold. The MEBT DBCM will protect the MEBT chopper target, while the SCL DBCM will abort beam to minimize fast beam losses in the SCL cavities. The new DBCM will also record instances of errant beam, such as beam dropouts, to assist in further optimization of the SNS Accelerator. A software Errant Beam Monitor was implemented on the regular BCM hardware to study errant beam pulses. The new system will take over this functionality and will also be able to abort beam on pulse-to-pulse variations. Because the system is based on the FlexRIO hardware and programmed in LabVIEW FPGA, it will be able to abort beam in about 5 us. This paper describes the development, implementation, and initial test results of the DBCM, as well as errant beam examples.

beam current monitor↗
DOE OSTI2016

Factors Affecting Treatment Outcome in Elderly Head and Neck Cancer Patients: A Retrospective Pilot Study

Head and neck cancer (HNC), the fifth most common cancer worldwide, is a complicated category of diseases comprised of cancers of the oral cavity, oropharynx, nasopharynx, hypopharynx, and larynx. Management of HNC can be very complex, with surgery, chemotherapy, and radiation therapy often used in combination to achieve optimal results. The optimal combination of therapies to maximize patient survival and post-treatment quality of life is yet unclear. Only some prognostic factors for HNC are relatively well understood, whereas others are affected by conflicting results of their significance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Theoretical estimates of maximum fields in superconducting resonant radio frequency cavities: stability theory, disorder, and laminates

Theoretical limits to the performance of superconductors in high magnetic fields parallel to their surfaces are of key relevance to current and future accelerating cavities, especially those made of new higher-Tc materials such as Nb$_3$Sn, NbN, and MgB$_2$. Indeed, beyond the so-called superheating field $H_{\mathcal{sh}}$, flux will spontaneously penetrate even a perfect superconducting surface and ruin the performance. We present intuitive arguments and simple estimates for $H_{\mathcal{sh}}$, and combine them with our previous rigorous calculations, which we summarize. We briefly discuss experimental measurements of the superheating field, comparing to our estimates. We explore the effects of materials anisotropy and the danger of disorder in nucleating vortex entry. Will we need to control surface orientation in the layered compound MgB$_2$? Can we estimate theoretically whether dirt and defects make these new materials fundamentally more challenging to optimize than niobium? Finally, we discuss and analyze recent proposals to use thin superconducting layers or laminates to enhance the performance of superconducting cavities. As a result, flux entering a laminate can lead to so-called pancake vortices; we consider the physics of the dislocation motion and potential re-annihilation or stabilization of these vortices after their entry.

43 PARTICLE ACCELERATORS↗
NASA NTRS2010

U.S. Air Force Research Laboratory's Need for Flow Physics and Control With Applications Involving Aero-Optics and Weapon Bay Cavities

To develop New Flow Control Techniques: a) Knowledge of the Flow Physics with and without control. b) How does Flow Control Effect Flow Physics (What Works to Optimize the Design?). c) Energy or Work Efficiency of the Control Technique (Cost - Risk - Benefit Analysis). d) Supportability, e.g. (size of equipment, computational power, power supply) (Allows Designer to include Flow Control in Plans).

Schmit, Ryan↗
DOE OSTI2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory

Abstract Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Advanced low-beta cavity development for proton and ion accelerators

Recent developments in designing and processing low-beta superconducting cavities at Argonne National Laboratory are very encouraging for future applications requiring compact proton and ion accelerators. One of the major benefits of these accelerating structures is achieving real-estate accelerating gradients greater than 3 MV/m very efficiently either continuously or for long-duty cycle operation (>1%). The technology has been implemented in low-beta accelerator cryomodules for the Argonne ATLAS heavy-ion linac where the cryomodules are required to have real-estate gradients of more than 3 MV/m. In offline testing low-beta cavities with even higher gradients have already been achieved. This paper will review this work where we have achieved surface fields greater than 166 mT magnetic and 117 MV/m electric in a 72 MHz quarter-wave resonator optimized for beta = 0.077 ions.

Heavy Ion Accelerators↗
DOE OSTI2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗
DOE OSTI2024

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗
DOE OSTI2024

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗
DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗
NASA NTRS2004

Small Mercury Ion Clock for On-board Spacecraft Navigation

I.Small Ion Clock Approach and Heritage: a) No lasers, uwave cavities, cryogenics, atomic beams, etc. b) Ions are electrically shuttled between separate optical and microwave traps. II. Each trap is optimized for its task: quadrupole for optical state selection; multi-pole for microwave clock. a) Very good stability shown in USNO. Timescale running "open loop." III. "Open loop" operation means no self-measurements of frequency offsets: (Zeeman, ion temperature,... etc.) a) Fewer parts and procedures, produces stable output continuously. IV. Ion clock is not so sensitive to temperature fluctuations a) Measured u:nshielded temperature coefficient of few 10(exp -15) per C. b) No bulky temperature isolation needed.

Prestage, John D.↗