Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “error of commission”

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 73 records · Page 4

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Task Decomposition in Human Reliability Analysis

In the probabilistic safety assessments (PSAs) used in the nuclear industry, human failure events (HFEs) are determined as a subset of hardware failures, namely those hardware failures that could be triggered by human action or inaction. This approach is top-down, starting with hardware faults and deducing human contributions to those faults. Elsewhere, more traditionally human factors driven approaches would tend to look at opportunities for human errors first in a task analysis and then identify which of those errors is risk significant. The intersection of top-down and bottom-up approaches to defining HFEs has not been carefully studied. Ideally, both approaches should arrive at the same set of HFEs. This question remains central as human reliability analysis (HRA) methods are generalized to new domains like oil and gas. The HFEs used in nuclear PSAs tend to be top-down— defined as a subset of the PSA—whereas the HFEs used in petroleum quantitative risk assessments (QRAs) are more likely to be bottom-up—derived from a task analysis conducted by human factors experts. The marriage of these approaches is necessary in order to ensure that HRA methods developed for top-down HFEs are also sufficient for bottom-up applications.

error of commission↗

Lattice Commissioning Stretgy Simulation for the B Factory

To prepare for the PEP-II turn on, we have studied one commissioning strategy with simulated lattice errors. Features such as difference and absolute orbit analysis and correction are discussed. To prepare for the commissioning of the PEP-II injection line and high energy ring (HER), we have developed a system for on-line orbit analysis by merging two existing codes: LEGO and RESOLVE. With the LEGO-RESOLVE system, we can study the problem of finding quadrupole alignment and beam position (BPM) offset errors with simulated data. We have increased the speed and versatility of the orbit analysis process by using a command file written in a script language designed specifically for RESOLVE. In addition, we have interfaced the LEGO-RESOLVE system to the control system of the B-Factory. In this paper, we describe online analysis features of the LEGO-RESOLVE system and present examples of practical applications.

43 PARTICLE ACCELERATORS↗

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗

I'll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets

Big data workflows often require the assembly and exchange of complex, multi-element datasets. For example, in biomedical applications, the input to an analytic pipeline can be a dataset consisting thousands of images and genome sequences assembled from diverse repositories, requiring a description of the contents of the dataset in a concise and unambiguous form. Typical approaches to creating datasets for big data workflows assume that all data reside in a single location, requiring costly data marshaling and permitting errors of omission and commission because dataset members are not explicitly specified. We address these issues by proposing simple methods and tools for assembling, sharing, and analyzing large and complex datasets that scientists can easily integrate into their daily workflows. These tools combine a simple and robust method for describing data collections (BDBags), data descriptions (Research Objects), and simple persistent identifiers (Minids) to create a powerful ecosystem of tools and services for big data analysis and sharing. We present these tools and use biomedical case studies to illustrate their use for the rapid assembly, sharing, and analysis of large datasets.

Chard, Kyle↗

Optimizing Residential HVAC Systems: Evaluating How the Usage of Smart Diagnostic Tools for Quality Installation and Commissioning Impacts System Performance and HVAC Contractor Businesses

The adoption of digital quality installation and fault detection tools has the potential to transform the $14 billon residential heating, ventilating, and air conditioning (HVAC) service and installation industry. Increased market penetration can be accelerated by providing an increased understanding of the energy and economic value proposition of the usage of these tools. In tandem with energy and HVAC system performance impact research and analysis, the Southface Team investigated the economic business implications for HVAC service and installation contractors adopting the use of measureQuick (mQ), a smart diagnostic app that aids in quality installation and fault detection and works agnostically with Bluetooth-enabled HVAC technician tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Relative Accuracy Assessment of LANDSAT-4 MSS and TM Data for Level 1 Land Cover Inventory

Digital data for the Washington, D.C. scene from the LANDSAT-4 Multispectral Scanner (MSS) and the LANDSAT-4 Thematic Mapper (TM) are compared. Classification success for the TM and MSS data sets was determined by a per pixel comparison with digitized ground verification data (GVD). These GVD were comprised of Level I land cover (developed, agriculture, forest, water, wetlands, and barren) for four USGS 7.5-minute topographic quadrangle maps. Classification accuracy was computed as an average value and for each cover type. Accuracy was expressed two ways: (1) as the percent correspondence with GVD (% correct) and (2) as the percent correspondence relative to both the GVD and LANDSAT classification schemes. Errors of omission and commission associated with the LANDSAT classifications were also computed. Specific results are discussed.

Middleton, E. M.↗

Relative Accuracy Assessment of LANDSAT-4 MSS and TM Data for Level 1 Land Cover Inventory

Digital data for the Washington, DC scene simultaneously acquired by the LANDSAT-4 Multispectral Scanner (MSS) and the LANDSAT-4 thematic mapper (TM) was compared. Classification success for the TM and MSS data sets was determined by a per pixel comparison with digitized ground verification data (GVD). These GVD were comprised of Level 7 land cover (developed, agriculture, forest, water, wetlands, and barren) for four USGS 7.5 minute topographic quadrangle maps. The relative improvement in classification success for TM was between 11% and 14%, or about a factor of 1.3, for these data. This represents a meaningful improvement in accuracy for Level 7 land cover categorization for TM relative to MSS, particularly when errors of omission and commission were considered.

Middleton, E. M.↗

Combining Information on Multiple Detection Techniques to Estimate the Effect of Patent Foramen Ovale on Susceptibility to Decompression Illness

The assembly and the maintenance of the International Space Station is expected to require hundreds of extravehicular excursions (EVA's) in the next 10 years. During an EVA, in order to allow movement and bending of limbs, spacesuit pressures are reduced to about 4.3 psi. as compared with about 14.7 psi. for normal atmospheric pressure at sea level. However, the exposure of astronauts to reduced pressures in spacesuits, is conducive to fonnation and growth of gas bubbles within venous blood or tissues, which could cause decompression illness (DCI), a pathology best known to occur among deep-sea divers when they return to the surface. To reduce the risk of DCI, astronauts adjust to the reduced pressure in stages for a prolonged time known as a "pre-breathe" period prior to their extravehicular activity. Despite the use of pre-breathe protocols, an increased risk of DCI can arise for about 25% of humans who have a small hole, known as a patent foramen ovale (PFO), between two chambers of the heart. The atrial septum's fossa oval is, an embryological remnant of a flap between the septae primum and secundum allows fetal right atrial blood to pass into the left atrium, and usually closes after birth (Hagen, et al,. 1984). If fusion does not occur, a valve-like opening, the foramen ovale persists between the two atria. It has been suggested that astronauts with PFO's might be at greater risk of stroke or other serious neurological DCI because bubbles from a venous site may traverse a PFO, travel to the aorta and then enter the cerebral circulatory system causing a stroke (Figure 1). Astronauts are not now screened for PFO's, however consideration is being given to doing so. Here, we study three main methods abbreviated here as "ITE", "TCD" and "TEE", for detecting PFO's in living subjects. All involve the introduction of bubbles into a vein, immediately after which a sensory probe attempts to detect the bubbles in systemic circulation. Presence of the injected bubbles in the systemic circulation is indicative of a PFO. More detailed descriptions are given after the explanation of PFO's under Figure I. Even if a true PFO affects the risk of DCI, there remains a question of how effective screening would be if the detection method has errors of omission and/or commission. Of the three methods studied here, TEE is the "gold standard", matching autopsy results with near-perfect sensitivity and specificity (Schneider, et al. , 1996). However TEE is also the most difficult method to implement, requiring an internal esophagal probe, and is therefore not widely used. Currently, the easiest to use and most common PFO detection method is TTE, which uses an external chest probe. This method has a specificity of near 100%, but suffers from a low sensitivity rate (about 30%). More recently, TCD has been developed, which uses ultrasound probes to detect the presence of bubbles in cerebral arteries. Studies indicate that TCD is quite effective, having a sensitivity of about 91% and a specificity of about 93% (Droste, et al., 1999) when applied correctly, however implementation is difficult and requires considerable training.

Feiveson, Alan H.↗

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Earth System Data Record↗

SU-E-T-367: Optimization of DLG Using TG-119 Test Cases and a Weighted Mean Approach

Purpose: Optimization of the dosimetric leaf gap (DLG) is an important step in commissioning the Eclipse treatment planning system for sliding window intensity-modulated radiation therapy (SW-IMRT) and RapidArc. Often the values needed for optimal dose delivery differ markedly from those measured at commissioning. We present a method to optimize this value using the AAPM TG-119 test cases. Methods: For SW-IMRT and RapidArc, TG-119 based test plans were created using a water-equivalent phantom. Dose distributions measured on film and ion chamber (IC) readings taken in low-gradient regions within the targets were analyzed separately. Since DLG is a single value per energy, SW-IMRT and RapidArc must be considered simultaneously. Plans were recalculated using a linear sweep from 0.02cm (the minimum DLG) to 0.3 cm. The calculated point doses were compared to the measured doses for each plan, and based on these comparisons an optimal DLG value was computed for each plan. TG-119 cases are designed to push the system in various ways, thus, a weighted mean of the DLG was computed where the relative importance of each type of plan was given a score from 0.0 to 1.0. Finally, SW-IMRT and RapidArc are assigned an overall weight based on clinical utilization. Our routine patient-QA (PQA) process was performed as independent validation. Results: For a Varian TrueBeam, the optimized DLG varied with σ = 0.044cm for SW-IMRT and σ = 0.035cm for RapidArc. The difference between the weighted mean SW-IMRT and RapidArc value was 0.038cm. We predicted utilization of 25% SW-IMRT and 75% RapidArc. The resulting DLG was ~1mm different than that found by commissioning and produced an average error of <1% for SW-IMRT and RapidArc PQA test cases separately. Conclusion: The weighted mean method presented is a useful tool for determining an optimal DLG value for commissioning Eclipse.

60 APPLIED LIFE SCIENCES↗

Rapid Commissioning of Large Machine Tools Using Finite Element-Based Correction of Geometric Errors

Large computer numerical control (CNC) machine tools derive their stiffness from monolithic cast iron bases or weldments that are sometimes integral to machine motion systems like box ways or guideways. However, the sheer size of castings and even floor flatness deviations result in dimensional errors in these systems, which manifest as machine motion errors. Typical geometric alignment processes rely on an iterative approach, where measurements are taken to assess alignment (straightness, squareness, and parallelism), followed by adjustment of the machine supports (fixators or leveling pads), which can take weeks even for an experienced operator. Conversely, a novel method is proposed to shorten the correction time by eliminating the trial-and-error process in favor of a more deterministic approach guided by a finite element (FE) method. A feasibility study is conducted on a CNC polymer hybrid machine, with a steel weldment frame, supported by six leveling pads. An FE model of the frame is utilized to obtain recommended leveling pad adjustments, based on measurement of machine errors taken using a laser tracker. After a single adjustment cycle, measurements reveal that geometric errors of the machine tool are reduced from 2.22 mm of flatness deviation to 0.32 mm, achieving an 85.6% reduction. Furthermore, the entire process including measurement, adjustment, and assessment is completed in just 6 h by two operators who are not professional service engineers. In conclusion, this methodology demonstrates feasibility for scaling up, especially to large, high-precision CNC machine tools with bases mounted by fixators, offering the capability for bidirectional adjustment.

42 ENGINEERING↗

Optimizing the accuracy of a helical diode array dosimeter: A comprehensive calibration methodology coupled with a novel virtual inclinometer

Purpose: The goal of any dosimeter is to be as accurate as possible when measuring absolute dose to compare with calculated dose. This limits the uncertainties associated with the dosimeter itself and allows the task of dose QA to focus on detecting errors in the treatment planning (TPS) and/or delivery systems. This work introduces enhancements to the measurement accuracy of a 3D dosimeter comprised of a helical plane of diodes in a volumetric phantom. Methods: We describe the methods and derivations of new corrections that account for repetition rate dependence, intrinsic relative sensitivity per diode, field size dependence based on the dynamic field size determination, and positional correction. Required and described is an accurate ''virtual inclinometer'' algorithm. The system allows for calibrating the array directly against an ion chamber signal collected with high angular resolution. These enhancements are quantitatively validated using several strategies including ion chamber measurements taken using a ''blank'' plastic shell mimicking the actual phantom, and comparison to high resolution dose calculations for a variety of fields: static, simple arcs, and VMAT. A number of sophisticated treatment planning algorithms were benchmarked against ion chamber measurements for their ability to handle a large air cavity in the phantom. Results: Each calibration correction is quantified and presented vs its independent variable(s). The virtual inclinometer is validated by direct comparison to the gantry angle vs time data from machine log files. The effects of the calibration are quantified and improvements are seen in the dose agreement with the ion chamber reference measurements and with the TPS calculations. These improved agreements are a result of removing prior limitations and assumptions in the calibration methodology. Average gamma analysis passing rates for VMAT plans based on the AAPM TG-119 report are 98.4 and 93.3% for the 3%/3 mm and 2%/2 mm dose-error/distance to agreement threshold criteria, respectively, with the global dose-error normalization. With the local dose-error normalization, the average passing rates are reduced to 94.6 and 85.7% for the 3%/3 mm and 2%/2 mm criteria, respectively. Some algorithms in the convolution/superposition family are not sufficiently accurate in predicting the exit dose in the presence of a 15 cm diameter air cavity. Conclusions: Introduction of the improved calibration methodology, enabled by a robust virtual inclinometer algorithm, improves the accuracy of the dosimeter's absolute dose measurements. With our treatment planning and delivery chain, gamma analysis passing rates for the VMAT plans based on the AAPM TG-119 report are expected to be above 91% and average at about 95% level for {gamma}(3%/3 mm) with the local dose-error normalization. This stringent comparison methodology is more indicative of the true VMAT system commissioning accuracy compared to the often quoted dose-error normalization to a single high value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-J-45: Design and Study of An In-House Respiratory Gating Phantom Platform for Gated Radiotherapy

Purpose: The main purpose of this work was to develop an in-house low cost respiratory motion phantom platform for testing the accuracy of the gated radiotherapy system and analyze the dosimetric difference during gated radiotherapy. Methods: An in-house respiratory motion platform(RMP) was designed and constructed for testing the targeting accuracy of respiratory tracking system. The RMP consist of acrylic Chest Wall Platform, 2 DC motors, 4 IR sensors, speed controller circuit, 2 LED and 2 moving rods inside the RMP. The velocity of the movement can be varied from 0 to 30 cycles per minute. The platform mounted to a base using precision linear bearings. The base and platform are made of clear, 15mm thick polycarbonate plastic and the linear ball bearings are oriented to restrict the platform to a movement of approximately 50mm up and down with very little friction. Results: The targeting accuracy of the respiratory tracking system was evaluated using phantom with and without respiratory movement with varied amplitude. We have found the 5% dose difference to the PTV during the movement in comparison with stable PTV. The RMP can perform sinusoidal motion in 1D with fixed peak to peak motion of 5 to 50mm and cycle interval from 2 to 6 seconds. The RMP was designed to be able to simulate the gross anatomical anterior posterior motion attributable to respiration-induced motion of the thoracic region. Conclusion: The unique RMP simulates breathing providing the means to create a comprehensive program for commissioning, training, quality assurance and dose verification of gated radiotherapy treatments. Create the anterior/posterior movement of a target over a 5 to 50 mm distance to replicate tumor movement. The targeting error of the respiratory tracking system is less than 1.0 mm which shows suitable for clinical treatment with highly performance.

60 APPLIED LIFE SCIENCES↗

FACET Tolerances for Static and Dynamic Misalignments

The Facility for AdvancedAccelerator and Experimental Tests (FACET) at the SLAC National Accelerator Laboratory is designed to deliver a beam with a transverse spot size on the order of 10 {micro}m x 10 {micro}m in a new beamline constructed at the two kilometer point of the SLAC linac. Commissioning the beamline requires mitigating alignment errors and their effects, which can be significant and result in spot sizes orders of magnitude larger. Sextupole and quadrupole alignment errors in particular can introduce errors in focusing, steering, and dispersion which can result in spot size growth, beta mismatch, and waist movement. Alignment errors due to static misalignments, mechanical jitter, energy jitter, and other physical processes can be analyzed to determine the level of accuracy and precision that the beamline requires. It is important to recognize these effects and their tolerances in order to deliver a beam as designed.

43 PARTICLE ACCELERATORS↗

Overview of NSTX Upgrade Initial Results and Modelling Highlights

The National Spherical Torus Experiment (NSTX) has undergone a major upgrade, and the NSTX Upgrade (NSTX-U) Project was completed in the summer of 2015. NSTX-U first plasma was subsequently achieved, diagnostic and control systems have been commissioned, H-Mode accessed, magnetic error fields identified and mitigated, and the first physics research campaign carried out. During 10 run weeks of operation, NSTX-U surpassed NSTX-record pulse-durations and toroidal fields, and high-performance ~1MA H-mode plasmas comparable to the best of NSTX have been sustained near and slightly above the n=1 no-wall stability limit and with H-mode confinement multiplier H98y2 above 1. Transport and turbulence studies in L-mode plasmas have identified the coexistence of at least two ion-gyro-scale turbulent micro-instabilities near the same radial location but propagating in opposite (i.e. ion and electron diamagnetic) directions. These modes have the characteristics of ion-temperature gradient and micro-tearing modes, respectively, and the role of these modes in contributing to thermal transport is under active investigation. The new second more tangential neutral beam injection was observed to significantly modify the stability of two types of Alfven Eigenmodes. Improvements in offline disruption forecasting were made in the areas of identification of rotating MHD modes and other macroscopic instabilities using the Disruption Event Characterization and Forecasting (DECAF) code. Lastly, the Materials Analysis and Particle Probe (MAPP) was utilized on NSTX-U for the first time and enabled assessments of the correlation between boronized wall conditions and plasma performance. These and other highlights from the first run campaign of NSTX-U are described.

Alfven Eigenmodes↗

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴ speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously previously impossible with conventional tools while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴× speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously—previously impossible with conventional tools—while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗