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At least 1,567 records · Page 87

Attitude Control and Orbital Dynamics Challenges of Removing the First 3-Axis Stabilized Tracking and Data Relay Satellite from the Geosynchronous ARC

Launched on April 4, 1983 onboard STS 6 (Space Shuttle Challenger), the First Tracking and Data Relay Satellite (TDRS 1) was retired above the Geosynchronous Orbit (GEO) on June 27, 2010 after having provided real-time communications with a variety of low-orbiting spacecraft over a 26-year period. To meet NASA requirements limiting orbital debris 1, a team of experts was assembled to conduct an End-Of-Mission (EOM) procedure to raise the satellite 350 km above the GEO orbit. Following the orbit raising via conventional station change maneuvers, the team was confronted with having to deplete the remaining propellant and passivate all energy storage or generation sources. To accomplish these tasks within the time window, communications (telemetry and control links), electrical power, propulsion, and thermal constraints, a spacecraft originally designed as a three-axis stabilized satellite was turned into a spinner. This paper (a companion paper to Innovative Approach Enabled the Retirement of TDRS 1, paper # 1699, IEEE 2011 Aerospace Conference, March 5-12, 2011 sup 2) focuses on the challenges of maintaining an acceptable spinning dynamics, while repetitively firing thrusters. Also addressed are the effects of thruster firings on the orbit characteristics and how they were mitigated by a careful scheduling of the fuel depletion operations. Periodic thruster firings for spin rate adjustment, nutation damping, and precession of the momentum vector were also required in order to maintain effective communications with the satellite. All operations were thoroughly rehearsed and supported by simulations thus lending a high level of confidence in meeting the NASA EOM goals.

Benet, Charles A.↗

Radiation Belt Environment Model: Application to Space Weather and Beyond

Understanding the dynamics and variability of the radiation belts are of great scientific and space weather significance. A physics-based Radiation Belt Environment (RBE) model has been developed to simulate and predict the radiation particle intensities. The RBE model considers the influences from the solar wind, ring current and plasmasphere. It takes into account the particle drift in realistic, time-varying magnetic and electric field, and includes diffusive effects of wave-particle interactions with various wave modes in the magnetosphere. The RBE model has been used to perform event studies and real-time prediction of energetic electron fluxes. In this talk, we will describe the RBE model equation, inputs and capabilities. Recent advancement in space weather application and artificial radiation belt study will be discussed as well.

Fok, Mei-Ching H.↗

Framework for Development of Object-Oriented Software

The Real-Time Control (RTC) Application Framework is a high-level software framework written in C++ that supports the rapid design and implementation of object-oriented application programs. This framework provides built-in functionality that solves common software development problems within distributed client-server, multi-threaded, and embedded programming environments. When using the RTC Framework to develop software for a specific domain, designers and implementers can focus entirely on the details of the domain-specific software rather than on creating custom solutions, utilities, and frameworks for the complexities of the programming environment. The RTC Framework was originally developed as part of a Space Shuttle Launch Processing System (LPS) replacement project called Checkout and Launch Control System (CLCS). As a result of the framework s development, CLCS software development time was reduced by 66 percent. The framework is generic enough for developing applications outside of the launch-processing system domain. Other applicable high-level domains include command and control systems and simulation/ training systems.

Perez-Poveda, Gus↗

High-Performance 3D Articulated Robot Display

In the domain of telerobotic operations, the primary challenge facing the operator is to understand the state of the robotic platform. One key aspect of understanding the state is to visualize the physical location and configuration of the platform. As there is a wide variety of mobile robots, the requirements for visualizing their configurations vary diversely across different platforms. There can also be diversity in the mechanical mobility, such as wheeled, tracked, or legged mobility over surfaces. Adaptable 3D articulated robot visualization software can accommodate a wide variety of robotic platforms and environments. The visualization has been used for surface, aerial, space, and water robotic vehicle visualization during field testing. It has been used to enable operations of wheeled and legged surface vehicles, and can be readily adapted to facilitate other mechanical mobility solutions. The 3D visualization can render an articulated 3D model of a robotic platform for any environment. Given the model, the software receives real-time telemetry from the avionics system onboard the vehicle and animates the robot visualization to reflect the telemetered physical state. This is used to track the position and attitude in real time to monitor the progress of the vehicle as it traverses its environment. It is also used to monitor the state of any or all articulated elements of the vehicle, such as arms, legs, or control surfaces. The visualization can also render other sorts of telemetered states visually, such as stress or strains that are measured by the avionics. Such data can be used to color or annotate the virtual vehicle to indicate nominal or off-nominal states during operation. The visualization is also able to render the simulated environment where the vehicle is operating. For surface and aerial vehicles, it can render the terrain under the vehicle as the avionics sends it location information (GPS, odometry, or star tracking), and locate the vehicle over or on the terrain correctly. For long traverses over terrain, the visualization can stream in terrain piecewise in order to maintain the current area of interest for the operator without incurring unreasonable resource constraints on the computing platform. The visualization software is designed to run on laptops that can operate in field-testing environments without Internet access, which is a frequently encountered situation when testing in remote locations that simulate planetary environments such as Mars and other planetary bodies.

Powell, Mark W.↗

Real-Time Frequency Response Estimation Using Joined-Wing SensorCraft Aeroelastic Wind-Tunnel Data

A new method is presented for estimating frequency responses and their uncertainties from wind-tunnel data in real time. The method uses orthogonal phase-optimized multi- sine excitation inputs and a recursive Fourier transform with a least-squares estimator. The method was first demonstrated with an F-16 nonlinear flight simulation and results showed that accurate short period frequency responses were obtained within 10 seconds. The method was then applied to wind-tunnel data from a previous aeroelastic test of the Joined- Wing SensorCraft. Frequency responses describing bending strains from simultaneous control surface excitations were estimated in a time-efficient manner.

Grauer, Jared A↗

Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air

The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.

Martos, Borja↗

NASA Tech Briefs, October 2012

Topics discussed include: Detection of Chemical Precursors of Explosives; Detecting Methane From Leaking Pipelines and as Greenhouse Gas in the Atmosphere; Onboard Sensor Data Qualification in Human-Rated Launch Vehicles; Rugged, Portable, Real-Time Optical Gaseous Analyzer for Hydrogen Fluoride; A Probabilistic Mass Estimation Algorithm for a Novel 7-Channel Capacitive Sample Verification Sensor; Low-Power Architecture for an Optical Life Gas Analyzer; Online Cable Tester and Rerouter; A Three-Frequency Feed for Millimeter-Wave Radiometry; Capacitance Probe Resonator for Multichannel Electrometer; Inverted Three-Junction Tandem Thermophotovoltaic Modules; Fabrication of Single Crystal MgO Capsules; Inflatable Hangar for Assembly of Large Structures in Space; Mars Aqueous Processing System; Hybrid Filter Membrane; Design for the Structure and the Mechanics of Moballs; Pressure Dome for High-Pressure Electrolyzer; Cascading Tesla Oscillating Flow Diode for Stirling Engine Gas Bearings; Compact, Low-Force, Low-Noise Linear Actuator; Ultra-Compact Motor Controller; Extreme Ionizing-Radiation-Resistant Bacterium; Wideband Single-Crystal Transducer for Bone Characterization; Fluorescence-Activated Cell Sorting of Live Versus Dead Bacterial Cells and Spores; Nonhazardous Urine Pretreatment Method; Laser-Ranging Transponders for Science Investigations of the Moon and Mars; Ka-Band Waveguide Three-Way Serial Combiner for MMIC Amplifiers; Structural Health Monitoring with Fiber Bragg Grating and Piezo Arrays; Low-Gain Circularly Polarized Antenna with Torus-Shaped Pattern; Stereo and IMU- Assisted Visual Odometry for Small Robots; Global Swath and Gridded Data Tiling; GOES-R: Satellite Insight; Aquarius iPhone Application; Monitoring of International Space Station Telemetry Using Shewhart Control Charts; Theory of a Traveling Wave Feed for a Planar Slot Array Antenna; Time Manager Software for a Flight Processor; Simulation of Oxygen Disintegration and Mixing With Hydrogen or Helium at Supercritical Pressure; A Superfluid Pulse Tube Refrigerator Without Moving Parts for Sub-Kelvin Cooling; Sapphire Viewports for a Venus Probe; The Mobile Chamber; Electric Propulsion Induced Secondary Mass Spectroscopy; and Radiation-Tolerant DC-DC Converters.

Source record↗

NASA Tech Briefs, September 2013

Topics include: ISS Ammonia Leak Detection Through X-Ray Fluorescence; A System for Measuring the Sway of the Vehicle Assembly Building; Fast, High-Precision Readout Circuit for Detector Arrays; Victim Simulator for Victim Detection Radar; Hydrometeor Size Distribution Measurements by Imaging the Attenuation of a Laser Spot; Quasi-Linear Circuit; High-Speed, High-Resolution Time-to-Digital Conversion; Li-Ion Battery and Supercapacitor Hybrid Design for Long Extravehicular Activities; Ultrasonic Low-Friction Containment Plate for Thermal and Ultrasonic Stir Weld Processes; High-Powered, Ultrasonically Assisted Thermal Stir Welding; Next-Generation MKIII Lightweight HUT/Hatch Assembly; Centrifugal Sieve for Gravity-Level-Independent Size; Segregation of Granular Materials; Ion Exchange Technology Development in Support of the Urine Processor Assembly; Nickel-Graphite Composite Compliant Interface and/or Hot Shoe Material; UltraSail CubeSat Solar Sail Flight Experiment; Mechanism for Deploying a Long, Thin-Film Antenna From a Rover; Counterflow Regolith Heat Exchanger; Acquisition and Retaining Granular Samples via a Rotating Coring Bit; Very-Low-Cost, Rugged Vacuum System; Medicine Delivery Device With Integrated Sterilization and Detection; FRET-Aptamer Assays for Bone Marker Assessment, C-Telopeptide, Creatinine, and Vitamin D; Multimode Directional Coupler for Utilization of Harmonic Frequencies from TWTAs; Dual-Polarization, Multi-Frequency Antenna Array for use with Hurricane Imaging Radiometer; Complementary Barrier Infrared Detector (CBIRD) Contact Methods; Autonomous Control of Space Nuclear Reactors; High-Power, High-Speed Electro-Optic Pockels Cell Modulator; Covariance Analysis Tool (G-CAT) for Computing Ascent, Descent, and Landing Errors; Enigma Version 12; Micrometeoroid and Orbital Debris (MMOD) Shield Ballistic Limit Analysis Program; Spitzer Telemetry Processing System; Planetary Protection Bioburden Analysis Program; Wing Leading Edge RCC Rapid Response Damage Prediction Tool (IMPACT2); ISSM: Ice Sheet System Model; Automated Loads Analysis System (ATLAS); Integrated Main Propulsion System Performance Reconstruction Process/Models. Phoenix Telemetry Processor; Contact Graph Routing Enhancements Developed in ION for DTN; GFEChutes Lo-Fi; Advanced Strategic and Tactical Relay Request Management for the Mars Relay Operations Service; Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data; Ionospheric Specifications for SAR Interferometry (ISSI); Implementation of a Wavefront-Sensing Algorithm; Sally Ride EarthKAM - Automated Image Geo-Referencing Using Google Earth Web Plug-In; Trade Space Specification Tool (TSST) for Rapid Mission Architecture (Version 1.2); Acoustic Emission Analysis Applet (AEAA) Software; Memory-Efficient Onboard Rock Segmentation; Advanced Multimission Operations System (ATMO); Robot Sequencing and Visualization Program (RSVP); Automating Hyperspectral Data for Rapid Response in Volcanic Emergencies; Raster-Based Approach to Solar Pressure Modeling; Space Images for NASA JPL Android Version; Kinect Engineering with Learning (KEWL); Spacecraft 3D Augmented Reality Mobile App; MPST Software: grl_pef_check; Real-Time Multimission Event Notification System for Mars Relay; SIM_EXPLORE: Software for Directed Exploration of Complex Systems; Mobile Timekeeping Application Built on Reverse-Engineered JPL Infrastructure; Advanced Query and Data Mining Capabilities for MaROS; Jettison Engineering Trajectory Tool; MPST Software: grl_suppdoc; PredGuid+A: Orion Entry Guidance Modified for Aerocapture; Planning Coverage Campaigns for Mission Design and Analysis: CLASP for DESDynl; and Space Place Prime.

Source record↗

Development, Implementation, and Pilot Evaluation of a Model-Driven Envelope Protection System to Mitigate the Hazard of In-Flight Ice Contamination on a Twin-Engine Commuter Aircraft

Fatal loss-of-control accidents have been directly related to in-flight airframe icing. The prototype system presented in this report directly addresses the need for real-time onboard envelope protection in icing conditions. The combination of prior information and real-time aerodynamic parameter estimations are shown to provide sufficient information for determining safe limits of the flight envelope during inflight icing encounters. The Icing Contamination Envelope Protection (ICEPro) system was designed and implemented to identify degradations in airplane performance and flying qualities resulting from ice contamination and provide safe flight-envelope cues to the pilot. The utility of the ICEPro system for mitigating a potentially hazardous icing condition was evaluated by 29 pilots using the NASA Ice Contamination Effects Flight Training Device. Results showed that real time assessment cues were effective in reducing the number of potentially hazardous upset events and in lessening exposure to loss of control following an incipient upset condition. Pilot workload with the added ICEPro displays was not measurably affected, but pilot opinion surveys showed that real time cueing greatly improved their awareness of a hazardous aircraft state. The performance of ICEPro system was further evaluated by various levels of sensor noise and atmospheric turbulence.

simulation training↗

Autonomous Spacecraft Communication Interface for Load Planning

Ground-based controllers can remain in continuous communication with spacecraft in low Earth orbit (LEO) with near-instantaneous communication speeds. This permits near real-time control of all of the core spacecraft systems by ground personnel. However, as NASA missions move beyond LEO, light-time communication delay issues, such as time lag and low bandwidth, will prohibit this type of operation. As missions become more distant, autonomous control of manned spacecraft will be required. The focus of this paper is the power subsystem. For present missions, controllers on the ground develop a complete schedule of power usage for all spacecraft components. This paper presents work currently underway at NASA to develop an architecture for an autonomous spacecraft, and focuses on the development of communication between the Mission Manager and the Autonomous Power Controller. These two systems must work together in order to plan future load use and respond to unanticipated plan deviations. Using a nominal spacecraft architecture and prototype versions of these two key components, a number of simulations are run under a variety of operational conditions, enabling development of content and format of the messages necessary to achieve the desired goals. The goals include negotiation of a load schedule that meets the global requirements (contained in the Mission Manager) and local power system requirements (contained in the Autonomous Power Controller), and communication of off-plan disturbances that arise while executing a negotiated plan. The message content is developed in two steps: first, a set of rapid-prototyping "paper" simulations are preformed; then the resultant optimized messages are codified for computer communication for use in automated testing.

Controls↗

A Flight-Calibrated Methodology for Determination of Cassini Thruster On-Times for Reaction Wheel Biases

This paper describes a methodology for accurate and flight-calibrated determination of the on-times of the Cassini spacecraft Reaction Control System (RCS) thrusters, without any form of dynamic simulation, for the reaction wheel biases. The hydrazine usage and the delta V vector in body frame are also computed from the respective thruster on-times. The Cassini spacecraft, the largest and most complex interplanetary spacecraft ever built, continues to undertake ambitious and unique scientific observations of planet Saturn, Titan, Enceladus, and other moons of Saturn. In order to maintain a stable attitude during the course of its mission, this three-axis stabilized spacecraft uses two different control systems: the RCS and the reaction wheel assembly control system. The RCS is used to execute a commanded spacecraft slew, to maintain three-axis attitude control, control spacecraft's attitude while performing science observations with coarse pointing requirements, e.g. during targeted low-altitude Titan and Enceladus flybys, bias the momentum of reaction wheels, and to perform RCS-based orbit trim maneuvers. The use of RCS often imparts undesired delta V on the spacecraft. The Cassini navigation team requires accurate predictions of the delta V in spacecraft coordinates and inertial frame resulting from slews using RCS thrusters and more importantly from reaction wheel bias events. It is crucial for the Cassini spacecraft attitude control and navigation teams to be able to, quickly but accurately, predict the hydrazine usage and delta V for various reaction wheel bias events without actually having to spend time and resources simulating the event in flight software-based dynamic simulation or hardware-in-the-loop simulation environments. The methodology described in this paper, and the ground software developed thereof, are designed to provide just that. This methodology assumes a priori knowledge of thrust magnitudes and thruster pulse rise and tail-off time constants for eight individual attitude control thrusters, the spacecraft's wet mass and its center of mass location, and a few other key parameters.

Earth Mean Equatorial↗

Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations

This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks [Scargle 1998]-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piece- wise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by [Arias-Castro, Donoho and Huo 2003]. In the spirit of Reproducible Research [Donoho et al. (2008)] all of the code and data necessary to reproduce all of the figures in this paper are included as auxiliary material.

signal detection↗

TPSAS-NF1676L-12387-DND

Fast-time wake prediction models are semi-empirical, and are designed to predict aircraft wake vortex information behind a generating aircraft. They are developed using theoretical concepts and often calibrated with data obtained from field measurements, laboratory studies, or numerical simulations. They rely upon inputs representing the generating aircraft (such as weight, airspeed, wingspan, lateral position, and altitude) and atmospheric environment (such as ambient winds, turbulence, and temperature lapse rate). Other input may include the type of aircraft (e.g., B-747- 400). Output from these models may include time histories of the wake vortex strength, and position, as well as a prediction of the uncertainties in strength and position. Fast-time models should provide solutions in a fraction of a second, and hence is an enabling technology able to perform in a real-time operational system, such as dynamic spacing systems envisioned by the Aircraft Vortex Spacing System or other Super Density Operations concepts. Other applications of fast-time models include 1) guidance for wake separation standards for new aircraft, 2) optimization of separation standards for existing aircraft, 3) guidance for setting vertical separation standards during cruise, 4) accident reconstructions, and 5) testing of new concepts for safe increases in airport capacity for both single and multiple runway configurations. Fast-time models are based on a number of assumptions which limit their accuracy and range of application. For example, they do not predict the meandering vortex paths that can result from the wake interaction with atmospheric turbulence. However, these models should account for the mean vortex position and may predict the level of uncertainty. This presentation describes a study in which comparative evaluations of fast-time wake transport and decay models were conducted using data sets from previous field programs taken at MEM (1995), DFW (1997, 1999, 2000), and Denver (2005, 2006) airports. These data sets contain, meteorological data, lidar measurements of wake vortices, and the aircraft parameters associated with these vortices.

Fred H Proctor↗

Spacecraft-to-Earth communications for Juno and Mars Science Laboratory critical events

This paper describes the Entry, Descent, and Landing (EDL) Data Analysis (EDA) system. The EDA software supports the real-time interpretation of Multiple Frequency-Shift Keying tones provided by the spacecraft. The objective of this software is to provide communication of status between the spacecraft and the mission personnel on Earth during critical events when low rate telemetry is not possible. Although these communications cannot be used to affect the landing due to the length of time required at these distances, this information is important in the case of a mission failure. Mars Science Laboratory (MSL) will utilize the EDA software during EDL. Juno usage will include deep space maneuvers, Jupiter orbital insertion, and its period reduction maneuver. Results are presented from the Juno tones test. Simulated MSL and Juno signals were also generated and these results are analyzed.

Navarro, Robert↗

Automating Sensor Characterization with Bayesian Optimization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert's time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Cuevas-Zepeda, Julian [Chicago U., KICP; Chicago U↗

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗

Exploration of Real Time Inference for MI-RR Deblending on GPU/TPU Systems

The Fermilab Main Injector (MI) and Recycler Ring (RR) share a common beam loss monitor (BLM) system, making loss events difficult to attribute to their source machine when beam is present in both simultaneously. The Real-time Edge AI for Distributed Systems (READS) project addresses this by deblending BLM readings in real time using machine learning (ML). The current FPGA based implementation meets the sub-3 ms latency requirement but carries a resource intensive hls4ml development cycle, motivating exploration of GPU based deployment. This paper characterizes inference latency on an NVIDIA Jetson Orin Nano and introduces a packet organization scheme for assembling synchronized event frames from seven distributed BLM DAQ streams. Using a Python based DAQ simulation with injected timing jitter in place of unavailable live beam data, the pipeline achieved an average end to end latency of 0.456 ms (σ = 0.122 ms) across 167,000 test frames, comfortably meeting the timing constraint. Early outliers were attributed to TensorRT warm-up rather than steady state limitations, suggesting GPU based inference is a viable alternative to the existing FPGA implementation.

Yu, Kellen [Fermilab; Cornell U.]↗