Engineering topics

Adams, A.

Publications and source records attributed to Adams, A..

5 records

DOE OSTI2025

Object detection with deep learning for rare event search in the GADGET II TPC

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. Here, we present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

Convolutional neural network↗

DOE OSTI2024

Time projection chamber for GADGET II

The established Gaseous Detector with Germanium Tagging (GADGET) detection system is used to measure weak, low-energy 𝛽-delayed proton decays. It consists of the Gaseous Proton Detector equipped with a MICROMEGAS (MM) readout to detect protons and other charged particles calorimetrically, surrounded by the Segmented Germanium Array (SeGA) for high-resolution detection of prompt 𝛾 rays. To upgrade GADGET's Proton Detector to operate as a compact time projection chamber (TPC) for the detection, three-dimensional imaging and identification of low-energy 𝛽-delayed single- and multiparticle emissions mainly of interest to astrophysical studies. A new high granularity MM board with 1024 pads has been designed, fabricated, installed, and tested. A high-density data acquisition system based on generic electronics for TPCs (GET) has been installed and optimized to record and process the gas avalanche signals collected on the readout pads. The TPC's performance has been tested using a 220 Rn 𝛼-particle source and cosmic-ray muons. In addition, decay events in the TPC have been simulated by adapting the attpcroot data analysis framework. Furthermore, a novel application of two-dimensional convolutional neural networks for GADGET II event classification is introduced. The optimization of data throughput is also addressed. The GADGET II TPC is capable of detecting and identifying 𝛼 particles as well as measuring their track direction, range, and energy. The extracted energy resolution of the GADGET II TPC using P10 gas is about 5.4% at 6.288 MeV ( 220 Rn 𝛼 events), computed using charge integration. Based on a systematic simulation study, we estimated the detection efficiency of the GADGET II TPC for protons and 𝛼 particles, respectively. It has also been demonstrated that the GADGET II TPC is capable of tracking minimum-ionizing particles (i.e., cosmic-ray muons). From these measurements, the electron drift velocity was measured under typical operating conditions. In addition to being one of the first generation of micropattern gaseous detectors (MPGDs) to utilize a resistive anode applied to low-energy nuclear physics, the GADGET II TPC will also be the first TPC surrounded by a high-efficiency array of high-purity germanium 𝛾-ray detectors. As a result, the TPC of GADGET II has been designed, fabricated, and tested and is ready for operation at the Facility for Rare Isotope Beams for radioactive-beam-line experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1988

High/variable mixture ratio O2/H2 engine

Vehicle/engine analysis studies have identified the High/Dual Mixture Ratio O2/H2 Engine cycle as a leading candidate for an advanced Single Stage to Orbit (SSTO) propulsion system. This cycle is designed to allow operation at a higher than normal O/F ratio of 12 during liftoff and then transition to a more optimum O/F ratio of 6 at altitude. While operation at high mixture ratios lowers specific impulse, the resultant high propellant bulk density and high power density combine to minimize the influence of atmospheric drag and low altitude gravitational forces. Transition to a lower mixture ratio at altitude then provides improved specific impulse relative to a single mixture ratio engine that must select a mixture ratio that is balanced for both low and high altitude operation. This combination of increased altitude specific impulse and high propellant bulk density more than offsets the compromised low altitude performance and results in an overall mission benefit. Two areas of technical concern relative to the execution of this dual mixture ratio cycle concept are addressed. First, actions required to transition from high to low mixture ratio are examined, including an assessment of the main chamber environment as the main chamber mixture ratio passes through stoichiometric. Secondly, two approaches to meet a requirement for high turbine power at high mixture ratio condition are examined. One approach uses high turbine temperature to produce the power and requires cooled turbines. The other approach incorporates an oxidizer-rich preburner to increase turbine work capability via increased turbine mass flow.

Adams, A.↗

NASA NTRS1973

Design study of RL10 derivatives. Volume 2: Engine design characteristics

The design characteristics of the RL-10 rocket engine are discussed. The results from critical elements evaluation, baseline engine design, parametric and special study tasks are presented. Critical element evaluation established the feasibility of various engine features such as tank head idle, pumped idle, autogenous tank pressurization, and two-phase pumping. Three baseline engines, derived from the RL-10 were conceptually designed. Parametric life and performance data were generated. Special studies were conducted to establish the impact on the engine design of environment, safety, interchangeability, and maintenance.

Adams, A.↗

NASA NTRS1973

Design study of RL10 derivatives. Volume 3, part 1: Preliminary interface control document

The Interface Control Document contains engine information necessary for installation of the baseline RL10 Derivative engines in the Space Tug vehicle. The ICD presents a description of the baseline engines and their operating characteristics, mass and load characteristics, and environmental criteria. The document defines the engine/vehicle mechanical, electrical, fluid and pneumatic interface requirements.

Adams, A.↗