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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Electrochemical Hydrogen Peroxide Generator

Two-electron reduction of oxygen to produce hydrogen peroxide is a much researched topic. Most of the work has been done in the production of hydrogen peroxide in basic media, in order to address the needs of the pulp and paper industry. However, peroxides under alkaline conditions show poor stabilities and are not useful in disinfection applications. There is a need to design electrocatalysts that are stable and provide good current and energy efficiencies to produce hydrogen peroxide under acidic conditions. The innovation focuses on the in situ generation of hydrogen peroxide using an electrochemical cell having a gas diffusion electrode as the cathode (electrode connected to the negative pole of the power supply) and a platinized titanium anode. The cathode and anode compartments are separated by a readily available cation-exchange membrane (Nafion 117). The anode compartment is fed with deionized water. Generation of oxygen is the anode reaction. Protons from the anode compartment are transferred across the cation-exchange membrane to the cathode compartment by electrostatic attraction towards the negatively charged electrode. The cathode compartment is fed with oxygen. Here, hydrogen peroxide is generated by the reduction of oxygen. Water may also be generated in the cathode. A small amount of water is also transported across the membrane along with hydrated protons transported across the membrane. Generally, each proton is hydrated with 3-5 molecules. The process is unique because hydrogen peroxide is formed as a high-purity aqueous solution. Since there are no hazardous chemicals or liquids used in the process, the disinfection product can be applied directly to water, before entering a water filtration unit to disinfect the incoming water and to prevent the build up of heterotrophic bacteria, for example, in carbon based filters. The competitive advantages of this process are: 1. No consumable chemicals are needed in the process. The only raw materials needed are water and oxygen or air. 2. The product is pure and can therefore be used in disinfection applications directly or after proper dilution with water. 3. Oxygen generated in the anode compartment is used in the electrochemical reduction process; in addition, external oxygen is used to establish a high flow rate in the cathode compartment to remove the desired product efficiently. Exiting oxygen can be recycled after separation of liquid hydrogen peroxide product, if so desired. 4. The process can be designed for peroxide generation under microgravity conditions. 5. High concentrations of the order of 6-7 wt% can be generated by this method. This method at the time of this reporting is superior to what other researchers have reported. 6. The cell design allows for stacking of cells to increase the hydrogen peroxide production. 7. The catalyst mix containing a diquaternary ammonium compound enabled not only higher concentration of hydrogen peroxide but also higher current efficiency, improved energy efficiency, and catalyst stability. 8. The activity of the catalyst is maintained even after repeated periods of system shutdown. 9. The catalyst system can be extended for fuel-cell cathodes with suitable modifications.

Tennakoon, Charles L. K.↗
NASA NTRS2010

Testing to Characterize the Advanced Stirling Radioisotope Generator Engineering Unit

The Advanced Stirling Radioisotope Generator (ASRG), a high efficiency generator, is being considered for space missions. Lockheed Martin designed and fabricated an engineering unit (EU), the ASRG EU, under contract to the Department of Energy. This unit is currently undergoing extended operation testing at the NASA Glenn Research Center to generate performance data and validate life and reliability predictions for the generator and the Stirling convertors. It has also undergone performance tests to characterize generator operation while varying control parameters and system inputs. This paper summarizes and explains test results in the context of designing operating strategies for the generator during a space mission and notes expected differences between the EU performance and future generators.

Lewandowski, Edward↗
NASA NTRS2014

SSL Freeform Generator v1.00

The Orion spacecraft utilizes a system of Compact Unique Identifiers (CUIs) to identify telemetry measurements in the process of communicating with the ground. While avionic systems are still in development, simulation of telemetric data must be used for the development of dependent systems. The SuperScript Language (SSL) developed by Honeywell Aerospace provides users a programming language for simulation of this data. The use of tools that provide SSL generation capabilities at a higher level allows for faster and more efficient generation of simulation waveforms. Previous SSL Generator implementations such as Orion Scripted Interface Generator (OrionSIG) relied on software supported routines to generate simulation points for the SSL scripts. This provided relevant simulation capabilities, but was reduced in flexibility by the available software routines available. For this approach, software supported routines have been entirely dropped. Rather, the user is required to enter their own simulation waveform input. This allows arbitrarily complex functions to be utilized simulated with maximum degree of freedom for the user.: The idea for this version of the SSL Generator was a mapping of arbitrary waveforms to Orion CUI telemetry data. The SSL Generator implemented offers a higher degree of freedom to the user than previous versions while attempting to maintain abstraction from the underlying SSL script and the Orion CUI data types. As such, many mappings of waveforms to CUIs will simply not work. Certain implementation decisions were made to minimize the damage caused by these unintended side-effects, such as saturation of values exceeding the maximum or minimum bounds of the data type. Other details, such as signed values being represented in unsigned data types, present problems which cant be fixed to an acceptable degree of intended behavior without user input. Awareness of the limitations of all layers of the software stack will increase the productivity of the end-user.

telemetry↗
NASA NTRS2016

Three Generations of Tracking and Data Relay Satellite (TDRS) Spacecraft

The current Tracking and Data Relay Satellite configuration consists of nine in-orbit satellites (four first generation, three second generation and two third generation satellites) globally distributed in geosynchronous orbit to provide near continuous data relay service to missions like Hubble Space Telescope and the International Space Station. The 1st generation spacecraft were designed by TRW/Northrop Grumman with their launches of the five spacecraft ranging from 1983 through 1995. The 2nd and 3rd generation spacecraft were designed by Boeing with their launches ranging 2000 - 2002 and 2013 - 2017 respectively. TDRS-3 is now 27 years on orbit, continues to be a capable asset for the TDRS constellation. Lack of need for inclination control combined with large fuel reserves and redundancy on critical elements provides spacecraft that operate well past design life, all of which contributes to expanded TDRS constellation support capabilities. All spacecraft generations have issues. Significant issues will be summarized with the focus on the Boeing related problems. Degradations and failures are continually assessed and provide the foundation for yearly updates to spacecraft reliability models, constellation service projections and deorbit plans (in order to meet NASAs mandate of limiting orbital debris). Even when accounting for degradations and failures, the life expectancy for the Boeing delivered 2nd generation TDRS-8, 9 10 TDRS are anticipated to be 25+ years.

TDRS↗
NASA NTRS2017

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Grauer, Jared A.↗
NASA NTRS2018

Plans and Concepts for a New Generation of RTGs for Planetary Science Missions

Of the six types of radioisotope thermoelectric generators NASA has flown in space, only the Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) is currently available for spaceflight, and it relies on technology first used for RTGs in the 1970s. The MMRTG is a rugged power system capable of delivering 110W at launch. NASA is considering future missions with higher power demands however, and sponsored a study to identify concepts and plans to address those needs. The Director of NASA’s Planetary Sciences Division was briefed on a potential enhancement to the MMRTG in late-2012, just a couple of days after the landing of the Mars Science Laboratory rover, Curiosity, on Mars. NASA subsequently funded system-level engineering and technology maturation tasks for a proposed enhanced MMRTG, or eMMRTG, in fiscal year 2013. There was no plan to build a complete generator, rather the engineering of one, and the transfer of technology from laboratories at the Jet Propulsion Laboratory to industry were begun. NASA has now formed a Project to take the eMMRTG from technology to a qualification unit. This would form the first of a new generation of RTGs in 50 years. NASA has also formed a Project for a Next-Generation RTG concept based upon a study led by this author and a large team. NASA’s Radioisotope Power Systems (RPS) Program set the objective for the study to explore what possible options NASA has for Next-Generation-RTGs. The scope and breadth of the study included many possible destinations within the solar system, and traded a variety of RTG conceptual designs, and risk rated a variety of thermoelectric materials and couple configurations. Requirements were defined for the RTG concepts, a variety of thermoelectric materials were evaluated to find the most mature candidates, and performance was estimated for each RTG concept that could use the most mature of these new thermoelectric materials. The study relied upon mission concepts outlined in the latest Planetary Science Decadal Survey (2011), other more recent mission studies completed throughout the agency, and recent analyses of potential missions to ocean worlds to identify requirements that were not applied to previous RTGs but might prove valuable to these NG-RTGs. RTG concepts with maximal potential utility were identified as being modular and ranging in power output from 50 to 500W. A variety of RTG design concepts with several distinguishing characteristics were formulated. The plans and concepts for a new generation of RTGs (the eMMRTG and NG-RTG) will be discussed.

Woerner, David F.↗
NASA NTRSDate not supplied

In-Situ Electrochemical Generation and Utilization of Hydrogen Peroxide for Disinfection

Disinfection needs to meet personal hygiene requirements at the International Space Station (ISS) is currently accomplished through the use of pre-packaged, disposable, wetted wipes, which represent an appreciable carry-along mass and disposal burden. However, as human missions travel further into the solar system the availability of resources to resupply will be diminished. Therefore, next-generation system should use onboard utilities to create on demand disinfectants, thereby reducing the dependence on earth-based supplies and further eliminating storage and disposal problems. Accordingly, we are developing an in-situ approach to electrochemically generate hydrogen peroxide disinfecting solution utilizing onboard life support supplies (Air/Water) to neutralize surface microorganisms present in closed living systems. As discussed within our 2019 and 2021 ICES papers (ICES-2019-38 and ICES-2021-273), we have continued to improve our TRL by scaling the electrochemical generation production process and validating the system in a zero-gravity parabolic loop flight test. In this paper we will demonstrate a system that can achieve over 1 L of >2 w/w% peroxide per day with DI water and air feeds. The hydrogen peroxide solutions generated were sent to NASA for microbial control property characterization. Overall, the electrochemical peroxide generation system offers a more economical and practical alternative, with the disinfectant being generated on demand and in-situ (using available life support materials of Air/Water); and applied to reusable cloths. The specific application of interest to this program is crew contact surfaces in space vehicles, but this technology could be utilized for waste water disinfection, heat exchanger biofouling remediation, and laundry applications. The peroxide generation system will also be able to address Earth-based needs in various settings such as field hospitals, restaurants, military, warehouses, movie theatres, among many others.

hydrogen peroxide↗
DOE OSTI2023

Beyond 15 MW: A cost of energy perspective on the next generation of drivetrain technologies for offshore wind turbines

Leading wind turbine manufacturers are racing to build larger and more powerful offshore machines. Drivetrain configurations often use a permanent-magnet synchronous generator (PMSG), in either a direct-drive configuration or coupled to a gearbox. With increasing demand for critical rare-earth magnets, new generator technologies are emerging to ensure a stable and secure supply chain. We evaluate three different topologies of radial flux synchronous generators employing high field magnets with reduced or no rare-earth content: a direct-drive interior PMSG (DD-IPMSG), a geared drivetrain combining a medium speed gearbox with a PMSG (MS-PMSG), and a direct-drive low-temperature superconducting generator (DD-LTSG). We develop a conceptual design module for each of these technologies within a larger framework for full turbine design. This provides the fairest comparison between technologies at nominal power ratings from 15-25 MW, which represent the next generation of offshore wind turbines. The analyses show that if operational expenditures (OpEx) are constant across the technologies, MS-PMSG results in the lowest LCOE with reductions of up to 7% relative to DD-IPMSG. DD-LTSG also yields lower LCOE values by 2%-3% for fixed-bottom turbines and 3%-5% with a floating platform. However, results are sensitive to OpEx assumptions, with a mere 10% increase causing the conclusions to shift.

17 WIND ENERGY↗
DOE OSTI2023

Deep generative models for vehicle speed trajectories

Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic trajectories but are subject to the curse of dimensionality. They do not allow to include conditional input variables into the generation process. In this paper, we show how extensions to deep generative models allow accurate and scalable generation. Proposed architectures involve recurrent and feed-forward layers and are trained using adversarial techniques. Our models are shown to perform well on generating vehicle trajectories using a model trained on GPS data from Chicago metropolitan area.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Assessing Climate Change-Induced Variability in Generation Potential and Droughts of Renewable Energy Systems in India

Solar photovoltaic (PV) and wind energy systems are crucial for decarbonizing the electricity sector and achieving climate goals. However, these systems are weather-dependent, and ignoring the potential changes in their generation levels due to climate change could compromise achieving climate targets and meeting future electricity demand. This study evaluates the impact of climate change on the generation potential of wind and solar PV systems in India for three future periods, 2030 (2021-2040), 2050 (2041-2060), and 2070 (2061-2080) compared to the baseline year 2000 (1991-2010), under three emission scenarios: SSP245, SSP370, and SSP585. Solar PV generation levels consistently decline (up to 10 %) across all regions and scenarios. Wind energy shows more pronounced variability (-20 % to 30 %). The South and Southeastern regions of India show improvements in wind potential across all scenarios and time periods. This study also investigated the projected changes in the generation droughts of both energy systems. For solar PV, drought days increase across most regions (exceeding 500 days under SSP370 across the 20-year period). In contrast, wind energy sees a reduction in drought days, especially in parts of South and Southeast India (declines exceeding 50 days across different scenarios). For both energy systems, the patterns of generation drought and generation potential are similar, and indicate that Western and Northern India may be less favorable for the future expansion of solar PV and wind energy, respectively. These results highlight the need to account for the potential impacts in future capacity planning.

14 SOLAR ENERGY↗
DOE OSTI2024

Generative $β$-hairpin design using a residue-based physicochemical property landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the -hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial -hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2023

FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration

Water systems worldwide are experiencing climate change-induced shifts in drought properties like frequency, intensity, and duration, affecting water security and reliability. To develop and test effective drought preparedness plans, researchers often use synthetic weather generators to create hydrological scenarios that explore drought variability beyond historical records. Existing weather generators typically allow users to adjust streamflow statistics like percentiles or temporal correlation but do not directly control drought properties of frequency, intensity, and duration. To fill this gap, we propose FIND (Frequency, INtensity, and Duration) synthetic weather generator. FIND incorporates a standardized drought index to directly and in dependently control drought frequency, intensity, and duration in generated streamflow time series while preserving observed hydrological variability. Use cases for FIND include i) water systems analysis applications that seek to train and test drought strategies under historical and plausible future drought conditions, and ii) bottom-up vulnerability studies relating system vulnerability outcomes to specific changes in drought properties of frequency, intensity, and duration. Here, we demonstrate FIND’s versatility through three experiments: replicating historically observed drought properties, generating streamflow scenarios for multiple sites preserving correlation between their drought conditions, and generating a set of scenarios with direct and independent changes in drought properties. FIND source code is openly available for applications beyond the scope of this paper.

42 ENGINEERING↗
DOE OSTI2022

Projected network performance for multiple isotopes using next-generation xenon monitoring systems

Since about 2000 (Bowyer et al., 1998), radioxenon monitoring systems have been under development and testing for the verification of the Comprehensive Nuclear Test-Ban Treaty (CTBT). Operation of the systems since then has resulted in development of a next-generation of systems that are nearly ready for operational deployment. By 2010, the need to screen out civilian sources was well known (Auer et al., 2010; Saey, 2009), and isotopic ratio approaches were soon considered (Kalinowski et al., 2014) to identify specific sources. New generation systems are expected to improve the ability to verify the absence of nuclear tests by using isotopic ratios when multiple isotopes are detected. In this work, thousands of releases were simulated to compute the global detection probability of 131m Xe, 133m Xe, 133 Xe, and 135 Xe at 39 noble gas systems in the International Monitoring System (IMS) for both current and next-generation systems. Three release scenarios are defined at 1 h, 1 d, and 10 d past a 1 kt TNT equivalent 235U explosion event. Multiple cases using from one part in a million to the complete release of the xenon isotopic activity are evaluated for each scenario. Coverage maps and global integrals comparing current and next-generation monitoring systems are presented showing that next-generation noble gas systems will create measurable improvements in the IMS. The global detection probability for 133 Xe is shown to be strong in all scenarios, but only modestly improved by next-generation equipment. However, the detection probability for 131m Xe and 133m Xe increased to about 50% in different scenarios, providing a second detectable isotope for many events. As anticipated from shorter sampling intervals, the expected number of detecting samples roughly doubled and the expected number of detecting stations rose by approximately 50% for all release scenarios. Thus, it might be anticipated that future events would consist of multiple 133 Xe detections and one or more second isotope detections. In conclusion, signals of this nature should increase detection confidence, tighten release location estimates, improve rejection of civilian signals, and lessen the impacts from individual systems being offline for maintenance or repair reasons.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Heat generation in electric double layer capacitors with neat and diluted ionic liquid electrolytes under large potential window between 5 and 80 °C

Here, this study investigates the effect of temperature on the heat generation and the associated electrochemical phenomena occurring in IL-based EDLCs. The EDLCs consisted of two identical activated carbon electrodes with neat Pyr14TFSI or Pyr14TFSI diluted in propylene carbonate (PC) as electrolytes. The instantaneous heat generation rate at each electrode was measured by isothermal calorimetry between 5 and 80 °C under constant current cycling and potential window of 2.5 V. First, the instantaneous heat generation rate was similar at each electrode in neat IL. However, it was smaller at the negative electrode in diluted IL and featured endothermic dips growing with increasing temperature > 40 °C due to overscreening effects, ion desolvation, and/or decomposition of PC. The irreversible heat generation was similar in each half-cell and decreased with increasing temperature due to the reduction in internal resistance, particularly with neat IL. The irreversible heat generation exceeded Joule heating in all cases, especially at high temperature and low current. This was attributed to ion desorption and charge redistribution in the porous electrodes. Finally, the reversible heat generation for both electrolytes was larger at the positive than at the negative electrode due to the difference in anion and cation sizes.

25 ENERGY STORAGE↗
DOE OSTI2024

Understanding the heat generation mechanisms and the interplay between joule heat and entropy effects as a function of state of charge in lithium-ion batteries

The thermal performance of lithium-ion battery cells is critical for ensuring their safe and reliable operation across various applications. In this study, we employed an isothermal calorimetry method to investigate the heat generation of commercial 18650 lithium-ion battery fresh cells during charge and discharge at different current rates, ranging from 0.05C to 0.5C, and across various temperatures: 20 °C, 30 °C, 40 °C, and 50 °C. Our findings revealed a direct correlation between heat generation and current rates, indicating that higher current rates lead to increased heat generation within the cells. Conversely, we observed that heat generation remained relatively stable as the temperature rose, suggesting that temperature changes within this range may not significantly impact the heat generation of fresh cells during typical operations. Furthermore, our study explored irreversible heat generation, which depends on the applied current and overpotential, using the galvanostatic intermittent titration technique at 0.05C–0.5C and 30 °C. Additionally, electrochemical impedance spectroscopy was performed on the same cells during charge and discharge at 20 °C, 30 °C, and 40 °C to analyze cell impedance. Finally, our results indicated a consistent dependence of impedance on the state of charge and depth of discharge, with a significant increase in impedance observed at the end of the discharge process.

25 ENERGY STORAGE↗
DOE OSTI2022

Synchronization in electric power networks with inherent heterogeneity up to 100% inverter-based renewable generation

The synchronized operation of power generators is the foundation of electric power network stability and a key to the prevention of undesired power outages and blackouts. Here, we derive the conditions that guarantee synchronization in power networks with inherent generator heterogeneity when subjected to small perturbations, and perform a parametric sensitivity analysis to understand synchronization with varied types of generators. As inverter-based resources, which are the primary interfacing technology for many renewable sources of energy, have supplanted synchronous generators in ever growing numbers, the center of attention on associated integration challenges have resided primarily on the role of declining system inertia. Our results instead highlight the critical role of generator damping in achieving a stable state of synchronization. Additionally, we report the feasibility of operating interconnected electric grids with up to 100% power contribution from inverter-based renewable generation technologies. Our study has important implications as it sets the basis for the development of advanced control architectures and grid optimization methods that ensure synchronization and further pave the path towards the decarbonization of the electric power sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗