Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Critical”

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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Search for the critical point of strongly-interacting matter in $^{40}$Ar + $^{45}$Sc collisions at 150A Ge V /c using scaled factorial moments of protons

The critical point of dense, strongly interacting matter is searched for at the CERN SPS in $^{40}$Ar + $^{45}$Sc collisions at 150A Ge V /c. The dependence of second-order scaled factorial moments of proton multiplicity distribution on the number of subdivisions of transverse momentum space is measured. The intermittency analysis is performed using both transverse momentum and cumulative transverse momentum. For the first time, statistically independent data sets are used for each subdivision number. The obtained results do not indicate any statistically significant intermittency pattern. An upper limit on the fraction of correlated proton pairs and the power of the correlation function is obtained based on a comparison with the Power-law Model developed for this purpose.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for a critical point of strongly-interacting matter in central \(^{40}\)Ar + \(^{45}\)Sc collisions at 13 A–75 A GeV/c beam momentum

The critical point of strongly interacting matter is searched for at the CERN SPS by the NA61/SHINE experiment in central \(^{40}\)Ar + \(^{45}\)Sc collisions at 13 A, 19 A, 30 A, 40 A, and 75 A GeV/c. The dependence of the second-order scaled factorial moments of proton multiplicity distributions on the number of subdivisions in transverse momentum space is measured. The intermittency analysis uses statistically independent data sets for every subdivision in transverse and cumulative-transverse momentum variables. The results obtained do not indicate the searched intermittent pattern. An upper limit on the fraction of correlated protons and the intermittency index is obtained based on a comparison with the Power-law Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Accelerated Assessment of Critical Infrastructure in Aiding Recovery Efforts During Natural and Human-made Disaster

Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as "Acute Phase" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.

Thakur, Gautam Malviya↗
DOE OSTI2022

The Critical Role of Process Analysis in Chemical Recycling and Upcycling of Waste Plastics

There is an urgent need for new technologies to enable circularity for synthetic polymers, spurred by the accumulation of waste plastics in landfills and the environment and the contributions of plastics manufacturing to climate change. Chemical recycling is a promising means to convert waste plastics into molecular intermediates that can be remanufactured into new products. Given the growing interest in the development of new chemical recycling approaches, it is critical to evaluate the economics, energy use, greenhouse gas emissions, and other life cycle inventory metrics for emerging processes, relative to the incumbent, linear manufacturing practices employed today. Here we offer specific definitions for classes of chemical recycling and upcycling and describe general process concepts for the chemical recycling of mixed plastics waste. We present a framework for techno-economic analysis and life cycle assessment for both closed- and open-loop chemical recycling. Rigorous application of these process analysis tools will be required to enable impactful solutions for the plastics waste problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Critical Barriers to Successful Implementation of Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: A Detailed Study of Low SOC Impedance

We report that earth-abundant, sustainable cathode chemistries based on Mn are increasingly attractive for enabling a broader portfolio of cathode oxides. The well-known class of lithium- and manganese-rich cathodes still represents very viable options. However, despite the important work on understanding the mechanisms of voltage fade, hysteresis, and oxygen activity, relatively little attention has been given to understanding the impedance characteristics of these electrodes. In particular, an anomalous rise in area specific impedance at lower states of charge, as well as overall impedance rise and surface damage due to electrolyte interactions, represent critical barriers to implementation. This work presents a comprehensive study of impedance behavior in cobalt-free, lithium- and manganese-rich electrodes. The use of a robust surface treatment allows for long-term behavior to be probed in the absence of surface damage, capacity loss, and impedance rise due to electrolyte interactions. The anomalous rise in impedance could not be correlated to surface changes, or surface phase formation, but could be directly correlated with the bulk processes of voltage fade and voltage hysteresis. The activated material can be explained as a percolating network of higher-voltage, layered-type sites having facile Li diffusion. Interspersed throughout this network are lower-voltage, disordered sites that represent a significant barrier.

25 ENERGY STORAGE↗
DOE OSTI2022

Critical Barriers to Successful Implementation of Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: The Effect of Particle Morphology

As the search for improved and next-generation cathodes continues, it is clear that a deeper understanding of synthesis–structure–electrochemical property relationships is of critical importance. The effects of primary and secondary particle morphologies on various transition metal oxides have been studied, but new findings are still being reported. To date, few studies have focused on the effects of particle morphologies on Li- and Mn-rich oxides (>50% Mn) and even fewer studies have focused on the influence over key properties such as electrode-level impedance. In this study, we report the effects of particle morphologies on the area-specific-impedance (ASI) and thermal behavior of Li- and Mn-rich oxides. Samples with a fixed, layered–layered–spinel (LLS), composition were synthesized with differing primary morphologies and tested under standardized, full-cell protocols. The results suggest that smaller primary particle size (i.e., higher surface area) leads to lower overall ASI, a delay in the increasing impedance at low states-of-charge (SOCs), and surprisingly, improved thermal behavior.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

The Critical Stack Pressure to Alter Void Generation at Li/Solid-Electrolyte Interfaces during Stripping

The lithium stripping process generates vacancies, which may accumulate as voids and lead to uneven current distribution and dendrite growth in the following plating cycles. A stack pressure is typically required during stripping, but how to optimize the stack pressure is not clear. In this work, extremely lithiophilic Li/Li 2 O and lithiophobic Li/LiF interfaces were used to reveal the combining effect of interface interaction and stack pressure induced lithium creep on the stripping critical current density (CCD). A multiscale simulation scheme with Density Functional Theory (DFT), kinetic Monte Carlo (KMC) simulations, and an analytical model was developed. The analytical model predicted lithiophobic interfaces require a higher stack pressure than lithiophilic interfaces to reach the same CCD. The KMC simulations also showed higher stack pressure is needed at lithiophobic interfaces to accelerate Li vacancy diffusion into the bulk and maintain a flat surface. This stack pressure needs to be high enough to alter the Li forward-and-backward hopping barriers at the interface. This multiscale simulation scheme illustrates the importance to include the chemical-mechanical effects during Li stripping morphology evolution. It can be used to design ideal interlayer coating materials to maintain a flat Li surface during cycling.

25 ENERGY STORAGE↗
DOE OSTI2024

Electrolysis in Chloride Molten Salts for Sustainable Critical Metals Production and Recovery

Critical materials, such as rare-earth metals, are essential to numerous applications, including clean energy; however, the present industrial practices for producing rare-earth metals involve environmentally damaging and thus unsustainable chemical and electrochemical processes. An alternative moderate-temperature chloride-based molten salt electrolysis process can address these issues, providing energy efficient and sustainable metal production. While it is being developed presently for rare-earth electrowinning, one can easily envision its broader application to rare-earth electrorefining and the electrolytic production of high-volume metals like Fe and Al. Presently, these high-volume metals industries account for nearly 10% of global greenhouse gas emissions. Furthermore, the chloride MSE process presents a huge opportunity for truly achieving sustainability if it is developed further for producing Fe, Al, Ti, Mg, and other commodity metals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗
DOE OSTI2022

Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)

Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.

Eseye, Abinet Tesfaye↗
DOE OSTI2022

RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)

RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.

Zhang, Xiangyu↗
DOE OSTI2026

Multi-omic characterization of a soil microbial consortium reveals critical role of succinate and glutamate metabolism during calcium carbonate precipitation

Microbially induced calcium carbonate precipitation (MICP) holds potential for use in soil stabilization and carbon sequestration, with the overall efficiency of the process being a major determinant for use in many environmental and civil engineering applications. While the biogeochemical pathways and enzymes driving MICP are known, the microbial metabolic networks and community dynamics underlying such precipitation remain poorly characterized. To address this gap, we developed a four-member consortium of soil bacteria (Curtobacterium flaccumfaciens, Rhodococcus qingshengii, Microbacterium sp., and Bacillus toyonensis), termed carbon storing consortium - A (CSC-A), that is capable of MICP. Prior work shows that MICP production is higher in CSC-A compared to the sum of carbonate produced by each member, suggesting carbonate production is driven by consortium dynamics. To that end we used a multi-omic integration approach of genomics, transcriptomics, and metabolomics to investigate potential inter-species interactions that may influence the MICP phenotype. Genomic life history characterizations identified evidence of niche specialization by B. toyonensis and Microbacterium, while metatranscriptomic analysis suggests R. qingshengii is a keystone species during growth in urea. By comparing individual species’ metabolomes to the metabolic profile of a shared well of precipitated metabolites, we identified over 200 metabolites predicted to be produced or consumed by CSC-A members. Integrating both data types to search the KEGG reactome highlighted a network centered around glutamine metabolism and branched chain amino acid biosynthesis under regulation during CSC-A growth in urea. Succinate metabolism was also a major node in this network and laboratory assays confirmed that increasing the amount of succinate in the growth medium leads to increased carbonate precipitation by CSC-A, a critical confirmation of our modeling approach. By isolating and identifying the interconnected metabolic components underlying MICP in CSC-A, we identified keystone taxa, metabolites, and pathways important for future optimization of the application of this consortia to carbonate precipitation.

carbon storing consortium - A (CSC-A)↗
DOE OSTI2022

Study of recirculating liquid fuel in a 1D critical stationary system

Several studies have been conducted to investigate the physics of liquid fuel reactors, showing also applications with molten salts. A liquid nuclear fuel implies changes in the neutron balance equation to take into account the precursors' displacement and the emission of delayed neutrons in a different position than at the original fission. This requires to upgrade the computer codes normally used to calculate nuclear reactors using only solid fuel. In this work, we revisit a simple problem with liquid fuel, which is proposed for the verification of the numerical solutions obtained by advanced computer codes. This problem studies criticality with constant coefficients, thus neglecting thermal feedback. We elaborate on the analytical solution of the problem, deriving also a generalized eigenvalue problem by finite-volume integration over the cells of a discretized mesh to study the evolution of the dominance ratio with fuel velocity. Finally, we investigate the influence of the fuel velocity on the reactivity of the system. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Sensitivity analyses of a homogeneous model and a RZ model of the MYRRHA reactor in its critical configuration

Two homogenized models of the MYRRHA (Multi-purpose hybrid Research Reactor for High-tech Applications) reactor in its critical configuration are presented in this study. Both models will be verified by comparing the main reactor parameters (K{sub eff}, β{sub eff} and Λ) with those of the heterogeneous model and a sensitivity analysis will be performed. A sensitivity analysis of some important parameters related to reactivity, namely the vacuum coefficient, the Doppler and the power peaking factors, is also presented. The study of the vacuum coefficient has been carried out by analyzing two possible scenarios: 50% vacuum in the coolant (lead bismuth eutectic) and 100%, obtaining a list of the 10 reactions and nuclides that most affect the k{sub eff} value. With respect to the Doppler coefficient, it will be seen that a 300 degree increase in fuel temperature (starting at 800 K) results in a reduction of the total reactivity of the system by 134 pcm.. Finally, the map of the power peaking factors will be shown, as well as a sensitivity analysis. For making the sensitivity calculations Serpent-2 reactor physics Monte Carlo code has been used and JEFF-3.3 library has been chosen in order to continue with the OECD/NEA WPEC SG46 work evaluating the nuclear data of this library. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Lead isotopic compositions of airborne particulates collected from snow and from dry deposition in the East River Watershed, Colorado and at the Southern Sierra Critical Zone Observatory, California

The data set consists of lead (Pb) isotopic ratios (206Pb/207Pb and 208Pb/207Pb, as well as 206Pb/204Pb, 207Pb/204Pb, 208Pb/204Pb) for particulate samples collected from snow and dry deposition. This was part of a study (O’Day et al. 2020) that was looking at the speciation of phosphorous in splits of these samples to evaluate the flux and bio-availability of phosphorous to the mountain sites in the study. The Pb isotopic data allow sourcing of long-range transported Pb, specifically the fraction of Pb sourced in Asia, and so a comparison of the relative distances of PM sources between the high and low elevation sites. Samples were collected at the East River Watershed, CO (dry deposition collected over Sept.-Oct. 2016, show sampling winter 2017) and at the Southern Sierra Critical Zone Observatory (dry deposition collected over Sept-Nov 2016, July-Sept 2017, June-July 2017). The data includes Pb concentration data, as well as calculated fraction of the Pb sourced in Asia. This data set was published in part in O’Day et al. (2020) Phosphorus Speciation in Atmospherically Deposited Particulate Matter and Implications for Terrestrial Ecosystem Productivity. ES&T, https://dx.doi.org/10.1021/acs.est.9b06150

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Criticality Accident Response

The document outlines procedures and priorities for Radiation Protection personnel response should a nuclear criticality accident occur.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

PNNL Measurement Results for the 2018 FlatTop Criticality Nuclear Accident Dosimetry Exercise at the Nevada National Security Site (IER-253)

The Pacific Northwest National Laboratory (PNNL) participated in the FlatTop exercise IER-253 at the National Nuclear Security Site (NNSS) during the week of May 21, 2018. This report summarizes the measurements of the personal nuclear accident dosimeters (PNAD). Additionally, portable survey instrument readings and measurements of the simulated biological samples are included. The FlatTop exercise (IER-253) tested only PNADs and did not include fixed nuclear accident dosimeters (FNAD). Previous PNAD results obtained in 2016 at the Godiva-IV exercise IER-148 were summarized in PNNL Measurement Results for the 2016 Criticality Accident Dosimetry Exercise at the Nevada National Security Site IER-148 (PNNL-26497). The results clearly indicated that the previous dose conversions were a historical legacy of the Hanford Site and corresponded closer to kerma dose (or first collision dose, and not to Hp(10) dose). The technical basis for PNAD dose was based on the Godiva-IV exercise and documented in A New Dose Calculation Methodology for New PNAD and FNAD Designs at PNNL (PNNL-27023). The configuration of the PNAD was described in these two documents. The FlatTop exercise was the first time PNNL tested this new dose calculation methodology. Results were generally favorable with some results conservatively over reported that fell above the performance criteria. The reported gamma dose results fell non-conservatively low because only the default parameters obtained from the Godiva-IV exercise were used, and because the OSL gamma dosimeter has an energy dependency. The results from the simulated biological samples were also favorable, and in several cases conservatively over reported.

61 RADIATION PROTECTION AND DOSIMETRY↗